KR102128398B1 - Method and apparatus for fast wireless localization of high accuracy - Google Patents

Abstract

A high-accuracy high-speed wireless positioning method and apparatus, which generates a pattern of change in at least one signal strength received from at least one fixed node until a first time point, and a distribution pattern of signal strength in an area where a mobile node is located The part having the pattern most similar to the change pattern of the signal strength up to the first time point in the map of the form is found, and the initial position of the mobile node is based on the similarity between the change pattern of the signal strength up to the first time point and the extracted part Is set, the portion having the pattern most similar to the change pattern of the signal strength up to the second time point is searched for based on the initial position set in the map, and the pattern most similar to the change pattern of the signal strength up to the second time point By determining the location of the mobile node using the location of the map indicated by the portion having the mobile node, the location of the mobile node can be measured quickly and accurately.

Description

Method and apparatus for fast wireless localization of high accuracy}

A wireless positioning method and apparatus for estimating a location of a mobile node using a wireless signal.

The Global Navigation Satellite System (GNSS) is a system for estimating the location of moving objects around the globe using radio waves from satellites orbiting space orbits. It is widely used in navigation devices such as ships and aircraft. Examples of GNSS include the Global Positioning System (GPS) in the United States, GLONASS in Russia, Galileo in Europe, and Quasi-Zenith Satellite System (QZSS) in Japan. However, GNSS has a problem that positioning is impossible in indoor spaces where radio waves transmitted from satellites cannot reach, and positioning accuracy in the city center is severely deteriorated due to radio wave blocking and reflection by high-rise buildings.

Recently, automakers around the world and global companies such as Google and Intel are focusing on research and development of autonomous vehicles. Although some autonomous driving performance has been achieved in the outdoors, GNSS's autonomous positioning is still far away, due to the inability to locate indoors. In order to solve the problems of the GNSS, a lot of attention has been focused on a wireless positioning technology for estimating a location of a user or a vehicle using a wireless signal existing in an indoor space. Wireless positioning technology is currently commercialized and serviced, but the positioning accuracy is very low compared to GNSS, and various types of wireless positioning technology are under development.

Wireless communication may be classified into short range wireless communication and wide area wireless communication. Typical examples of short-range wireless communication include Wi-Fi, Bluetooth, and Zigbee, and typical examples of wide-area wireless communication are 3G (3rd Generation), 4G (4th Generation), and Laura (Lora). And the like. LTE (Long Term Evolution) is a type of 4G wireless communication. Short-range signals such as Bluetooth and ZigBee are not suitable for positioning due to the characteristics that temporarily occur and disappear according to the needs of users in the indoor space. Currently, it is known that Wi-Fi signals and LTE signals are distributed in most indoors.

Accordingly, a Wi-Fi Positioning System (WPS) that performs positioning using a Wi-Fi signal in the 2.4 GHz band has been spotlighted. Examples of the positioning method using the Wi-Fi signal include a triangulation technique and a fingerprint technique. The triangulation technique estimates the position by measuring the received signal strength (RSS) of three or more access points (APs) and converting it to a distance. However, in indoor spaces, the attenuation, reflection, and diffraction of radio signals are caused by walls, obstacles, and people in buildings. not.

For this reason, the fingerprint technique is mainly used in indoor spaces. This technique constructs a radio map by dividing the indoor space into a grid structure and collecting and database signal strength values in each unit area. In such a state that the radio map is constructed, the strength of the signal received at the user's location is compared with the data of the radio map to estimate the user's location. This technique has the advantage that the positioning accuracy is very high compared to the triangulation technique because it collects data reflecting the spatial characteristics of the room. It has been reported that the wireless environment is good and the indoor space is densely divided to collect more signals and the positioning accuracy increases, which can be improved up to 2-3 meters.

The fingerprint technique performs relatively accurate positioning when there is little difference between the signal strength collected at the time of constructing the radio map and the signal strength collected at the time of performing positioning. However, changes in the wireless environment, such as signal interference between communication channels that occur frequently in the real world, expansion of access points, and failures or obstacles, lead to the collection of signal strength that is different from the data of the radio map constructed in the past. This will seriously affect the accuracy. Accordingly, various attempts have been made to improve positioning accuracy by applying KNN (K-Nearest Neighbor), particle filter, etc. to the fingerprint technique.

First of all, due to the nature of short-range wireless communication, Wi-Fi signals are distributed only in a part of the city. It has inherent limitations. LTE signals are evenly distributed throughout the indoor and outdoor areas, but there are limitations in improving positioning accuracy due to the wide area where the change in signal strength is not large. As a result, positioning services using LTE signals remain at a level that roughly informs the user's location and still have many problems to be used for vehicle navigation systems or autonomous driving where positioning errors can lead to accidents.

The position of the mobile node can be quickly and accurately measured by preventing a case where a pattern in a region where the mobile node is not actually located is incorrectly colored in a pattern similar to a change pattern of signal strength received from the fixed node, and particularly, the execution of wireless positioning starts. It is to provide a wireless positioning method and apparatus capable of elevating the position accuracy of a mobile node to a vehicle navigation system or a certain level available for autonomous driving within a very short time. In addition, it is to provide a recording medium readable by a computer recording a program for executing the above-described wireless positioning method on a computer. It is not limited to the technical problems as described above, and another technical problem may be derived from the following description.

A wireless positioning method according to an aspect of the present invention includes the steps of generating a change pattern of at least one signal strength received from at least one fixed node until a first time point; Detecting a portion having a pattern most similar to a change pattern of signal strength up to the first viewpoint in a map in the form of a distribution pattern of signal strength in an area where the mobile node is located; Setting an initial position of the mobile node on the basis of the similarity between the pattern of change in signal strength up to the first time point and the extracted portion; Generating a change pattern of at least one signal strength received from at least one fixed node until a second time point; Finding out a portion of the map having a pattern most similar to a change pattern of signal strength up to the second viewpoint based on the initial position; And determining the location of the mobile node using the location of the map indicated by the portion having the pattern most similar to the pattern of change in signal strength up to the second time point.

The change pattern of the at least one signal strength may be a change pattern of the at least one signal strength represented by a continuous sequence of the strength of at least one signal received multiple times at a plurality of relative positions of the mobile node estimated at the plurality of viewpoints. Can.

The wireless positioning method further includes estimating a location of the map indicated by a portion having a pattern most similar to a change pattern of signal strength up to the first time point as the location of the mobile node, and setting the initial location In the step, the initial position can be set by selecting the estimated position of the mobile node as the initial position based on the similarity between the pattern of change in signal strength up to the first time point and the extracted part.

The step of setting the initial position includes parts in the map that are compared to a pattern of changes in signal intensity up to the first point in the process of finding a portion having a pattern most similar to the pattern of change in signal intensity up to the first point in time. And an initial position of the mobile node based on a plurality of similarity change patterns between the signal intensity change patterns up to the first time point.

The wireless positioning method further includes estimating a location of the map indicated by a portion having a pattern most similar to a change pattern of signal strength up to the first time point as the location of the mobile node, and setting the initial location The step may set the initial position by calculating the reliability of the estimated position of the mobile node based on the variation pattern of the plurality of similarities, and selecting the estimated position of the mobile node as the initial position according to the position reliability. have.

The setting of the initial position is an index inversely proportional to the similarity between the pattern of change in signal intensity up to the first time point and the extracted part, and the difference between the pattern of change in signal intensity up to the first time point and the extracted part. A corresponding correlation distance may be calculated, and an initial position of the mobile node may be set based on the calculated correlation distance.

The wireless positioning method further includes estimating a location of a map indicated by a portion having a pattern most similar to a change pattern of signal strength up to the first time point as the location of the mobile node, and setting the initial location The step may set the initial position by selecting the estimated position of the mobile node as the initial position based on the calculated correlation distance.

The step of setting the initial position includes parts in the map that are compared to a pattern of changes in signal intensity up to the first point in the process of finding a portion having a pattern most similar to the pattern of change in signal intensity up to the first point in time. And calculating a plurality of correlation distances corresponding to differences between patterns of change in signal strength up to the first point in time; Generating a variation pattern of the calculated plurality of correlation distances; And selecting a position of the estimated mobile node as an initial position of the mobile node based on the change pattern of the plurality of correlation distances.

The step of selecting the initial position may include detecting a lowest peak and a lower peak of the plurality of correlation distance variation patterns; Calculating a reliability of a position of the estimated mobile node based on a ratio of the detected lowest peak and difference peak; And if the reliability is higher than a reference value, selecting the estimated location of the mobile node as the initial location. In calculating the reliability, the reliability may be calculated by dividing the value of the detected difference peak by the value of the detected lowest peak.

The pattern of change in signal strength up to the first time point is a pattern of a geometric surface shape that graphs a change in signal strength up to the first time point according to a relative change in the position of the mobile node, and the first pattern The step of finding a portion having a pattern most similar to the change pattern of signal strength up to the point of view is most similar to the surface shape of the pattern of geometric surface shape graphing the change of signal strength up to the first point in the map. The portion of the surface having the shape can be retrieved.

The step of finding a portion having a pattern most similar to the change pattern of the signal strength up to the second time point may include a plurality of peaks detected in the change pattern of the signal strength up to the second time point and a plurality of peaks detected in the map. By comparing the plurality of peaks that are most similar to the plurality of peaks detected in the map among the plurality of peaks detected in the change pattern of the signal strength up to the second time point based on the initial position in the map, the method The portion having the pattern most similar to the change pattern of the signal strength up to the second time point may be found.

The step of determining the location of the mobile node is a location of a map indicated by a portion having the pattern most similar to the pattern of change in signal strength up to the second time point, and uses the location of occurrence of the plurality of similar peaks found in step 630. To determine the location of the mobile node.

The step of finding a portion having a pattern most similar to the pattern of change in signal strength up to the second time point is the pattern most similar to the pattern of change in signal strength up to the second time point, using the initial position as the starting point of color search in the map It is possible to find the part having.

According to another aspect of the present invention, there is provided a computer-readable recording medium recording a program for executing the wireless positioning method on a computer.

A wireless positioning apparatus according to another aspect of the present invention includes a pattern generator configured to generate a change pattern of at least one signal strength received from at least one fixed node until a first time point; A signal comparator for detecting a portion having a pattern most similar to a change pattern of signal strength up to the first viewpoint in a map in the form of a distribution pattern of signal strength in an area where the mobile node is located; An initial position setting unit configured to set an initial position of the mobile node based on a variation pattern of signal strength up to the first point of time and a similarity between the extracted parts; And a location processor configured to determine the location of the mobile node using a location of a map indicated by a portion having a pattern most similar to a change pattern of signal strength up to a second time point, and based on the initial location in the map. As a result, a portion having a pattern most similar to the change pattern of signal strength up to the second time point is found.

Within a map in the form of a distribution pattern of signal intensity in a region where a mobile node is located, a portion having a pattern most similar to the change pattern of the signal intensity up to the first time point is found, and a change pattern of the signal intensity up to the first time point and The initial position of the mobile node is set based on the similarity between the extracted parts, and the part having the pattern most similar to the change pattern of the signal strength up to the second time point based on the initial position set in the map is found in the map. The pattern most similar to the change pattern of signal strength from to the second time point can be quickly and accurately searched. The location of the mobile node can be quickly and accurately measured by determining the location of the mobile node using the location of the map indicated by the portion having the pattern most similar to the pattern of change in signal strength up to the second point of time. As a result, a high-accuracy high-speed positionless positioning method and apparatus can be provided.

According to the wireless positioning method of the present invention, after the start of the wireless positioning device, the steps of the wireless positioning method are continuously repeated, so that the data size of the change pattern of the signal strength received from the fixed node is gradually increased. When the data size of the signal intensity change pattern is small, the accuracy of radio positioning decreases as the ability to distinguish a surface shape matching this from the map decreases. The present invention is based on the similarity between the pattern of change in signal strength up to a certain point and the similarity between the extracted parts, and the pattern most similar to the pattern of change in signal strength from the point in time on the map to the point in time after that point on the basis of the initial position of the mobile node. The pattern of the region where the mobile node is not actually located is blocked by detecting the pattern in the region where the pattern most similar to the pattern of the variation of the signal strength is unlikely to exist by finding out the portion having the change of the signal strength received from the fixed node It is possible to prevent a case in which color is incorrectly patterned.

As described above, even when the data size of the signal intensity change pattern used for wireless positioning is small, it is possible to prevent a case where the pattern of the region where the mobile node is not actually located is incorrectly colored in a pattern similar to the signal intensity change pattern. Accordingly, the location accuracy of the mobile node can be increased to a certain level or more that can be used for a vehicle navigation system or autonomous driving within a very short time after the start of the wireless positioning of the present invention. Particularly, when the position of a mobile node is estimated by using a radio signal with little change in signal strength over a large area, such as an LTE signal, if the data size of the change pattern of the signal strength used for radio positioning is small, the mobile node There is a high probability that the pattern of the region where is not actually located is incorrectly colored in a pattern similar to the change pattern of the signal strength received from the fixed node. The present invention can provide a positioning service with very high accuracy at the beginning of the execution of wireless positioning even when the position of a mobile node is estimated using a wireless signal with little change in signal strength over a large area, such as an LTE signal. .

Due to signal interference between communication channels, expansion of access points, changes in radio environment such as failures or obstacles, or noise, a signal strength different from the signal strength collected at the time of radio map construction may occur. In this case, the variation pattern of the signal strength received from the fixed node includes the measured signal strength, and thus the similarity between the variation pattern of the signal strength and the extracted portion, that is, the position reliability of the mobile node estimated according to the present invention. Will be low. In this case, the initial position of the mobile node is not set in this case, that is, the initial position is not updated, and thus the pattern of the region where the mobile node is not actually located changes in signal strength received from the fixed node. It is possible to prevent a case in which color is wrongly colored with a pattern similar to the pattern. The effects are not limited to the above, and other effects may be derived from the following description.

1 is a block diagram of a wireless communication system according to an embodiment of the present invention.
2 is a configuration diagram of a wireless positioning device of the mobile node 1 shown in FIG. 1.
3 is a flowchart of a wireless positioning method according to an embodiment of the present invention.
FIG. 4 is a detailed flowchart of step 220 illustrated in FIG. 3.
5 is a view for explaining the pattern forming principle in step 320 of FIG. 3.
FIG. 6 is a diagram illustrating a three-dimensional spatial coordinate system for generating a pattern of change in signal strength used for wireless positioning in this embodiment.
7 is a diagram showing the accumulation of pattern data used for wireless positioning in the present embodiment in a table form.
8 is a diagram illustrating an example in which a change pattern of signal strength used in wireless positioning of the present embodiment is generated.
9-10 are diagrams illustrating examples in which the absolute position of the mobile node 1 is estimated according to the wireless positioning algorithm of the present embodiment.
11 is a diagram illustrating an example of a pattern of change in signal strength received by a vehicle passing through a tunnel section.
12 is a contrast diagram of the signal change pattern generated in step 320 and the signal distribution pattern received in step 450 shown in FIG. 3.
13 is a diagram illustrating an example in which a change pattern of signal intensity is flattened by the peak detector 21 shown in FIG. 2.
FIG. 14 is a detailed flowchart of step 630 shown in FIG. 3.
15 is an exemplary view of speed estimation of the speed processing unit 23 shown in FIG. 2.
16 is a view showing an example of position error correction in step 650 shown in FIG.
17 is a detailed flowchart of step 530 shown in FIG. 3.
18-20 are diagrams illustrating an example of a change pattern of the surface correlation distance generated in step 532 shown in FIG. 17.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. Hereinafter, all mobile objects that are targeted for positioning, such as a mobile phone carried by a user and a navigation system mounted on a vehicle and moved, will be collectively referred to as a “mobile node”. In addition, it is fixedly installed in a certain area, such as an access point (AP, access point) of a Wi-Fi network, a base station of an LTE network, and a repeater that amplifies and retransmits a wireless signal to relay wireless communication of a mobile node. It will be collectively referred to as "fixed node" to encompass communication devices. In addition, a radio frequency (RF) signal transmitted from a fixed node will be simply referred to as a "signal".

An embodiment of the present invention to be described below relates to a wireless positioning method and apparatus for providing a positioning service using a wireless signal such as a Wi-Fi signal, a Long Term Evolution (LTE) signal, etc., in particular, an area where a mobile node is not actually located. The position of the mobile node can be measured quickly and accurately by preventing the case where the pattern of the signal is incorrectly colored in a pattern similar to the change pattern of the signal strength received from the fixed node, and in particular, within a very short time after the start of the radio positioning. The present invention relates to a wireless positioning method and apparatus capable of elevating position accuracy to a certain level or higher that can be used for a vehicle navigation system or autonomous driving. Hereinafter, the wireless positioning method and the wireless positioning device will be briefly referred to as "wireless positioning method" and "wireless positioning device".

1 is a block diagram of a wireless communication system according to an embodiment of the present invention. Referring to FIG. 1, the wireless communication system according to the present embodiment includes a plurality of mobile nodes 1, a plurality of fixed nodes 2, and a positioning server 3. Each of the plurality of mobile nodes 1 is carried by a user or mounted on a vehicle, and performs wireless communication with other nodes through at least one kind of wireless communication network. In general, each mobile node 1 performs wireless communication through at least two types of wireless communication networks, for example, a Wi-Fi network and an LTE network. Each of the plurality of fixed nodes 2 relays wireless communication of each mobile node 1 so that each mobile node 1 can access the wireless communication network and perform wireless communication with other nodes. The fixed node may be an access point when the mobile node 1 performs wireless communication through a Wi-Fi network, and the fixed node may be a base station when performing wireless communication through an LTE network. The positioning server 3 provides each mobile node 1 with a part of the radio map required for wireless positioning in this embodiment.

2 is a configuration diagram of a wireless positioning device of the mobile node 1 shown in FIG. 1. Referring to FIG. 2, the wireless positioning device of the mobile node 1 shown in FIG. 1 includes a wireless communication unit 10, a sensor unit 20, a buffer 30, an initial position setting unit 40, and a scanning unit 11 ), signal processing unit 12, relative position estimation unit 13, domain conversion unit 14, pattern generation unit 15, cluster selection unit 16, map loader 17, signal comparison unit 18, It consists of an absolute position estimation unit 19, a peak detection unit 21, a peak comparison unit 22, a speed processing unit 23, and a position processing unit 24. Those of ordinary skill in the art to which this embodiment belongs may be implemented with hardware that provides specific functions, or a combination of memory, processor, bus, etc. in which software providing specific functions is recorded. It can be understood that it may. Each of the above-described components is not necessarily implemented in separate hardware, and several components may be implemented by a combination of common hardware, for example, a processor, memory, and bus.

As described above, the mobile node 1 may be a smart phone carried by a user or a navigation system mounted in a vehicle. The embodiment illustrated in FIG. 2 relates to a wireless positioning device. In addition to the configuration of the wireless positioning device shown in FIG. 2, if another configuration of a smartphone or another configuration of a navigation system is shown in FIG. 2, features of the present embodiment may be blurred. Because it is omitted. Those of ordinary skill in the art to which this embodiment belongs may understand that other components may be added in addition to the components shown in FIG. 2 when the mobile node 1 is implemented as a smart phone or a navigation system. have.

The wireless communication unit 10 transmits and receives signals through at least one wireless communication network. The sensor unit 20 is composed of at least one sensor that detects the movement of the mobile node 1. The buffer 30 is used for accumulating pattern data generated by the pattern generator 15. The sensor unit 20 may be composed of an acceleration sensor measuring the acceleration of the mobile node 1 and a gyro sensor measuring the angular velocity of the mobile node 1. The sensor type of the sensor unit 20 may vary depending on what kind of device the mobile node 1 is implemented with. When the mobile node 1 is implemented as a smart phone, the sensor unit 20 may be composed of an acceleration sensor and a gyro sensor as described above. When the mobile node 1 is implemented as a navigation system mounted on a vehicle, the sensor unit 20 may be composed of an acceleration sensor and a gyro sensor as described above, and instead of such a sensor, an encoder, a geomagnetic sensor, etc. This can also be used.

3 is a flowchart of a wireless positioning method according to an embodiment of the present invention. Referring to FIG. 3, the wireless positioning method according to the present embodiment is composed of the following steps executed by the wireless positioning device of the mobile node 1 shown in FIG. 2. Hereinafter, referring to FIG. 3, the initial position setting unit 40, the scanning unit 11, the signal processing unit 12, the relative position estimation unit 13, the domain conversion unit 14, and the pattern generation shown in FIG. Unit 15, cluster selection unit 16, map loader 17, signal comparison unit 18, absolute position estimation unit 19, peak detection unit 21, peak comparison unit 22, speed processing unit 23 ), and the position processing unit 24 will be described in detail.

In step 110, the scan unit 11 of the mobile node 1 receives at least one signal transmitted from at least one fixed node 2 by periodically scanning the frequency band of the wireless communication through the wireless communication unit 10. . The sampling rate of the time domain data to be described below is determined according to the length of the scan period of the scan unit 11. The shorter the scan period of the wireless communication unit 10, the higher the sampling rate of the time domain data to be described below, and as a result, the precision of the absolute position of the mobile node 1 estimated according to the present embodiment can be improved. When the sampling rate of the time domain data increases, the amount of data of the time domain data increases, so that the time required to estimate the absolute position of the mobile node 1 may increase as the data processing load of the mobile node 1 increases. Due to the characteristics of wireless positioning used for purposes such as user location tracking and vehicle navigation, the current location must be provided to the user in real time, so the hardware performance of the mobile node 1, positioning accuracy required in the field to which the present embodiment is applied, etc. It is preferable that the scan period of the wireless communication unit 10 is determined in consideration of. Since the ID of the fixed node 2 is carried on the signal transmitted from a certain fixed node 2, the ID of the fixed node 2 can be known from the signal transmitted from the fixed node 2.

If there is only one fixed node 2 within the communication range within the current position of the mobile node 1, the wireless communication unit 10 receives one signal from one fixed node 2 through a scan process Is done. If a plurality of fixed nodes 2 are present in the communication range at the current position of the mobile node 1, the wireless communication unit 10 may receive the fixed nodes 2 from the plurality of fixed nodes 2 through a scan process. ) As many as the number of signals. FIG. 1 shows an example in which the mobile node 1 receives three signals from three fixed nodes 21, 22, and 23. It can be seen that the other fixed node 24 is located outside the communication range of the mobile node 1. Since this embodiment can be applied to a region where the wireless communication infrastructure is relatively well equipped, the mobile node 1 mostly receives signals from a plurality of fixed nodes 2, but in some areas where the wireless communication infrastructure is weak, one fixed node The signal of (2) can also be received. On the other hand, if no signal is received in the scan process, since the positioning itself according to the present embodiment is impossible, the mobile node 1 waits until it receives the signal from the fixed node 2.

In step 120, the signal processing unit 12 of the mobile node 1 measures the strength of each signal received in step 110. In step 130, the signal processing unit 12 of the mobile node 1 generates time domain data indicating each signal strength measured in step 120 in association with any one time point. Here, any one time point is used as information for distinguishing the signal received in step 110 from the signal previously received or the signal received thereafter. This point in time may be a point in time at which each signal is received. The reception time of each signal may be a time when the signal processing unit 12 reads the time of the internal clock of the mobile node 1 at the moment when each signal is input from the wireless communication unit 10. In more detail, in step 130, the signal processing unit 12 of the mobile node 1 transmits each signal for each signal received in step 110, the ID of the fixed node 2, when each signal is received, and 120 Generate time domain data including at least one signal strength set {RSS _mn , ...} _TD that combines the strength of each signal measured in the step into one set. Here, RSS is an abbreviation of "Received Signal Strength", TD is an abbreviation of "Time Domain", "m" of the subscript indicates the sequence number of the ID of the fixed node 2, and "n" is the symbol of each signal. Represents the sequence number at the time of reception.

For example, when the wireless positioning method shown in FIG. 3 is repeatedly executed three times, the scan unit 11 scans the surrounding signals three times. If the scan unit 11 receives only one signal transmitted from the fixed node 2 having the second ID when scanning the third signal, the time domain data includes only one signal strength set RSS ₂₃ . If the scan unit 11 receives a signal transmitted from a fixed node 2 having a second ID and a signal transmitted from a fixed node 2 having a third ID when the third signal is scanned, time domain data Will include the signal strength sets RSS ₂₃ and RSS ₃₃ .

As described above, the time domain data may be referred to as data for classifying the strength of each signal measured in step 302 into the ID of the fixed node 2 that transmitted each signal in the time domain and the time when each signal was received. Whenever the radio positioning method according to the present embodiment is executed, the reception times of the plurality of signal strength sets {RSS _mn , ...} _TD included in the time domain data generated in step 130 are all the same. Accordingly, in order to reduce the length of the time domain data, signals collected at the same time point may be arranged by attaching a plurality of fixed node IDs and a plurality of signal strengths at one time point. Those of ordinary skill in the art to which this embodiment belongs may understand that time domain data can be expressed in various formats in addition to the formats described above.

In step 210, the relative position estimation unit 13 of the mobile node 1 periodically receives the output signal of the sensor unit 20. In step 220, the relative position estimating unit 13 of the mobile node 1 calculates the moving distance and the moving direction of the mobile node 1 from the value of the output signal of the sensor unit 20 received in step 210. In step 230, the relative position estimator 13 of the mobile node 1 moves the mobile node 1 to the previous position of the mobile node 1 based on the moving distance and the moving direction of the mobile node 1 calculated in step 220. ), the current relative position of the mobile node 1 with respect to the previous position of the mobile node 1 is estimated by calculating the relative change of the current position. According to this embodiment, the relative position estimator 13 compensates for an error in the speed of the mobile node 1 calculated from the value of the output signal of the acceleration sensor using the speed estimated by the speed processor 21, The relative position of the mobile node 1 is estimated from the error-compensated speed. Here, the previous position of the mobile node 1 becomes the reference point of the cluster to be described below when the wireless positioning method according to the present embodiment is first executed, and is present after the relative position with respect to the reference point is estimated. It becomes the estimated relative position immediately before the relative position to be estimated.

As described below, in the process of converting the domain in which the signal strength is displayed from the time domain to the spatial domain, the reception time of each signal is replaced with the relative position of the mobile node 1 at the reception time. It is preferable that the government 13 periodically calculates the relative position of the mobile node 1 in synchronization with the scan period of the scan unit 11. In order to increase the accuracy of the relative position of the mobile node 1, the relative position estimator 13 may calculate the relative position of the mobile node 1 at a period shorter than the scan period of the scan unit 11. As described above, since the sensor type of the sensor unit 20 may vary depending on what kind of device the mobile node 1 is implemented, the mobile node 1 is used to estimate the relative position of the mobile node 1. Different navigation algorithms can be used depending on what kind of device is implemented.

FIG. 4 is a detailed flowchart of step 220 illustrated in FIG. 3. Referring to FIG. 4, step 220 illustrated in FIG. 3 includes the following steps executed by the relative position estimating unit 13 illustrated in FIG. 2. When the mobile node 1 is a smart phone, the relative location estimator 13 may estimate the relative location of the mobile node 1 using a PDR (Pedestrian Dead Reckoning) algorithm. When the mobile node 1 is mounted on a vehicle as a navigation system, the relative location estimator 13 may estimate the relative location of the mobile node 1 using a dead reckoning (DR) algorithm. For example, the relative position estimator 13 may calculate the moving distance and the moving direction of the mobile node 1 by attaching the acceleration sensor and the gyro sensor of the sensor unit 20 to the wheel of the vehicle. The method for calculating the moving distance and the moving direction of the mobile node 1 shown in FIG. 4 can be applied to an existing relative position estimation algorithm such as PDR, DR algorithm, etc., and a Kalman filter or the like may be additionally applied to reduce positioning error.

In step 221, the relative position estimating unit 13 integrates the acceleration of the mobile node 1 indicated by the signal output from the acceleration sensor of the sensor unit 20 from the previous time point to the current time point according to the following equation (1). The speed of the mobile node 1 between the current viewpoints is calculated. Here, the current time point means a time point at which the relative position estimator 13 currently receives the output signal of the acceleration sensor of the sensor unit 20. In order to periodically calculate the relative position of the mobile node 1 in synchronization with the scan period of the scan unit 11, the relative position estimator 13 receives the signal at step 110 in step 110. The output signal of the acceleration sensor of the current sensor unit 20 is received. The previous time point means a time point at which the relative position estimator 13 last received the output signal of the acceleration sensor of the sensor unit 20 to estimate the relative position of the mobile node 1 before the current time point. If the relative position of the mobile node 1 has never been estimated before the current time, the wireless positioning method according to the present embodiment is executed so that the relative position estimator 13 receives the output signal of the acceleration sensor of the sensor unit 20. It is the time when the first input was received.

In Equation 1, "v _s "is the speed of the mobile node 1 between the previous time point and the current time point calculated in step 221, "t ₁ " is the previous time point, "t ₂ "is the current time point, and" a _s "is the acceleration represented by the output signal of the acceleration sensor of the sensor unit 20, "a _r " is the actual acceleration of the mobile node 1, and "e" is the acceleration of the mobile node 1 with respect to the actual acceleration. It is the error of acceleration represented by the output signal of the sensor. Due to the bias error of the acceleration sensor, the acceleration represented by the output signal of the acceleration sensor is different from the actual acceleration of the mobile node 1. As described in Equation 1, the acceleration “a _s ”indicated by the output signal of the acceleration sensor is the actual acceleration “a _r ” of the mobile node 1 and the output signal of the acceleration sensor for the actual acceleration of the mobile node 1. It becomes the sum of the error "e" of the acceleration shown. Accordingly, the speed "v _s "of the mobile node 1 calculated in step 221 is the output signal of the acceleration sensor for the integration of the actual acceleration "a _r " of the mobile node 1 and the actual acceleration of the mobile node 1 It is the sum of the integrals of the error "e" of acceleration represented by.

In step 222, the relative position estimating unit 13 checks whether the speed of the mobile node 1 estimated between the previous time point and the current time point is present by the speed processing unit 23 in step 640. Here, the speed of the mobile node 1 estimated between the previous time point and the current time point by the speed processing unit 23 means the speed of the mobile node 1 estimated at step 640 executed immediately before the execution of step 222. do. When the radio positioning method shown in FIG. 3 is repeatedly executed, the execution time of one turn is very short within approximately 1 second, so the actual speed of the mobile node 1 at the time of execution of step 222 and immediately before execution of step 222 The speed of the mobile node 1 estimated in step 640 has little difference. As a result of the check in step 222, if the speed of the mobile node 1 estimated between the previous time point and the current time point is present by the speed processing unit 23 in step 640, the process proceeds to step 223, otherwise it proceeds to step 225.

In step 223, the relative position estimator 13 moves from the speed of the mobile node 1 calculated in step 221 according to the following equation (2) by the speed processor 23 in step 640 between the previous time point and the current time point. By subtracting the speed of the node 1, in step 640, the speed of the mobile node 1 calculated in step 221 for the speed of the mobile node 1 estimated between the previous time point and the current time point by the speed processing unit 23 Calculate the error. In Equation 2, “v _r ”is the speed of the mobile node 1 estimated between the previous time point and the current time point by the speed processing unit 23 in step 640.

In step 224, the relative position estimator 13 compensates for an error in the speed of the mobile node 1 calculated in step 221 using the speed error calculated in step 223. In more detail, the relative position estimating unit 13 adjusts the speed of the mobile node 1 calculated in step 221 in the direction in which the speed error calculated in step 223 is eliminated, thereby calculating the mobile node 1 calculated in step 221 (1). ) Can compensate for errors in speed. As described below, the speed “v _r ”of the mobile node 1 estimated by the speed processing unit 23 in step 640 is compared to the speed “v _s ” of the mobile node 1 calculated in step 221. This is a value very close to the actual speed of the node 1. Accordingly, the speed "v _s "of the mobile node 1 calculated in step 221 is the sum of the speed "v _r " of the mobile node 1 estimated by the speed processor 23 and the speed error calculated in step 223. Can be. As described in Equation 2, when the error calculated in step 223 converges to "0", the error of the speed "v _s "of the mobile node 1 calculated in step 221 may be eliminated.

In step 225, the relative position estimator 13 integrates the speed of the mobile node 1 calculated in step 221 or the speed of the compensated mobile node 1 in step 224, thereby integrating the mobile node between the previous time point and the current time point ( Calculate the moving distance of 1). In step 226, the relative position estimator 13 moves between the previous time point and the current time point by integrating the angular velocity of the mobile node 1 indicated by the signal output from the gyro sensor of the sensor unit 20 from the previous time point to the current time point. The moving direction of the node 1 is calculated. As described below, the relative position of the mobile node 1 estimated in step 220 is used to generate spatial domain data. The spatial domain data of this embodiment includes a plurality of relative positions estimated in the past in addition to the relative positions of the currently estimated mobile node 1. The relative position estimator 13 may repeat steps 221 to 225 for the plurality of estimated relative positions in the past to compensate for errors in the plurality of estimated relative positions in the past using the speed estimated in step 640. have. In this case, the accuracy of the spatial domain data of the present embodiment is improved, and as a result, positioning accuracy can be improved.

Recently, some of the navigation systems mounted on vehicles estimate existing relative positions, such as PDR, DR algorithms, etc., to inform the vehicle's location in environments such as tunnels that cannot receive GPS signals, for example, GPS signals. The location of the vehicle is being measured using an algorithm. As described above, due to the bias error of the acceleration sensor and the accumulation of errors due to integration, there was a very serious positioning error. As described above, this embodiment compensates for the error of the speed of the mobile node 1 calculated from the value of the output signal of the acceleration sensor using the speed of the mobile node 1 estimated by the speed processing unit 23. The relative position error of the mobile node 1 can be greatly reduced, and consequently, the position accuracy of the mobile node 1 can be greatly improved.

When the wireless positioning method shown in FIG. 3 is executed and executed again, the relative position estimator 13 moves after the estimation of the absolute position of the mobile node 1 in step 520, which will be described below, in step 520. The relative position of the mobile node with respect to the absolute position of the node 1 is estimated. Accordingly, in step 320, after the change pattern of at least one signal strength according to the relative change of the position of the mobile node 1 over a plurality of viewpoints is generated, that is, after the plurality of viewpoints, the absolute position of the mobile node 1 A change pattern of at least one signal strength according to the relative change of the position of the mobile node 1 is generated from the estimated relative position of the mobile node with respect to. According to this embodiment, the relative position of the mobile node 1 is not continuously estimated based on the previous relative position of the mobile node 1, but when the relative position of the mobile node 1 is replaced with an absolute position Since it is estimated based on the absolute position, the section to which the relative position estimation of the mobile node 1 is applied becomes very short, so that the absolute position error of the mobile node 1 due to the accumulation of errors in the relative position due to the repetition of the relative position estimation is almost Will not occur.

As described above, since the PDR and DR algorithms for estimating the relative position of the mobile node 1 estimate the relative position of the mobile node 1 through the integration of the output signal value of the sensor, the relative position of the mobile node 1 The error of the relative position of the mobile node 1 accumulates as the position estimation is repeated. Accordingly, as the section to which the relative position estimation of the mobile node 1 is applied is longer, the error of the relative position of the mobile node 1 increases. In the present embodiment, since the relative position of the mobile node 1 is replaced with an absolute position in the middle in which the relative position of the mobile node 1 is estimated, error accumulation of the relative position due to repetition of the relative position estimation hardly occurs. do. Accordingly, the accuracy of positioning according to the present embodiment is very high compared to a technique in which a relative position estimation algorithm such as PDR and DR is fused to a conventional wireless positioning technique.

After the absolute position of the mobile node 1 is estimated according to the present embodiment, the absolute position may be estimated for each of the estimated relative positions of the mobile node 1, and then the relative position of the estimated mobile node 1 may be determined. After multiple estimation, one absolute position may be estimated. In the former case, after the absolute position of the mobile node 1 is estimated, the previous position of the mobile node 1 is always the absolute position estimated immediately before the relative position to be currently estimated. In the latter case, the previous position of the mobile node 1 becomes the estimated absolute position immediately before the current relative position to be estimated immediately after the absolute position of the mobile node 1 is estimated, but after that, the relative position is as many times as described above. Until the position is estimated, it becomes the estimated relative position immediately before the current relative position to be estimated.

In step 310, the domain conversion unit 14 of the mobile node 1 associates the time domain data generated in step 130 with each signal strength measured in step 120 to the relative position of the mobile node 1 estimated in step 230. It is converted into spatial domain data. In more detail, the domain converter 14 is fixed to each set RSS _mn for each set of at least one signal strength set {RSS _mn , ...} _TD included in the time domain data generated in step 130. A fixed node is used to replace the time domain data by replacing the ID of the node 2, the reception time of each signal, and the intensity of each signal with the relative position of the mobile node 1 corresponding to the reception time of each signal. The ID of (2), the relative position of the mobile node 1, and the strength of each signal are combined into at least one signal strength set {RSS _mn , ...} _SD , which are grouped into one set.

Here, RSS is an abbreviation of "Received Signal Strength", SD is an abbreviation of "Space Domain", "m" of the subscript indicates the sequence number of the ID of the fixed node 2, and "n" is the sign of each signal. Indicates the sequence number of the relative position of the mobile node 1 corresponding to the sequence number at the time of reception. When the signal reception in step 110 and the signal reception in step 210 are synchronized and executed at substantially the same time, the relative position of the mobile node 1 corresponding to the reception time of each signal is the estimated movement at the reception time of each signal. It may be a relative position of the node 1. In this case, the sequence number at the time of reception of each signal is the sequence number of the relative position of the mobile node 1 as it is. For example, the signal strength set RSS ₂₃ included in the spatial domain data indicates the strength of the signal received from the fixed node 2 having the second ID when the relative position estimator 13 estimates the third relative position. .

If the synchronization of the signal reception in step 110 and the signal reception in step 210 is not performed, the relative position of the mobile node 1 corresponding to the reception point of each signal is determined by the relative position of each signal among the estimated relative positions at various time points. It may be a relative position estimated at a time point closest to the reception time point. As described above, the time domain data is time-based data represented by associating each signal strength with the reception time of each signal by grouping the ID of the fixed node 2, the reception time of each signal, and the strength of each signal into one set. On the other hand, the spatial domain data includes the ID of the fixed node 2 included in the time domain data, the relative position of the mobile node 1 estimated at the time included in the time domain data, and the strength of each signal included in the time domain data. It is spatial-based data that is shown by associating each signal strength with the relative position of the mobile node 1 by grouping them into one set.

Since the reception times of the plurality of signal strength sets {RSS _mn , ...} _TD included in the time domain data generated in step 130 are the same every time the radio positioning method according to the present embodiment is executed, in this embodiment Whenever the radio positioning method according to the execution is executed, the relative positions of the plurality of signal strength sets {RSS _mn , ...} _SD included in the spatial domain data converted in step 310 are all the same. Accordingly, in order to reduce the length of the spatial domain data, a plurality of fixed node IDs and a plurality of signal strengths may be arranged and attached to signals collected at the same relative position. Those of ordinary skill in the art to which this embodiment belongs may understand that spatial domain data can be expressed in various formats in addition to the formats described above.

In step 320, the pattern generating unit 15 of the mobile node 1 positions the at least one signal strength measured in step 120 and the position of the mobile node over a plurality of viewpoints from the relative positions of the mobile node 1 estimated in step 230. A change pattern of at least one signal strength according to a relative change of is generated. In more detail, the pattern generating unit 15 may include at least one signal strength measured in step 120 and at least one signal strength currently received in step 110 from the relative position of the mobile node 1 estimated in step 230. Generating a pattern, and successively listing the pattern of the at least one signal currently received in the pattern of the at least one signal received before the signal reception time in step 110 to determine the position of the mobile node 1 over a plurality of time points. A change pattern of at least one signal strength according to a relative change is generated.

The wireless positioning method according to this embodiment is a method for repeatedly estimating its current position in real time when the mobile node 1 moves in a certain path, as shown in FIG. 3 while the wireless positioning device shown in FIG. 2 is being driven. Steps are repeated continuously. For example, it is assumed that the steps shown in FIG. 3 are repeated three times after the start of the wireless positioning device shown in FIG. 2 and are currently being repeated four times, and the first, second, and third steps in step 110 are performed. , Fourth, each time the signal is received will be referred to as "T1", "T2", "T3", and "T4". In this example, the pattern generator 15 generates at least one signal intensity change pattern received from at least one fixed node 2 until the time T4. That is, the pattern generator 15 sequentially lists at least one signal strength pattern received from T1 to T4 time points, thereby at least one signal according to a relative change in the position of the mobile node 1 over T1 to T4 time points. Generate a pattern of change in intensity.

5 is a view for explaining the pattern forming principle in step 320 of FIG. 3. Referring to (a) of FIG. 5, the intensity of the signal transmitted from the fixed node 2 is attenuated approximately inversely proportional to the square of the distance from the fixed node 2. When the user approaches and moves away from the fixed node 2, the mobile node 1 carried by the user receives a signal having an intensity as shown in Fig. 4A. In general, the user does not always walk at a constant speed and may temporarily stop while walking. While the user is temporarily stopped, as shown in FIG. 5(b), even if the wireless positioning method shown in FIG. 3 is repeatedly executed, the strength of the signal transmitted from the fixed node 2 is almost the same. Is measured. The x-axis of FIG. 5(b) represents the point at which the signal was measured, and the y-axis represents the signal strength. 5(c), the x-axis represents the relative position (RL) of the mobile node 1, and the y-axis represents the signal strength.

Since the intensity of the signal transmitted from the fixed node 2 is measured each time the wireless positioning method shown in FIG. 3 is executed, the intensity of the signal transmitted from the fixed node 2 is continuous as shown in FIG. 5(b). It is not displayed in the form of a curved curve, but in practice, dots displayed at a height corresponding to the signal strength are displayed in a continuously arranged form. When the reception point of each signal is replaced with the relative position of the mobile node 1 by the domain conversion unit 14, as shown in FIG. 4(c), the signal strength generated by the pattern generation unit 15 The change pattern is represented by a continuous sequence of signal strengths received multiple times at multiple relative positions of the mobile node 1 estimated at multiple viewpoints. Accordingly, the change pattern of the at least one signal strength generated by the pattern generator 15 is continuous in the strength of at least one signal received multiple times at a plurality of relative positions of the mobile node 1 estimated at a plurality of viewpoints. It can be said that it is a change pattern of at least one signal intensity represented by a list.

In the database of the positioning server 3, a radio map representing a pattern of distribution of signal strength collected in all regions where a wireless positioning service according to the present embodiment is provided is stored. When a user repeats moving multiple times on the same route, the time taken to complete the route is generally different. In the case where the user's movement path is the same, even if the time required to complete the path is different, the various locations of the user on the path are the same. Therefore, it is not only impossible but also unnecessary to reflect the reception time point of the signal transmitted from the fixed node 2 in the radio map. That is, the radio map reflects the ID of the fixed node 2 that has transmitted a certain signal, the absolute position of the point where the signal is received, and the strength of the signal for a number of signals collected from all regions where wireless positioning services are provided. It is expressed as a map in the form of a distribution pattern of signal strength.

In order to estimate the absolute position of the mobile node 1 according to the present embodiment, a pattern that can be matched to this radio map must be generated. Since the positioning of the mobile node 1 is performed without knowing the location of the mobile node 1, the mobile node 1 generates time domain data representing each signal strength by associating each signal strength with the reception time of each signal, and then The time domain data is converted into spatial domain data represented by associating each signal strength with a relative position of the mobile node 1 corresponding to the reception time point of each signal. In order to determine the coordinates of the radio map, the real world area where wireless positioning service is provided is divided into a grid structure in which the distance between the scales is constant. Since the value of the absolute position of a certain point on the radio map is expressed in two-dimensional coordinates having the resolution of this unit, the pattern generated by the pattern generator 15 is the same as the coordinate resolution of the radio map or as low a resolution as possible. It is preferable that the relative position of the mobile node 1 is estimated.

As illustrated in (c) of FIG. 5, a plurality of dots indicating intensity of a plurality of signals received from a plurality of relative positions of the mobile node 1 may be densely packed as the user is temporarily stopped. have. In this case, if the maximum distance between a plurality of dots densely packed with each other is within a distance corresponding to a coordinate resolution unit of the radio map, that is, a resolution unit of coordinates for indicating the relative position of the mobile node 1, the plurality of dense clusters A dot is a dot, and the same effect as indicating one signal strength occurs, resulting in a pattern of change in signal strength. For example, if the coordinate resolution unit of the radio map is 1 meter, multiple dots clustered within 1 meter have the same effect as representing a single signal strength as a single dot, and a variation pattern of signal strength is generated. Results.

In step 320, the pattern generating unit 54 is configured to generate at least one signal strength received from at least one fixed node 2 at a relative position of the mobile node 1 estimated in step 230 from the spatial domain data converted in step 310. Create a pattern. At least one signal strength pattern generated by the pattern generator 54 in step 320 is at least one fixed node indicated by the spatial domain data at a relative position indicated by the spatial domain data among the movement paths of the mobile node 1. It is a pattern of at least one signal strength generated by displaying at least one signal strength represented by the spatial domain data. In step 320, the pattern generating unit 54 sets at least one signal strength set in the spatial domain data converted in step 310 {RSS _mn , ...} Each signal strength set RSS _{SD mn for} each signal strength set RSS _mn At least one signal strength pattern is generated by generating a signal strength graph representing the signal strength of.

FIG. 6 is a diagram illustrating a three-dimensional spatial coordinate system for generating a pattern of change in signal strength used for wireless positioning in this embodiment. Referring to FIG. 6, the x-axis of the three-dimensional space is a coordinate axis in which IDs of a plurality of fixed nodes 2 are arranged at regular intervals, and the y-axis represents a movement path of the mobile node 1 and a relative position of the mobile node 1 A coordinate axis divided by a resolution unit of coordinates to be issued, and a z-axis is a coordinate axis obtained by dividing a measurement range of signal intensity received from a plurality of fixed nodes 2 into a measurement resolution unit of signal intensity. Those of ordinary skill in the art to which this embodiment pertains can understand that information represented by each of the x-axis, y-axis, and z-axis of the 3D space can be exchanged with each other. For example, the x-axis may indicate the relative position of the mobile node 1, and the y-axis may indicate the ID of the fixed node 2.

The 3D spatial coordinate system illustrated in FIG. 6 is based on the premise that a user or a vehicle travel path is determined, such as a road in a city center, and a radio map stored in the database of the positioning server 3 moves along the determined path. When constructed based on the collected signals, the distribution pattern of the signal strength of the radio map, which will be described below, includes a moving path. That is, when the change pattern of the current signal strength of the mobile node 1 coincides with a certain portion in the radio map, it is found through comparison with the radio map that the mobile node 1 is located at a certain point in a certain movement path. Can. If the moving path of the mobile node 1 is not determined or if the height of the mobile node 1 is to be estimated in addition to the location of the mobile node 1 on the ground, at least one received in step 110 in a multidimensional spatial coordinate system of four or more dimensions It may be necessary to generate a pattern of change in signal strength of.

In order to help understand this embodiment, 10 access points corresponding to the fixed node 2 of the Wi-Fi network are listed on the x-axis of FIG. 6, and a user carrying the mobile node 1 on the y-axis is 1 They are listed in meters of 10 meters long. Therefore, the resolution unit of the relative position coordinate of the mobile node 1 is 1 meter. As described below, in step 510, a change pattern of signal strength compared to a map represented by map data is a 3D pattern generated in a 3D space of the size shown in FIG. That is, the size of the 3D space illustrated in FIG. 6 is a change in signal strength compared to a map indicated by map data at 10 meter intervals with respect to a path moved by the mobile node 1 during positioning according to the present embodiment. This means that a pattern is created. At this time, the number of access points on the movement path of the mobile node 1 is 10. The 3D spatial coordinate system illustrated in FIG. 6 is only an example, and the number of access points and the length of the movement path of the mobile node 1 may be variously designed.

In step 320, the pattern generation unit 54 is any one of signal strength set for each signal strength set RSS _mn contained in the spatial domain data converted in step 310 to the x-axis of the three-dimensional space, the ID of the fixed node that represents the RSS _mn A point in 3D space determined by mapping, mapping the relative position of the mobile node 1 represented by the signal strength set RSS _mn on the y-axis, and mapping the signal strength represented by the signal strength set RSS _mn on the z-axis. A graph showing the signal strength of the signal strength set RSS _mn is generated by displaying a dot in. The signal strength graph is not a graph for outputting a screen to show to a user, but a graphic element of an intermediate step for showing a process of generating a change pattern of signal strength in the form of a 3D graph used for wireless positioning. However, in order to help understand the present embodiment, the signal strength set RSS _mn signal strength graph, the signal strength pattern at one relative location, and the signal strength variation pattern according to the relative location change may be visually recognized below. It will be described assuming it is in the form.

As described above, the pattern of at least one signal strength generated by the pattern generator 54 is associated with the ID of at least one fixed node indicated by the spatial domain data and the relative position indicated by the spatial domain data, and the spatial domain data Means at least one signal strength pattern representing at least one signal strength represented by. Accordingly, if the mobile node 1 receives only one signal, the signal intensity pattern at the relative position of the mobile node 1 estimated in step 230 may be in the form of one dot. If the mobile node 1 has received a plurality of signals, the signal strength pattern at the relative position of the mobile node 1 estimated in step 230 may be a straight line or a curved form represented by a plurality of dots adjacent to each other. You can.

In step 320, the pattern generation unit 54 accumulates and stores pattern data representing the pattern of at least one signal strength generated in this way in the pattern data stored in the buffer 30. The pattern data stored in the buffer 30 is pattern data for the relative position estimated before the relative position estimation in step 230. By accumulating the pattern data, a change pattern of at least one signal strength measured in step 120 is generated. The buffer 30 may accumulate as much pattern data as necessary to generate a pattern of change in signal intensity compared to a map indicated by the map data, and a larger amount of pattern data may be accumulated. In the latter case, a change pattern of signal strength is generated from a part of the pattern data accumulated in the buffer 30.

7 is a diagram showing the accumulation of pattern data used for wireless positioning in the present embodiment in a table form. 7A, pattern data accumulated in the buffer 30 is represented in a table form. In operation 320, the pattern generation unit 54 may accumulate spatial domain data in the buffer 30 in the form of a table in FIG. 7A. In the table of (a) of FIG. 7, the “m” value of “APm” corresponds to the coordinate value of the x-axis of the 3D space as the sequence number of the ID of the fixed node 2, and the “n” value of “RLn” moves As the sequence number of the relative position of the node 1, it corresponds to the coordinate value of the y-axis in the three-dimensional space, and "RSS _mn "is sent from the fixed node 2 having the ID of "APm" and the relative position of the mobile node 1 The strength of the signal received at "RLn", which corresponds to the coordinate value of the z-axis in 3D space.

According to the pattern generation technique of the pattern generation unit 54 as described above, "RSS _mn "on any one point of the two-dimensional plane determined by the "m" value of "APm" and the "n" value of "RLn" Since the dot is displayed at a height corresponding to the value, the set of "RSS _mn " shown in FIG. 7A forms a geometric surface in 3D space. As described above, in step 320, the pattern generator 54 maps the ID of any one fixed node to the x-axis in the 3D space, maps the relative position of the mobile node 1 to the y-axis, and the z-axis. A change in at least one signal strength according to a relative change in the position of the mobile node 1 in a manner of displaying a dot at a point in a three-dimensional space determined by mapping the strength of a signal transmitted from a fixed node and received at the relative position Creates a three-dimensional pattern in the form of a geometric surface graphed by. The plurality of signal strength sets included in the spatial domain data accumulated in the buffer 30 may not be accumulated in the buffer 30 in the form of a table in FIG. 7A, in various forms for efficient use of memory space. It may accumulate in the buffer 30.

8 is a diagram illustrating an example in which a change pattern of signal strength used in wireless positioning of the present embodiment is generated. The pattern generation method of the pattern generation unit 54 as described above when the user moves 20 meters under the assumption that the scale of the 3D spatial coordinate system shown in FIG. 8 is 10 times the scale of the 3D spatial coordinate system shown in FIG. 6. According to, the relative position of the mobile node 1 is estimated 20 times, and a pattern in each of the 20 relative positions generates a three-dimensional pattern in the form of a surface corresponding to the moving distance. The surface shown in FIG. 8 is formed by dense dots of different heights. It can be seen that when the user moves 40 meters, 60 meters, and 80 meters, the surface-shaped 3D pattern is expanded by an additional portion of the moving distance. The curvature of the surface is caused by a difference in intensity between signals transmitted from fixed nodes 2 adjacent to each other, that is, a difference between “RSS _mn ” adjacent to each other.

In step 410, the cluster selection unit 16 of the mobile node 1 selects at least one cluster from among clusters in all regions where positioning service according to the present embodiment is provided based on at least one signal received in step 110. do. All areas where wireless positioning services are provided are divided into multiple clusters. In more detail, the cluster selection unit 16 selects one cluster in which the mobile node 1 is located based on the ID of at least one fixed node 2 carried in at least one signal received in step 110. do. For example, when a certain fixed node 2 transmits a signal only to a specific cluster, or when a certain combination of multiple fixed nodes 2 can receive signals only from a specific cluster, the cluster may be configured with only the ID of at least one fixed node 2 Can be selected.

If the cluster selection unit 16 cannot select one cluster in which the mobile node 1 is located based on the ID of the at least one fixed node 2, the cluster selection unit 16 determines the strength of at least one signal received in step 110. Based on this, one cluster in which the mobile node 1 is located is selected. For example, when a fixed node 2 transmits a signal to two neighboring clusters, or when a combination of a plurality of fixed nodes 2 receives signals from two neighboring clusters, it is possible to transmit at least one signal. Clusters can be selected based on the century. The cluster selection unit 16 may also select a plurality of clusters by adding the surrounding clusters to the thus selected cluster. For example, a plurality of clusters may be selected when the mobile node 1 is located at the boundary of two neighboring clusters or when the number of clusters is increased to improve the accuracy of radio positioning.

In step 420, the map loader 17 of the mobile node 1 transmits the map data corresponding to at least one cluster selected in step 410 to the positioning server 3 through the wireless communication unit 10. To send. In this signal, data representing at least one cluster selected in step 410 is carried. In step 430, when the location server 3 receives the request signal of the map data transmitted from the mobile node 1, the radio map in which distribution data of signal strength in all regions where the location service according to the present embodiment is provided is recorded. From this, map data indicating a map in the form of a distribution pattern of signal strength in at least one cluster indicated by the request signal, that is, at least one cluster selected in step 410 is extracted. The radio map is stored in the database of the location server 3.

In step 440, the location server 3 transmits the map data extracted in step 430 to the mobile node 1. In step 450, the mobile node 1 receives the map data transmitted from the positioning server 3. For example, the mobile node 1 may receive map data as shown in FIG. 8B. In the table of FIG. 8(b), the “m” value of “APm” is the sequence number of the ID of the fixed node 2 installed in the region of at least one cluster selected in step 410, and the “n” value of “ALn” Is the sequence number of the absolute location (AL) of the mobile node 1, and "RSS _mn "is sent from the fixed node 2 having the ID of "APm" and the absolute location "ALn" of the mobile node 1 It is the strength of the signal received at.

Since the pattern data accumulated in the buffer 30 of the mobile node 1 and the map data received from the positioning server 3 must be matchable with each other, the format of the map data is the same as that of the pattern data. Therefore, the description of the map data will be replaced with the description of the pattern data described above. Since the map data is extracted from the radio map constructed by databaseting the strength of numerous signals collected in the area where the wireless location service is provided, the value of “RSS _mn ” in FIG. 8B is displayed as a specific value. If the mobile node 1 has enough databases to accommodate the radio map stored in the database of the positioning server 3, the mobile node 1 extracts map data from the radio map stored in the database therein. It might be. In this case, steps 420, 440, and 450 may be omitted, and step 430 is performed by the mobile node 1.

In operation 510, the signal comparison unit 18 of the mobile node 1 may include at least one signal intensity change pattern generated in operation 320 and a map indicated by the map data received in operation 450, that is, the mobile node 1 is located. By comparing the map in the form of a distribution pattern of signal strength in a region, a portion having a pattern most similar to the change pattern of at least one signal strength generated in step 320 is found in the map represented by the map data. The signal comparator 18 moves the pattern of change in at least one signal strength generated in step 320 on the map indicated by the map data received in step 450, and changes the pattern of change in at least one signal strength generated in step 320. By sequentially comparing the parts in the map overlapping with the movement, the part having the pattern most similar to the change pattern of at least one signal strength generated in step 320 is found in the map.

In more detail, the signal comparator 18 compares the three-dimensional pattern of the geometric surface that graphs the change in at least one signal strength generated in step 320 and the map indicated by the map data received in step 450. By doing so, the surface portion having the shape most similar to the surface shape of the 3D pattern in which the change in at least one signal intensity generated in step 320 is graphed in the map indicated by the map data received in step 450 is retrieved. The signal comparator 18 is generated in step 320 while moving the three-dimensional pattern of the geometric surface graphed with the change in at least one signal intensity generated in step 320 on the map indicated by the map data received in step 450. The surface portion having the shape most similar to the surface shape of the three-dimensional pattern generated in step 320 in the map by sequentially comparing the surface-shaped three-dimensional pattern with the surface portions of the map overlapping with it as it moves. Color.

In the above example, the signal comparator 18 displays the pattern most similar to the change pattern of at least one signal strength according to the relative change of the position of the mobile node 1 over the time points T1 to T4 in the map indicated by the map data. Find the part you have. That is, the signal comparator 18 searches for a portion of the map indicated by the map data having the pattern most similar to the pattern of change in signal strength up to the time T4. As described above, the change pattern of the signal strength up to the T4 time point is a geometric surface pattern that graphs the change of signal strength up to the T4 time point. The signal comparator 18 detects a surface portion having a shape most similar to a surface shape of a 3D pattern in which a change in signal strength up to a T4 point in the map represented by the map data is graphed.

As described above, the present embodiment is generated in step 320 based on a surface correlation between at least one change pattern of signal strength generated in step 320 and a distribution pattern of signal strength indicated by map data received in step 450. It is determined where the at least one signal intensity change pattern is located in the map indicated by the map data received in step 450. For example, the surface correlation may be calculated using a three-dimensional shape matching algorithm well known to those of ordinary skill in the art. In step 520, the absolute position estimating unit 19 of the mobile node 1 determines the absolute position of the map indicated by the portion extracted by comparison in step 510, and more specifically, the extracted surface portion of the mobile node 1 The absolute position of the mobile node 1 estimated as the absolute position is determined as the current position of the mobile node 1. In the above-described example, the absolute position estimator 19 moves the absolute position of the map indicated by the part found by comparison in step 510, that is, the part having the pattern most similar to the change pattern of signal strength up to the time T4. It is assumed to be the absolute position of the node 1.

In step 530, the initial position setting unit 40 of the mobile node 1 is estimated in step 520 based on the similarity between the at least one signal strength change pattern generated in step 320 and the portion found by comparison in step 510. The reliability of the absolute position of the mobile node 1 is calculated. For example, in order to explain in more detail, the initial position setting unit 40 in the process of searching for a portion having the pattern most similar to the pattern of changing the signal strength up to the time T4, the pattern of changing the signal strength up to the time T4 The reliability of the absolute position of the mobile node 1 estimated in step 520 is calculated based on a change pattern of a plurality of similarities between portions in the map compared to and a change pattern of signal strength up to the time point T4. The reliability calculation method of the absolute position of the mobile node 1 according to the present embodiment will be described in detail below.

In step 540, the initial position setting unit 40 of the mobile node 1 checks whether the reliability calculated in step 530 is higher than the reference value. As a result of the check in step 540, if the reliability calculated in step 530 is higher than the reference value, the process proceeds to step 550, otherwise it returns to step 530. If the reference value of the reliability calculated in step 530 is too high, it may be difficult to newly define or update the initial position of the mobile node 1, and if the reference value is too low, the accuracy of the initial position of the mobile node 1 is low and positioning error is Can increase. If the initial position of the mobile node 1 is difficult to be newly defined or updated, the initial position of the mobile node 1 continues or the initial position of the mobile node 1 according to the movement of the mobile node 1 continues. Positioning errors may increase because location updates may not be reflected. Accordingly, the reference value for the reliability calculated in step 530 is performed through multiple positioning simulations in consideration of various factors such as the resolution of the signal intensity change pattern used in the present embodiment and the size of the color extraction unit region based on the initial position. It is desirable that it is designed to a suitable value.

In step 550, the initial position setting unit 40 of the mobile node 1 selects the absolute position of the mobile node 1 estimated in step 520 as the initial position of the mobile node 1, so that the initial position of the mobile node 1 is determined. To set. According to steps 530 to 550, the initial position setting unit 40 determines the absolute position of the mobile node 1 estimated in step 520 according to the reliability of the absolute position of the mobile node 1 calculated in step 530. ) As the initial position. That is, if the reliability of the absolute position of the mobile node 1 calculated in step 530 is higher than the reference value, the initial position setting unit 40 initially sets the absolute position of the mobile node 1 estimated in step 520 of the mobile node 1. It will be selected as a location. In this way, the initial position setting unit 40 is based on the similarity between the at least one signal intensity change pattern generated in step 320 and the portion found by comparison in step 510, the mobile node 1 estimated in step 520. The initial position of the mobile node 1 is set by selecting the absolute position of as the initial position of the mobile node 1.

In the above example, the initial position setting unit 40 is based on the similarity between the signal intensity change pattern up to the time T4 and the portion detected by comparison in step 510, the absolute value of the mobile node 1 estimated in step 520. The initial position of the mobile node 1 is set by calculating the reliability of the position and selecting the absolute position of the mobile node 1 estimated in step 520 as the initial position of the mobile node 1 according to the reliability of the absolute position. can do. That is, the initial position setting unit 40 in the process of finding the portion having the pattern most similar to the change pattern of the signal strength up to the T4 time point, the portion in the map compared to the change pattern of the signal strength up to the T4 time point and the T4 time point The reliability of the absolute position of the mobile node 1 estimated in step 520 is calculated based on the change pattern of a plurality of similarities between the change patterns of the signal strength up to and the mobile node estimated in step 520 according to the reliability of the absolute position. It can be said that the initial position of the mobile node 1 is set by selecting the absolute position of (1) as the initial position of the mobile node 1. If the initial position of the mobile node 1 does not exist, the initial position is set in such a way that the initial position of the mobile node 1 is first defined, and if so, the initial position of the mobile node 1 is updated. In this way, the initial position is set.

According to this embodiment, the initial position setting unit 40 is an index inversely proportional to the similarity between the signal intensity change pattern up to the T4 time point and the portion retrieved in step 510, and the signal intensity change pattern up to the T4 time point in step 510. The mobile node is calculated by calculating a correlation distance corresponding to the difference between the extracted parts, and selecting the absolute position of the mobile node 1 estimated in step 520 as the initial position of the mobile node 1 based on the calculated correlation distance. Set the initial position in (1). Here, the correlation distance becomes 0 when the pattern shape between the pattern of change in signal strength up to the T4 time point and the portion extracted in step 510 is the same, and increases as the number of differences increases. For example, the initial position setting unit 40 changes the signal strength up to the time T4 to the number of pixels located outside the portion extracted in step 510 among the pixels constituting the change pattern of the signal intensity up to the time T4. It can be calculated as a correlation distance between the pattern and the portion extracted in step 510.

As described above, the present embodiment, unlike the conventional method, does not consider only the currently received signal strength, and uses at least one pattern of changing the signal strength according to the relative change in the position of the mobile node 1 over a plurality of viewpoints so far. Since the position of the mobile node 1 is estimated, if the length of the change pattern of the signal strength is set very long, real-time positioning of the mobile node 1 may be deteriorated. However, the shape similarity between the surface representing the pattern of the intensity change of the signal up to the current position of the mobile node 1 and the surface representing the distribution pattern of the signal intensity represented by the map data is rapidly increased using a three-dimensional shape matching algorithm. Since it can be determined, even if the length of the pattern of the change in signal strength over a plurality of time points is very long, it is possible to ensure real-time positioning of the mobile node 1.

9-10 are diagrams illustrating examples in which the absolute position of the mobile node 1 is estimated according to the wireless positioning algorithm of the present embodiment. The scale of the 3D spatial coordinate system shown in FIG. 9-10 is the same as the scale of the 3D spatial coordinate system shown in FIG. 6, and an example of a pattern based on the relative position of the mobile node 1 shown on the left side of FIG. 9-10 Is the same as the example shown in FIG. 8. The example of the pattern based on the absolute position of the map shown on the right side of FIGS. 9-10 shows a map of the distribution pattern of signal strength for a travel path up to 100 meters. The map indicated by the map data provided by the positioning server 3 is much larger than the map shown on the right side of FIGS. 9-10, but due to the limitation of the size of one floor, the map displayed by the map data on the right side of FIGS. On the left side of 9-10, only the part related to matching with the pattern shown is shown. When the user moves 20 meters, a surface-shaped three-dimensional pattern shown on the left side of FIG. 9(a) is generated.

According to the matching technique based on the surface correlation as described above, the comparator 57 searches for a darkly marked portion in the pattern map shown on the right side of FIG. 9A. Likewise, when the user moves 40 meters, 60 meters, and 80 meters, three-dimensional patterns in the form of surfaces shown on the left of FIGS. 9-10 (b), (c), and (d) are sequentially generated. The comparator 57 sequentially searches out the darkly marked portions in the pattern map shown on the right side of FIGS. 9-10 (b), (c), and (d). The absolute position estimating unit 58 moves the relative position estimated in step 230 among the plurality of absolute positions of the portion found in step 510, that is, the surface part, that is, the absolute position corresponding to the most recently estimated relative position (1). Is assumed to be the absolute position of The correspondence between the relative position and the absolute position is determined from the shape matching relationship between the two surfaces. That is, the absolute position estimator 58 determines the absolute position of the part having the shape most similar to the shape of the relative position estimated in step 230 from among the plurality of absolute positions of the surface part retrieved in step 440. Estimated by location.

Several wireless positioning algorithms, including K-Nearest Neighbor (KNN) algorithm, Particle Filter algorithm, and fusion algorithm of particle filter and PDR, which are widely known as the conventional wireless positioning technology, commonly move using only the currently received signal strength. The position of the node 1 is estimated. When signal strengths different from the signal strengths collected at the time of radio map construction are measured due to changes in the radio environment, such as signal interference between communication channels, expansion of access points, failures or obstacles, points adjacent to each other within the radio map are similar. Because of the signal strength distribution, the conventional wireless positioning algorithm has a very high probability that the current position of the mobile node 1 is estimated to be another adjacent position rather than its actual position. The greater the difference between the signal strength collected at the time of the radio map construction and the strength of the currently received signal, the larger the positioning error.

As described above, since the wireless positioning algorithm of the present embodiment estimates the position of the mobile node 1 using a pattern of at least one signal strength change according to the relative change of the position of the mobile node over a plurality of viewpoints, the communication channel Even if a change in the radio environment such as signal interference, increase of access points, or failure or obstacle occurs, errors in the estimated values of the current position of the mobile node 1 hardly occur. That is, the wireless positioning algorithm of the present embodiment considers not only the strength of the currently received signal but also all of the past signal strengths received in the path that the mobile node 1 has traversed so far, and based on the change pattern of the signal strength. Since the current location of (1) is estimated, changes in the radio environment at the current location of the mobile node 1 have little effect on the estimation of the current location of the mobile node 1.

When considering only the strength of a currently received signal due to a change in the radio environment according to a conventional radio positioning algorithm, an adjacent point of the actual location of the mobile node 1 estimated is a point deviating from the path indicated by the change pattern of the signal strength so far. do. According to this embodiment, the change in the radio environment at the point where the mobile node 1 is currently located cannot change the entire pattern of change in signal strength received in the path that the mobile node 1 has traversed so far. Since only the current point of view is changed, the position of the mobile node 1 is estimated using the pattern of change of at least one signal strength according to the relative change in the position of the mobile node over a plurality of time points so far. It is very likely to estimate the actual position of the mobile node 1 as the absolute position of the mobile node 1, not the adjacent point of the actual position of the mobile node 1 estimated according to the algorithm. Of course, if the wireless environment changes continuously at various points on the moving path of the mobile node 1, a positioning error may occur, but this rarely occurs.

In particular, the intensity of the signal received from a certain fixed node 2 forms a peak when passing around it, which tends not to be greatly affected by changes in the radio environment. Therefore, the mobile node 1 has already been received even if the currently received signal is not a peak or an adjacent portion of the peak, to the extent that the real-time property of the location is guaranteed in the length of the pattern of the change in signal strength used for wireless positioning according to the present embodiment. If you make it long enough to cover the peaks of the various signals on the route you have been through, you will be very resistant to changes in the wireless environment. In addition, the position change between the peak and the peak in the change pattern of signal intensity used for positioning according to the present embodiment estimates the relative position of the mobile node 1 within a relatively short distance without error accumulation due to the relative position estimation. Since it can be accurately estimated by, the accuracy of the position estimation of the mobile node 1 can be greatly improved even when the radio environment changes severely.

As described above, the change pattern of the signal strength used in the wireless positioning according to the present embodiment is a geometric surface 3 in which the change of at least one signal strength according to the relative change in the position of the mobile node 1 is graphed. As a dimensional pattern, from the viewpoint of comparison between the surface-shaped three-dimensional pattern of the mobile node 1 and the surface-shaped three-dimensional pattern of map data, a change in the radio environment at the current position of the mobile node 1 is the current received signal. This leads only to the height error of the surface portion corresponding to the intensity, and does not affect most of the surfaces corresponding to points other than the point of change in the wireless environment. That is, changes in the radio environment at the current location of the mobile node 1 have little effect on the overall shape of the surface even if it causes some deformation of the surface shape.

Since the conventional wireless positioning algorithm compares the numerical value of the currently received signal strength with the numerical value of the signal strength distributed in the radio map, the mobile node 1 having the most similar numerical value to the numerical value of the currently received signal strength This leads to a result of incorrectly estimating the adjacent point of the actual position as the position of the mobile node 1. According to the wireless positioning algorithm of the present embodiment, since the change in the radio environment at the current position of the mobile node 1 has little effect on the overall shape of the surface, it is most similar to the surface shape of the three-dimensional pattern in the map represented by the map data. When searching for a portion of a surface having a shape, it is very unlikely that a portion of a surface different from the original portion to be searched for due to an error in the strength of the currently received signal. As described above, the positioning error of the conventional algorithm according to the comparison of the numerical value of the currently received signal strength with the numerical value of the signal strength distributed in the radio map can be fundamentally blocked, thereby significantly improving the positioning accuracy of the mobile node 1. You can.

Since the base station of the LTE network is very expensive compared to the access point of the Wi-Fi network, the base station and the relay service area are installed as far away from the neighboring base stations as possible so as not to overlap. As a result, the LTE signal is evenly distributed throughout the indoor and outdoor areas, but has a characteristic that the area where the change in signal strength is not large is wide. As described above, since the conventional wireless positioning algorithm commonly estimates the position of the mobile node 1 using only the currently received signal strength, a change in signal strength between positioning points on the mobile node 1's moving path In the rare case, it is not only possible to distinguish the positioning points by the signal strength alone, but also very sensitive to ambient noise, and thus the positioning error becomes very large.

Even if there is little change in the strength of the LTE signal between positioning points adjacent to each other on the moving path of the mobile node 1, the length of the change pattern of the signal strength used in the wireless positioning of the present embodiment is determined by the positioning of the mobile node 1. If the length is sufficiently long in a limit where real-time property is guaranteed, the strength of the LTE signal is sufficiently changed to the extent that accurate location estimation of the mobile node 1 is possible within the movement distance corresponding to the length of the change pattern of the signal strength. Accordingly, the wireless positioning algorithm of the present embodiment can accurately estimate the position of the mobile node 1 even when there is little change in the strength of the LTE signal between positioning points adjacent to each other on the mobile node 1's moving path. .

As described above, since the wireless positioning algorithm of the present embodiment can accurately estimate the location of the mobile node 1 using the LTE signal with little change in signal strength between measurement points on the moving path, it covers both the indoors and outdoors. It is possible to provide a wireless positioning service that can be performed. As a result, the wireless positioning algorithm of the present embodiment uses a LTE signal distributed widely in the building indoors and in all parts of the city, and is used for vehicle navigation systems or autonomous driving where both indoor and outdoor positioning with high accuracy is possible even in the city center without the influence of high-rise buildings. As it can provide wireless positioning service, it is currently the most widely used vehicle navigation system, but indoor positioning is impossible and it can replace GPS, which severely degrades positioning accuracy in the city center.

11 is a diagram illustrating an example of a pattern of change in signal strength received by a vehicle passing through a tunnel section. Currently, a conventional navigation system mounted on a vehicle uses GNSS, for example, GPS for vehicle positioning. Since the signal transmitted from the satellite cannot reach the inside of the tunnel, when the vehicle passes through the tunnel section, the conventional navigation system stays at displaying the preset route, rather than the signal-based location transmitted from the satellite. For this reason, the vehicle speed is not displayed when the vehicle passes through the tunnel section or is fixedly displayed at the speed when entering the tunnel. In the tunnel section, Wi-Fi communication is generally not possible, but a wireless environment is established to enable LTE communication suitable for a vehicle moving at high speed. Since the base station of the LTE network cannot be continuously installed inside the tunnel due to its installation cost and space, multiple repeaters are installed inside the tunnel to amplify and retransmit radio signals between the base station and the base station.

When the vehicle equipped with the wireless positioning apparatus according to this embodiment passed through a tunnel section in which six base stations were installed, an experiment was performed to measure the strength of signals transmitted from the six base stations, and the experimental results are shown in FIG. 11. . In FIG. 11, the surface coordinates of the point where the vehicle wireless positioning apparatus starts to be driven are set to (0, 0), and the east-west direction and the north-south direction are displayed in a scale that increases or decreases in units of 1000 m based on the point. Referring to FIG. 11, it can be seen that the coordinates of the point at which the vehicle enters the tunnel are approximately (-2000, 0). The intensity change of the signal received from the first base station is a thick dashed line, the intensity change of the signal received from the second base station is a thin dashed line, the intensity change of the signal received from the third base station is a thick dotted line, the fourth base station The intensity change of the signal received from is indicated by a thin dotted line, the intensity change of the signal received from the fifth base station is indicated by a thick solid line, and the intensity change of the signal received from the sixth base station is indicated by a thin solid line.

As described above, the strength of a signal transmitted from a fixed node 2, such as an access point of a Wi-Fi network, a base station of an LTE network, or the like, is attenuated roughly in inverse proportion to the square of the distance from the fixed node 2. The intensity of the signal transmitted from the repeater is attenuated roughly in inverse proportion to the square of the distance from the fixed node 2, like other kinds of fixed nodes 2. That is, as the vehicle approaches the repeater, the strength of the signal received from the repeater becomes stronger, and the farther away from the repeater, the strength of the signal received from the repeater becomes weaker. When the vehicle passes through a section in which a plurality of repeaters are continuously installed, the strength of the signal received by the vehicle is repeated stronger and weaker. It can be seen from FIG. 11 that there are several peaks in the signal intensity change pattern for each base station, and it can be predicted that a repeater is installed at the point of occurrence of each peak.

As described above, the change pattern of the signal strength used for the absolute position estimation of this embodiment is related to the ID of the fixed node 2 that sent the signal and the relative position of the mobile node 1 that received the signal. It means the change pattern of the signal strength, which indicates the signal strength. Since the repeater is installed in a signal shaded area near a base station and serves to amplify and retransmit the signal transmitted from the base station, the ID of the signal transmitted from the repeater, that is, the ID of the fixed node 2 that transmitted the signal is It is the same as the ID of the base station. Even when a plurality of repeaters are installed in a signal shaded area near a certain base station, the IDs of signals transmitted from the plurality of repeaters are all the same.

As described above, in an environment such as a tunnel in which a plurality of repeaters are continuously installed, the IDs of signals transmitted from a plurality of repeaters are all the same. The accuracy of the estimated absolute position based on the pattern comparison may be lowered. In an environment in which a plurality of repeaters are continuously installed, such as inside a tunnel, the signal strength peaks repeatedly occur as the signal strength representing one fixed node 2 becomes stronger and weaker. In particular, the peak portion of the signal intensity change pattern has characteristics that are more robust to noise than other portions. Hereinafter, a mobile node (1) in various environments, such as a communication weak environment in which signals can only be received from one fixed node or a tunnel section in which it is difficult to distinguish which signal is transmitted from a fixed node as multiple repeaters are continuously installed ), a wireless positioning algorithm capable of improving the positioning accuracy will be described.

In step 610, the peak detector 21 of the mobile node 1 generates at least one signal intensity change pattern generated in step 320, that is, at least one signal received from at least one fixed node 2 over a plurality of time points. Multiple peaks are detected in the intensity change pattern. 12 is a contrast diagram of the signal change pattern generated in step 320 and the signal distribution pattern received in step 450 shown in FIG. 3. FIG. 12B illustrates an example of a pattern of change in signal strength received over a plurality of time points in a tunnel section in which a plurality of repeaters, which are a kind of the plurality of fixed nodes 2, are continuously installed. In this case, the IDs of the plurality of fixed nodes 2 that transmit a plurality of signals are all the same. In this case, as only one ID is mapped to the x-axis of the three-dimensional coordinate system shown in FIG. 6, the change pattern of the signal strength used in the wireless positioning of the present embodiment is only the y-axis and z-axis of the three-dimensional coordinate system, that is, two-dimensional It can be expressed in a coordinate system.

The x-axis of the 2D coordinate system illustrated in FIG. 12B corresponds to the y-axis of the 3D coordinate system and corresponds to the relative position of the mobile node 1 instead of the relative position of the mobile node 1 for speed estimation. The reception time points are mapped, and the y-axis of the 2D coordinate system corresponds to the z-axis of the 3D coordinate system, and the intensity of the signal transmitted from each fixed node 2 is mapped. The plurality of peaks detected in step 610 are indicated by dots in FIG. 12B. As described above, in step 310, the domain converting unit 14 converts the time domain data generated in step 130 into spatial domain data, and the mobile node 1 corresponding to the reception time of each signal corresponds to the reception time of each signal. ), it is possible to replace the relative position of the at least one signal intensity change pattern generated in step 320 with the reception time of each signal.

In step 620, the peak detection unit 21 of the mobile node 1 receives a plurality of peaks from a map represented by the map data received in step 450, that is, a map in the form of a distribution pattern of signal strength in a region where the mobile node 1 is located. Detects. Peak detection in step 620 may be performed by the location server 3. In this case, the location server 3 may provide the plurality of peaks detected as described above to the mobile node 1 in the form of a map. FIG. 12A shows an example of a signal intensity distribution pattern in the same tunnel section as that of FIG. 12A. Accordingly, the IDs of the plurality of fixed nodes 2 that transmit the plurality of signals shown in FIG. 12A are the same as in FIG. 12B, and the map indicated by the map data received in step 450 is shown. Can be expressed in a 2D coordinate system only for the tunnel section. The absolute position of the mobile node 1 is mapped to the x-axis of the 2D coordinate system illustrated in FIG. 12A, and the strength of the signal transmitted from each fixed node 2 is mapped to the y-axis of the 2D coordinate system. . The plurality of peaks detected in step 620 are indicated by dots in Fig. 12A. Even if the signal is received in the same tunnel section, the intensity change pattern of the signal received by the vehicle may vary depending on the timing of the reception due to noise, which changes from time to time, and the speed of the vehicle.

FIG. 13 is a view showing an example in which the change pattern of the signal intensity is flattened by the peak detector 21 shown in FIG. 2. In general, since the noise has a very high frequency compared to a signal transmitted from the fixed node 2, the change pattern of at least one signal strength generated in step 320 is very irregular due to this noise, as shown in FIG. It appears in a fluctuating form. In a noise-free environment, at least one signal intensity change pattern generated in step 320 approaches the fixed node 2, the stronger the signal strength, and the further away from the fixed node 2, the weaker the signal strength. It appears in the form of a curve, as shown in FIG. 13. It can be seen from FIG. 13 that the peak position of the signal intensity change pattern may change slightly each time the signal intensity is measured due to noise.

In step 610, the peak detection unit 21 of the mobile node 1 smooths through at least one signal intensity change pattern generated in step 320 through regression modeling to increase the accuracy of peak detection, A plurality of peaks can be detected from the flattened signal intensity change pattern. As described above, when the change pattern of at least one signal intensity generated in step 320 is flattened through regression modeling, it is returned to the change pattern of the actual signal intensity in a noise-free environment, and is less affected by noise. In step 620, the peak detection unit 21 performs regression modeling on the distribution pattern of signal intensity in the region where the mobile node 1 is located so that the peak detection result in step 620 matches the peak detection result after being flattened in step 610. Through this, it is possible to detect a plurality of peaks in the flattened signal intensity change pattern. Regression modeling is a technique known to those of ordinary skill in the art to which this embodiment belongs, and a description thereof will be omitted to prevent blurring of features of this embodiment.

In step 630, the peak comparison unit 22 of the mobile node 1 compares the plurality of peaks detected in step 610 with the plurality of peaks detected in step 620, and among the plurality of peaks detected in step 620, it is detected in step 610. In a manner of extracting a plurality of peaks most similar to the plurality of peaks, a portion having a pattern most similar to a change pattern of at least one signal intensity generated in step 320 is found in a map represented by the map data. The portion having the plurality of peaks most similar to the color extracted in operation 630 becomes a portion having the pattern most similar to the change pattern of at least one signal intensity generated in operation 320. In the above-described example, the peak comparator 22 detects the change pattern of the signal intensity up to the T4 time point by comparing the plurality of peaks detected on the map with the plurality of peaks detected on the change pattern of signal intensity up to the T4 time point. Among the plurality of peaks, a portion having a pattern most similar to a change pattern of signal intensity up to a time point T4 in a map is searched for by extracting a plurality of peaks most similar to the plurality of peaks detected on the map.

The color extraction in step 510 is performed by comparing the pattern of the change in signal intensity generated in step 320 with the pattern of the map indicated by the map data, but the color extraction in step 630 is the peak and map of the signal intensity change pattern generated in step 320. This is done by comparing the peaks of the map represented by the data. As described below, the location-based positioning in step 630 has a higher positioning accuracy than the location-based positioning in step 510, but has a high data throughput such as peak detection. In particular, if the peak detector 21 in step 630 detects a plurality of peaks most similar to the plurality of peaks detected in step 610 from the entire map represented by the map data received in step 450, the amount of data to be compared in step 630 is very It can increase.

In order to reduce the amount of data to be compared in step 630, the peak detection unit 21 in step 630 is a unit expected to exist a plurality of peaks most similar to the plurality of peaks detected in step 610 in the map indicated by the map data An area may be set, and only a plurality of peaks most similar to the plurality of peaks detected in step 610 may be found within the unit area. However, if there are no plurality of peaks most similar to the plurality of peaks detected in step 610 in the unit region, the positioning error becomes very large. The initial position of the mobile node 1 set in step 550 serves to select the unit region in order to minimize the probability that there are no multiple peaks most similar to the plurality of peaks detected in step 610 within the unit region. The color extraction unit area may be an area of a certain size in the map or an area that is colored for a predetermined time based on the initial position.

In step 630, the peak comparator 22 of the mobile node 1 compares the plurality of peaks detected in step 610 with the plurality of peaks detected in step 620, thereby setting the mobile node set in step 550 in the map indicated by the map data ( Based on the initial position of 1), at least one signal intensity change pattern generated in step 320 and a method of finding out a plurality of peaks most similar to the plurality of peaks detected in step 610 among the plurality of peaks detected in step 620 and You can find out the part with the most similar pattern. For example, the peak comparator 22 compares a plurality of peaks detected in step 610 with a plurality of peaks detected in step 620, and the initial position of the mobile node 1 set in step 550 in the map indicated by the map data. At least one generated in step 320 in a manner of extracting a plurality of peaks most similar to the plurality of peaks detected in step 610 among the plurality of peaks detected in step 620 in the unit region including the initial position as the starting point of color extraction. The portion having the pattern most similar to the change pattern of the signal strength can be found. Here, step 550 is not the previous step of step 630 in the process in which the steps shown in FIG. 3 are executed in sequence, but the step 550 before step 550 described above when the steps shown in FIG. 3 are repeatedly executed. You can.

The initial position of the mobile node 1 may be a signal intensity change pattern including a plurality of peaks most similar to the plurality of peaks detected in step 610, that is, a possibility that a pattern most similar to the signal intensity change pattern generated in step 320 exists. It may be the center of a unit area within this highest map. The peak comparator 22 is a pattern most similar to a change pattern of at least one signal strength generated in step 320 in a direction radiating around the initial position of the mobile node 1 set in step 550 in the map indicated by the map data. It is possible to find out the part having. If the size of the unit area including the initial position of the mobile node 1 in the map represented by the map data is large enough to ensure that the plurality of peaks most similar to the plurality of peaks detected in step 610 is reliably achieved, the map data is It is not necessary to detect a plurality of peaks most similar to the plurality of peaks detected in step 610 in the entire map shown.

According to the positioning of the present embodiment, whenever a new signal is received from the fixed node, the change pattern of the signal strength received from the fixed node is slightly updated while the absolute value of the mobile node 1 changed according to the movement of the mobile node 1 Since the position is estimated in real time, it is most likely that a pattern most similar to the change pattern of the signal strength received from the fixed node exists at or near the initial position of the mobile node 1. In the present embodiment, among the plurality of peaks detected in step 620 based on the initial position of the mobile node 1 set in step 550 in the map indicated by the map data, the plurality of peaks most similar to the plurality of peaks detected in step 610 are selected. Among the plurality of peaks detected in step 620, the plurality of peaks most similar to the plurality of peaks detected in step 610 can be quickly and accurately searched out. As a result, the initial position-based retrieval enables the fast and accurate retrieval of the current position of the mobile node 1 by enabling the fast and accurate retrieval of the pattern most similar to the signal intensity change pattern received from the fixed node 2 in the map. To do it.

14 is a detailed flowchart of step 630 shown in FIG. 3. Referring to FIG. 14, step 630 illustrated in FIG. 3 includes the following steps executed by the peak comparator 22 illustrated in FIG. 2. In step 631, the peak comparator 22 compares the IDs of the plurality of peaks detected in step 610 with the IDs of each of the plurality of peaks detected in step 610, and among the plurality of peaks detected in step 620, the plurality of peaks detected in step 610. A plurality of peaks having the same ID as each of the peaks is retrieved. Here, the ID of each peak means the ID of the fixed node 2 that has transmitted the signal forming each peak. In step 632, the peak comparison unit 22 checks whether the IDs of the plurality of peaks detected in step 610 correspond to the IDs of the plurality of peaks detected in step 631. As a result of the check in step 632, if the IDs of the plurality of peaks detected in step 610 correspond to the IDs of the plurality of peaks detected in step 631, the process proceeds to step 633. Otherwise, the process proceeds to step 634.

Detected in step 610 when the peak IDs are different for each of the plurality of peaks detected in steps 610 and 631, and a peak having the same ID as the ID of each peak detected in step 631 is present in each of the plurality of peaks detected in step 631. The IDs of the plurality of peaks and the IDs of the plurality of peaks retrieved in step 631 may be mapped one-to-one. In an environment where a base station of an LTE network or an access point of a Wi-Fi network is continuously installed without a repeater that amplifies and retransmits a wireless signal, the ID of the fixed node 2 that transmits each signal for each of the plurality of signals received by the mobile node 1 is Because it is different, the IDs of the plurality of peaks detected in step 610 and the IDs of the plurality of peaks detected in step 631 correspond one-to-one. In this environment, the process proceeds to step 633. On the other hand, in an environment where the repeater is continuously installed, the IDs of the fixed nodes 2 that transmit the multiple signals received by the mobile node 1 overlap, and thus the IDs of the plurality of peaks detected in step 610 and the colors detected in step 631 are retrieved. IDs of multiple peaks cannot be mapped one-to-one. In this environment, the process proceeds to step 634.

In step 633, the peak comparator 22 correlates a plurality of peaks detected in step 631 by one-to-one correspondence between a plurality of peaks detected in step 631 and a plurality of peaks detected in step 610 among peaks having the same ID. It is determined as the part most similar to the plurality of detected peaks. As described above, if the base station of the LTE network or the access point of the Wi-Fi network is continuously installed without a repeater, the peak comparator 22 may include IDs of each of the plurality of peaks detected in step 610 and each of the plurality of peaks detected in 620. By comparing the IDs, a portion most similar to the plurality of peaks detected in step 610 among the plurality of peaks detected in 620 may be found.

In step 634, the peak comparator 22 compares the position patterns of the plurality of peaks detected in step 610 with the position patterns of the plurality of peaks detected in step 631 to detect the peaks detected in step 610 among the plurality of peaks detected in step 631. A plurality of peaks having a position pattern most similar to the position pattern of the plurality of peaks is retrieved. Here, the position pattern of a plurality of peaks means a pattern representing the height of each of the plurality of peaks and the interval between the plurality of peaks. In step 635, the peak comparator 22 correlates the plurality of peaks detected in step 610 with the plurality of peaks detected in step 634 in one-to-one correspondence in order of peak generation, in step 610. Determine the portion most similar to the multiple peaks detected at.

That is, in step 635, the peak comparator 22 corresponds to the first peak among the plurality of peaks detected in step 610 and the first peak among the plurality of peaks detected in step 634, and the plurality of peaks detected in step 610. The next peak among the peaks and the next peak among the plurality of peaks extracted in step 634 are matched. In this manner, the remaining peaks among the plurality of peaks detected in step 610 and the remaining peaks detected in step 634 may also be mapped one-to-one. As described above, if the repeater is continuously installed, the peak comparator 22 compares the position patterns of the plurality of peaks detected in step 610 with the position patterns of the plurality of peaks detected in 620 to detect the plurality of peaks detected in 620. Among them, a portion most similar to the plurality of peaks detected in step 610 may be detected.

In step 640, the speed processing unit 23 of the mobile node 1 between the time difference between the time points between the plurality of peak detection points detected in step 610 and the distance between the locations of occurrences of the most similar multiple peaks detected in step 630 is received. Estimate the speed of the mobile node (1). Here, the reception time of each peak detected in step 610 refers to the reception time of the signal forming the peak, and the occurrence position of each peak detected in step 630 indicates the absolute position of the map mapped to the peak. do. In more detail, in step 640, the speed processing unit 23 corresponds to the time difference between the reception time points of any two peaks among the plurality of peaks detected in step 610 and the two peaks among the most similar plurality of peaks detected in step 630. The speed of the mobile node 1 can be estimated by calculating the distance between the occurrence positions of the two peaks, and dividing the calculated distance by the calculated time difference, thereby calculating the mobile node 1 between the reception points. .

15 is an exemplary view of speed estimation of the speed processing unit 23 shown in FIG. 2. FIG. 15 shows the same signal change pattern and signal distribution pattern as shown in FIG. 12. As shown in FIG. 15B, the speed processing unit 23 calculates a time difference between the reception points of the last two peaks among the plurality of peaks detected in step 610. As shown in FIG. 15(a), the speed processing unit 23 calculates a distance between occurrence positions of the last two peaks that correspond one to one to the last two peaks among the plurality of similar peaks detected in operation 630. The speed processing unit 23 may estimate the speed of the mobile node 1 by calculating the mobile node 1 between the reception points by dividing the calculated distance by the calculated time difference.

In step 640, the speed processing unit 23 calculates a plurality of time differences by calculating a time difference between reception points for two peaks adjacent to each other with respect to the plurality of peaks detected in step 610, and each of the plurality of peaks detected in step 630. A plurality of distances can be calculated by calculating the distance between the generated positions for every two neighboring peaks. The speed processing unit 23 calculates a plurality of speeds from the plurality of time differences calculated as described above and a plurality of calculated distances, and calculates an average of the plurality of speeds to receive the first peak among the plurality of peaks detected in step 610. It is possible to more accurately estimate the speed of the mobile node 1 between and the last peak reception time. The speed processing unit 23 may calculate a plurality of speeds by dividing a plurality of distances into a plurality of speeds corresponding to each of the distances.

12 and 15, the speed processor 23 calculates five time differences by calculating a time difference between reception points for two peaks adjacent to each other for the six peaks detected in step 610, and step 630 Five distances can be calculated by calculating the distance between the occurrence positions of two adjacent peaks for the six peaks detected at. The speed processing unit 23 calculates five speeds by dividing the five distances by five time differences corresponding to each of them, and receiving the first peak among the six peaks detected in step 610 by calculating the average of the five speeds It is possible to more accurately estimate the speed of the mobile node 1 between the starting point and the last peak.

As described above, it is possible to know the exact reception time point of each signal for the signal intensity change pattern generated in step 320, and for the map indicated by the map data received in step 450, the exact reception position of each signal can be known. Therefore, the speed of the mobile node 1 can be accurately estimated. The mobile node 1 may display the estimated speed of the mobile node 1 to the user. Since the signal transmitted from the satellite cannot reach the inside of the tunnel, the conventional navigation system when the vehicle passes through the tunnel section does not display the vehicle speed when the vehicle passes through the tunnel section or is fixedly displayed at the speed when entering the tunnel. According to this embodiment, it is possible to display the correct speed of the mobile node 1 to the user even in an environment in which a GPS signal cannot be received, such as a tunnel section or a city center. As a result, it is possible to prevent an overspeed accident that occurs when the vehicle speed is not displayed accurately.

In operation 650, the location processing unit 24 of the mobile node 1 compares peaks in operation 630, that is, a plurality of peaks detected in at least one signal intensity change pattern generated in operation 320 and map data received in operation 450. The current position of the mobile node 1 is determined based on comparison with a plurality of peaks detected on the map represented by. That is, in operation 650, the location processing unit 24 determines the current location of the mobile node 1 using the locations of the plurality of similar peaks found in operation 630. As described above, a portion having a plurality of the most similar peaks extracted in step 630 becomes a portion having a pattern most similar to the change pattern of at least one signal strength generated in step 320. In the above example, the location processing unit 24 uses the location of occurrence of the most similar multiple peaks found in step 630 as the absolute location of the map indicated by the portion having the pattern most similar to the change pattern of signal strength up to the time T4. It can be said that the current position of the mobile node 1 is determined.

Accordingly, even if a wireless environment change such as signal interference between communication channels, expansion of an access point, failure or obstacle occurs, it is possible to accurately estimate the position of a mobile node, as well as a signal from only one fixed node 2 The location accuracy of a mobile node can be greatly improved in various environments, such as a tunnel environment where it is difficult to distinguish which signal is transmitted from a fixed node (1) as a communication weak environment capable of receiving or multiple repeaters are continuously installed. have. The TDOA technique, which is currently widely used as an LTE signal-based wireless positioning technology, is impossible to locate in a weak communication environment or a tunnel section in which a plurality of repeaters are continuously installed, which can receive signals only from one fixed node. The wireless positioning technology is a communication vulnerable environment that can receive signals only from one fixed node (2) or a tunnel section in which it is difficult to distinguish which signal is sent from a fixed node (1) as a plurality of repeaters are continuously installed. , As the positional accuracy of a mobile node can be greatly improved in various environments, it is possible to overcome the disadvantages of various conventional wireless positioning technologies, each of which has its own unique advantages and disadvantages, thereby overcoming the limitations of the wireless positioning technologies that have emerged so far. have.

The current position of the mobile node 1, which is the result of the execution of step 520, is determined each time a routine of the surface surface correlation (CSC) corresponding to steps 320, 510, and 520 shown in FIG. 3 is repeated. The current position of the mobile node 1, which is the result of the operation in step 650, is determined whenever the Precise Surface Correlation (PSC) routine corresponding to steps 610, 620, 630, and 650 is repeated. In this embodiment, the PSC routine is started when the initial position of the mobile node 1 is set in step 550. That is, the PSC routine is not executed when the initial position of the mobile node 1 is not set. As described above, the current position of the mobile node 1 determined whenever the PSC routine is repeated is a tunnel section in which a plurality of repeaters are continuously installed than the current position of the mobile node 1 determined whenever the CSC routine is repeated. In the location accuracy of the mobile node 1 is high. Each time the PSC routine is repeated, the PSC routine has a much higher data throughput than the CSC routine because the peaks must be detected from the at least one signal intensity change pattern generated in step 320 and the map indicated by the map data received in step 450. .

Accordingly, only the current position of the mobile node 1 determined whenever the PSC routine is repeated may be used as a result of the wireless positioning according to the present embodiment, but real-time performance of the wireless positioning may be deteriorated. On the other hand, the current position of the mobile node 1 determined whenever the CSC routine is repeated can be updated at a much shorter interval than the current position of the mobile node 1 determined each time the PSC routine is repeated. This embodiment can improve both real-time and accuracy of radio positioning by replacing some of the plurality of current positions continuously determined according to the repetition of the CSC routine with current positions determined according to the repetition of the PSC routine.

In step 650, the position processing unit 24 compensates for the error of the absolute position estimated in step 520 by using the occurrence positions of the plurality of similar peaks found in step 630, and the mobile node (1) ). As described above, the relative position of the mobile node 1 is not continuously estimated based on the previous relative position of the mobile node 1, but is absolute when the relative position of the mobile node 1 is replaced with an absolute position Since it is estimated based on the position, if the error of the absolute position estimated in step 520 is compensated, the accuracy of the absolute position estimated in step 520 is improved, and the next 230 steps according to the repetition of the wireless positioning method shown in FIG. The accuracy of the relative position of the mobile node 1 estimated at can also be improved. As the accuracy of the relative position of the mobile node 1 estimated in step 230 is improved, the accuracy of the absolute position estimated in step 520 is improved, and the absolute position is repeatedly estimated according to the iteration of the wireless positioning method illustrated in FIG. 3. The accuracy of can be improved as a whole.

In step 650, the position processing unit 24 is a mobile node estimated in step 520 in a direction in which an error of the occurrence positions of the plurality of peaks detected in step 610 with respect to the positions of occurrence of the most similar multiple peaks detected in step 630 is removed ( By shifting the absolute position of 1), the error of the absolute position of the mobile node 1 calculated in step 520 is compensated. In more detail, in step 650, the position processing unit 24 corresponds to the distance between the occurrence positions of any two peaks among the plurality of peaks detected in step 610 and the two peaks among the most similar plurality of peaks detected in step 630. The distance between the occurrence positions of the two peaks is calculated, and the difference between the two distances calculated in this way is the error of the occurrence positions of the plurality of peaks detected in step 610 with respect to the occurrence positions of the plurality of similar peaks found in step 630. Calculate as

16 is a view showing an example of position error correction in step 650 shown in FIG. FIG. 16A shows an example of a pattern of change in signal strength received over a plurality of viewpoints in an area where a plurality of access points are continuously installed. The position processing unit 24 calculates the distance between the peaks having the ID of the fourth access point and the peaks having the ID of the tenth access point as 25 meters among the plurality of peaks detected in step 610. Subsequently, the position processing unit 24 calculates the distance between the peaks having the ID of the fourth access point and the peaks having the ID of the tenth access point as 30 meters among the plurality of the most similar peaks found in operation 630. Subsequently, the position processing unit 24 subtracts the calculated distance of 25 meters from the calculated distance of 30 meters to generate the positions of the plurality of peaks detected in step 610 with respect to the positions of the plurality of similar peaks found in step 630. Yields an error of 5 meters.

Since the absolute position of the mobile node 1 calculated in step 520 is estimated based on a change pattern of signal intensity corresponding to a source of a plurality of peaks detected in step 610, this position error has an error corresponding to 5 meters. . Subsequently, the position processing unit 24 shifts the absolute position of the mobile node 1 estimated in step 520 in the direction in which the position error 5 meters is removed, thereby correcting the error of the absolute position of the mobile node 1 calculated in step 520. To compensate. For example, the position processor 24 determines the absolute position of the mobile node 1 calculated in step 520 from the occurrence position of the peak having the ID of the fourth access point to the occurrence position of the peak having the ID of the tenth access point. By moving by 5 meters in the direction facing, it is possible to compensate for the error of the absolute position of the mobile node 1. In step 640, the speed processing unit 23 calculates a distance between the occurrence positions of two peaks adjacent to each other with respect to the plurality of peaks detected in step 610, and occurs in every two peaks adjacent to each other with respect to the plurality of peaks detected in step 630. It is also possible to calculate the distance between the positions and to repeat the error compensation of the absolute position of the mobile node 1 for every two neighboring peaks using this, so that the accuracy of the absolute position of the mobile node 1 can be further improved.

FIG. 17 is a detailed flowchart of step 530 shown in FIG. 3. Referring to FIG. 17, step 530 illustrated in FIG. 3 includes the following steps executed by the initial position setting unit 40 illustrated in FIG. 2. In step 531, the initial position setting unit 40 is an index inversely proportional to a plurality of similarities between parts in the map sequentially compared in step 510 and at least one signal intensity change pattern generated in step 320, in step 510. A plurality of correlation distances corresponding to the difference between the parts in the map to be compared and the change pattern of at least one signal intensity generated in step 320 is calculated.

According to the above, the parts in the map sequentially compared in step 510 are at least one signal generated in step 320 in the process of finding out a part having a pattern most similar to the change pattern of at least one signal strength generated in step 320. It means the parts in the map that are sequentially compared to the intensity change pattern. In the above-described example, the initial position setting unit 40 is a part in the map compared to the change pattern of the signal strength up to the T4 time in the process of finding the part having the pattern most similar to the change pattern of the signal strength up to the time T4 And a plurality of correlation distances corresponding to the difference between the signal intensity change patterns up to the time T4.

As described above, in step 510, the signal comparator 18 moves the pattern of change in signal strength generated in step 320 on the map indicated by the map data received in step 450, and changes the pattern of signal strength generated in step 320. It sequentially compares the parts in the map that overlap with this as it moves. In step 531, the initial position setting unit 40 calculates a difference between each portion in the map overlapping the signal intensity change pattern and the signal intensity change pattern according to the movement of the signal intensity change pattern in step 510. Each correlation distance can be calculated. For example, the initial position setting unit 40 may calculate, as each correlation distance, the number of pixels located outside each portion of the map overlapping this among the pixels constituting the change pattern of the signal strength generated in step 320. have.

In more detail, the initial position setting unit 40 calculates a plurality of surface correlation distances corresponding to differences between surface parts in the map sequentially compared in step 510 and the three-dimensional pattern of the surface generated in step 320. do. In the above example, the initial position setting unit 40 corresponds to the difference between the surface parts in the map that are sequentially compared in step 510 and the change in the signal strength up to the point of time T5, in the form of a geometric surface-shaped three-dimensional pattern. To calculate a plurality of surface correlation distances. Here, the surface correlation distance is a correlation distance in 3D space, and if the shape between the 3D pattern of the surface generated in step 320 and the surface portion extracted in step 510 is the same, it becomes 0, and is different from each other. Increases as it flies. For example, the initial position setting unit 40 calculates, as each correlation distance, the number of pixels located outside each part of the map overlapping this among the pixels constituting the surface-shaped 3D pattern generated in operation 320. Can.

In step 532, the initial position setting unit 40 generates a plurality of correlation distance variation patterns calculated in step 531, that is, a plurality of surface correlation distance variation patterns calculated in step 531. These multiple surface correlation distances are calculated at different time points. The initial position setting unit 40 maps a calculation time point of each surface correlation distance calculated in step 531 to one axis in the two-dimensional space for each of the plurality of surface correlation distances calculated in step 531, and 531 to the other axis. A method of displaying a dot at a point in a two-dimensional space determined by mapping the size of each surface correlation distance calculated in step, and flattening a connection line of a plurality of dots corresponding to the plurality of correlation distances calculated in step 531 A pattern of changing the plurality of surface correlation distances calculated in the step is generated. Here, one axis of the two-dimensional space is a coordinate axis that divides the time at which the 510 step of color extraction is performed in a certain unit, and the other axis is a coordinate axis that divides a range of surface correlation distances in a constant unit.

18-20 are views illustrating an example of a change pattern of the surface correlation distance generated in operation 532 shown in FIG. 17. Immediately after the operation of the wireless positioning device shown in FIG. 2 starts, the number of pattern data accumulated in the buffer 30 is small because the number of repetitions of the steps shown in FIG. 3 is small, and thus the mobile node 1 estimated in step 520. The accuracy of the absolute position of, i.e., the reliability of the absolute position of the mobile node 1 is low. As the steps illustrated in FIG. 3 are continuously repeated, the reliability of the absolute position of the mobile node 1 increases as the amount of pattern data accumulated in the buffer 30 increases. This embodiment calculates the reliability of the absolute position of the mobile node 1 from the change pattern of the surface correlation distance generated in step 532. 18-20, in the situation where the reliability of the absolute position of the mobile node 1 gradually increases as the amount of pattern data accumulated in the buffer 30 increases after the wireless positioning device shown in FIG. 2 starts to be driven. A total of six pattern examples are shown.

The x-axis of each graph of FIGS. 18-20 represents the time at which the 510-step search is performed, that is, 0 to 200 epoch (epoch, 1 epoch = 2 second), and the y-axis represents the range of the surface correlation distance, that is, 0 to 2000. Since the surface correlation distance of this embodiment is not a geographic distance, it is not expressed in units of meters or the like, and as described above, it can be expressed in the number of pixels. A thin solid line having a very irregularly vibrating shape corresponds to a connection line of a plurality of dots, and a thicker solid line is a change pattern of the surface correlation distance generated in step 532, and the thin solid line is the same as the flattening method of FIG. 13. It is flattened. 18-20(a) shows a change pattern of the surface correlation distance in a state in which the number of repetitions of the steps shown in FIG. 3 is the smallest. Referring to FIGS. 18-20 (a) to (f), as the steps shown in FIG. 3 are continuously repeated, the pattern of change in the surface correlation distance increases as the amount of pattern data accumulated in the buffer 30 increases. It can be seen that it gradually changes to a parabolic shape.

In the state in which the amount of pattern data accumulated in the buffer 30 is small because the number of repetitions of the steps shown in FIG. 3 is small, the size of the surface correlation distance is small as the data size of the surface-shaped pattern generated in step 320 is small. However, the ability to discriminate the shape of the surface matching this from the map is reduced, and thus the surface correlation distances of similar sizes are distributed at various viewpoints. As the amount of pattern data accumulated in the buffer 30 gradually increases, that is, as the process proceeds from (a) to (f) of FIGS. 18-20, the size of the surface correlation distance increases somewhat, but this is within the map. As the ability to discriminate between and matching surface shapes improves, the surface correlation distance rapidly decreases when a certain part of the map matches the surface shape pattern generated in step 320. From this, it can be seen that as the change pattern of the surface correlation distance generated in step 532 becomes a sharper parabolic shape, the reliability of the absolute position of the mobile node 1 estimated in step 520 increases.

In step 533, the initial position setting unit 40 detects the lowest peak and the secondary lower peak of the variation pattern of the plurality of correlation distances generated in step 532. In each of (a) to (f) of FIGS. 18-20, the lowest peak is indicated by "①", and the lower peak is indicated by "②". In step 534, the initial position setting unit 40 calculates the reliability of the absolute position of the mobile node 1 estimated in step 520 based on the ratio of the lowest peak and the lower peak detected in step 533. In more detail, the initial position setting unit 40 divides the value of the difference peak detected in step 533 by the value of the lowest peak detected in step 533 to determine the absolute position of the mobile node 1 estimated in step 520. To calculate the reliability. As described above, the initial position setting unit 40 in steps 533 and 534 is the mobile node 1 estimated in step 520 based on the plurality of correlation distance change patterns generated in step 532, that is, the plurality of surface correlation distance change patterns. ) Is selected as the initial position of the mobile node 1.

In the change pattern of the surface correlation distance shown in (a), (b), (c), and (d) of FIGS. 18-20, the mobile node because the difference in size between the lowest peak and the lower peak detected in step 533 is small. The magnitude of the reliability of the absolute position in (1) becomes small. Since the change pattern of the surface correlation distance shown in (e) and (f) of FIGS. 18-20 has a parabolic shape, only the lowest peak is present alone, and no difference peak is present. In this case, the reliability of the absolute position of the mobile node 1 is set to the maximum value. The reference value of the reliability of the absolute position of the mobile node 1 is the lowest difference peak detected in the change pattern of the surface correlation distance shown in (a), (b), (c), and (d) of FIGS. 18-20. If it is set higher than the value divided by the peak, the initial position of the mobile node 1 is set only when the change pattern of the surface correlation distance of the parabolic shape as shown in (e) and (f) of FIGS. 18-20 is represented. .

According to the above example, when the steps shown in FIG. 3 are executed again from the beginning after the execution of steps 530 and subsequent steps is completed, a signal is received fifth in step 110. If the PSC is executed once every time the CSC is executed twice, the PSC is executed only when the sixth execution is performed after the steps shown in FIG. 3 are executed five times. The sixth execution of the steps shown in FIG. 3 begins when the signal is received from step 110 to the sixth. Thereafter, in step 320, the pattern generator 15 generates at least one change pattern of signal strength received from at least one fixed node 2 until the time T6.

In step 630, the peak comparator 18 compares a plurality of peaks detected in the signal intensity change pattern up to the time T6 to a plurality of peaks detected in the map indicated by the map data, and the step illustrated in FIG. 3 in the map. Based on the initial position set in step 530 of the fourth execution, i.e., using the initial position as the starting point for the search, among the peaks detected in the pattern of change in signal intensity up to the time T6, it is most similar to the plurality of peaks detected on the map. In a manner of extracting a plurality of peaks, a portion having a pattern most similar to a change pattern of signal intensity up to the time T6 is searched. According to the above, in step 650, the position processing unit 24 is the absolute position of the map indicated by the portion having the pattern most similar to the change pattern of signal intensity up to the time T6, and the generation of the plurality of similar peaks detected in step 630 occurs. The current location of the mobile node 1 is determined using the location.

In the above, the case where positioning in the PSC routine corresponding to steps 610, 620, 630, and 650 is executed at a high speed by using the initial position set in step 530 is very accurate. By using the initial position set in step 530, the positioning in the CSC routines corresponding to steps 320, 510, and 520 can also be executed very accurately and at high speed. That is, in step 510, the signal comparator 18 simulates a change pattern of signal strength up to the time point T6 based on the initial position set in step 530 of the fifth execution of the steps shown in FIG. 3 in the map indicated by the map data. It is possible to find out parts having a similar pattern. For example, the signal comparison unit 18 is the pattern most similar to the change pattern of the signal strength up to the T6 time point within a region of a certain size centered on the initial position set in step 530 among the map regions indicated by the map data. It is also possible to color the portion having.

According to the wireless positioning technique of this embodiment, after the start of the wireless positioning device, the steps of the wireless positioning method are continuously repeated, so that the data size of the change pattern of signal strength received from the fixed node 2 is gradually increased. When the data size of the signal intensity change pattern is small, the accuracy of radio positioning decreases as the ability to distinguish a surface shape matching this from the map decreases. This embodiment is the pattern most similar to the change pattern of the signal strength up to a point after the point in the map based on the initial position of the mobile node set based on the similarity between the pattern of change of the signal intensity up to a certain point and the extracted part. By detecting the part having the signal intensity, the pattern of the area where the mobile node 1 is not actually located is blocked from the fixed node 2 by blocking the pattern search in the area where the pattern most similar to the pattern of the signal strength is unlikely to exist. It is possible to prevent a case in which the color is incorrectly colored in a pattern similar to the pattern of change in the received signal strength.

In this way, even when the data size of the signal intensity change pattern used for radio positioning is small, it is prevented that the pattern of the region where the mobile node 1 is not actually located is incorrectly colored in a pattern similar to the signal intensity change pattern. As it can, the position accuracy of the mobile node 1 can be increased to a certain level or more that can be used for a vehicle navigation system or autonomous driving within a very short time after the start of the wireless positioning of the present embodiment. Particularly, when the position of a mobile node is estimated using a radio signal with little change in signal strength over a large area, such as an LTE signal, if the data size of the pattern of change in signal strength used for radio positioning is small, the mobile node It is highly probable that the pattern in the region where (1) is not actually located is incorrectly colored in a pattern similar to the change pattern of signal strength received from the fixed node. This embodiment can provide a very high accuracy positioning service at the initial stage of execution of wireless positioning even when the position of a mobile node is estimated using a wireless signal with little change in signal strength over a large area, such as an LTE signal. have.

Due to signal interference between communication channels, expansion of access points, changes in radio environment such as failures or obstacles, or noise, a signal strength different from the signal strength collected at the time of radio map construction may occur. In this case, the variation pattern of the signal strength received from the fixed node 2 includes the measured signal strength, and thus the similarity between the variation pattern of the signal strength and the extracted portion, that is, the mobile node estimated according to the present invention ( The position reliability of 1) becomes low. In this case, in this case, the initial position of the mobile node 1 is not set, that is, the initial position is not updated, and thus the pattern of the region where the mobile node 1 is not actually located is fixed. It is possible to prevent a case in which color is incorrectly colored in a pattern similar to the pattern of change in signal strength received from (2).

In the above, the superiority of the positioning accuracy of the wireless positioning algorithm of the present embodiment has been described for the case of using the Wi-Fi signal and the LTE signal, but there is no limit to the signal that can be used for the wireless positioning according to the present embodiment, and Bluetooth, Zigbee, Laura, etc Positioning according to the radio positioning of the present embodiment may be performed using the same radio signal strength.

On the other hand, the composite positioning method according to an embodiment of the present invention as described above can be written in a program executable on a processor of a computer, and implemented in a computer that records and executes the program on a computer-readable recording medium. have. A computer includes any type of computer capable of executing a program, such as a desktop computer, a notebook computer, a smart phone, or an embedded type computer. In addition, the structure of the data used in the above-described embodiment of the present invention can be recorded on a computer-readable recording medium through various means. The computer-readable recording medium is a storage device such as RAM, ROM, magnetic storage medium (eg, floppy disk, hard disk, etc.), optical read media (eg, CD-ROM, DVD, etc.). Includes media.

So far, the present invention has been focused on the preferred embodiments. Those skilled in the art to which the present invention pertains will understand that the present invention can be implemented in a modified shape without departing from the essential characteristics of the present invention. Therefore, the disclosed embodiments should be considered in terms of explanation, not limitation. The scope of the present invention is shown in the claims rather than the foregoing description, and all differences within the equivalent range should be interpreted as being included in the present invention.

1 ... mobile node
10 ... wireless communication unit 20 ... sensor unit
30 ... buffer 40 ... initial position setting part
11 ... scan unit 12 ... signal processing unit
13 ... Relative position estimation unit 14 ... Domain conversion unit
15 ... pattern generation unit 16 ... cluster selection unit
17 ... Map loader 18 ... Signal comparator
19 ... absolute position estimation unit
21 ... peak detector 22 ... peak comparator
23 ... speed processing unit 24 ... position processing unit
2, 21, 22, 23, 24 ... fixed nodes
3 ... positioning server

Claims (16)

A change pattern of at least one signal strength represented by a continuous sequence of strengths of at least one signal received multiple times at multiple locations of a mobile node from at least one fixed node up to a first time point. Generating a change pattern of at least one signal strength according to a relative change in position;
Finding a portion having a pattern most similar to a change pattern of signal strength up to the first viewpoint in a map in the form of a distribution pattern of signal strength in an area where the mobile node is located;
Setting an initial position of the mobile node on the basis of the similarity between the pattern of change in signal strength up to the first time point and the extracted portion;
At least one signal strength change pattern represented by a continuous sequence of at least one signal strength received at a plurality of times from a plurality of locations of the mobile node from at least one fixed node until a second time point, the mobile node until the second time point Generating a change pattern of at least one signal strength according to a relative change in the position of the;
Finding out a portion of the map having a pattern most similar to a change pattern of signal strength up to the second viewpoint based on the initial position; And
And determining the location of the mobile node using the location of the map indicated by the portion having the pattern most similar to the pattern of change in signal strength up to the second time point. delete According to claim 1,
The method further includes estimating the location of the map indicated by the portion having the pattern most similar to the change pattern of signal strength up to the first time point as the location of the mobile node,
The setting of the initial position may include setting the initial position by selecting the estimated position of the mobile node as the initial position on the basis of the similarity between the pattern of change in signal strength up to the first time point and the extracted part. Wireless positioning method characterized by. According to claim 1,
The setting of the initial position includes parts in the map that are compared to a change pattern of signal intensity up to the first point in the process of finding a portion having a pattern most similar to a change pattern of signal intensity up to the first point in time. And setting an initial position of the mobile node based on a plurality of similarity change patterns between the signal intensity change patterns up to the first time point. The method of claim 4,
The method further includes estimating the location of the map indicated by the portion having the pattern most similar to the change pattern of signal strength up to the first time point as the location of the mobile node,
The setting of the initial position calculates the reliability of the estimated position of the mobile node based on the variation pattern of the plurality of similarities, and selects the estimated position of the mobile node as the initial position according to the reliability of the position Wireless positioning method, characterized in that by setting the initial position. According to claim 1,
The setting of the initial position is an index inversely proportional to the similarity between the pattern of change in signal intensity up to the first time point and the extracted part, and the difference between the pattern of change in signal intensity up to the first time point and the extracted part. And calculating a corresponding correlation distance and setting an initial position of the mobile node based on the calculated correlation distance. The method of claim 6,
The method further includes estimating the location of the map indicated by the portion having the pattern most similar to the change pattern of signal strength up to the first time point as the location of the mobile node,
The step of setting the initial position is to set the initial position by selecting the estimated position of the mobile node based on the calculated correlation distance as the initial position. The method of claim 7,
The step of setting the initial position
Signals up to the first point and parts in the map compared to the change pattern of the signal intensity up to the first point in the process of finding a part having a pattern most similar to the change pattern of the signal intensity up to the first point in time Calculating a plurality of correlation distances corresponding to differences between intensity change patterns;
Generating a variation pattern of the calculated plurality of correlation distances; And
And selecting a position of the estimated mobile node as an initial position of the mobile node based on the change pattern of the plurality of correlation distances. The method of claim 8,
The step of selecting the initial position is
Detecting a lowest peak and a lower peak of the plurality of correlation distance variation patterns;
Calculating a reliability of a position of the estimated mobile node based on a ratio of the detected lowest peak and difference peak; And
And if the reliability is higher than a reference value, selecting the estimated location of the mobile node as the initial location. The method of claim 9,
The calculating of the reliability may include calculating the reliability by dividing the detected difference peak value by the detected lowest peak value. According to claim 1,
The signal intensity change pattern up to the first time point is a geometric surface pattern that graphs a change in signal intensity up to the first time point according to a relative change in the position of the mobile node,
The step of finding a portion having a pattern that is most similar to the pattern of change in signal strength up to the first time point is a surface shape of a pattern of geometric surface shape graphing the change in signal strength up to the first time point in the map. Wireless positioning method, characterized in that for detecting the surface portion having the form most similar to. According to claim 1,
The step of searching for a portion having a pattern most similar to the change pattern of the signal strength up to the second time point may include a plurality of peaks detected in the change pattern of the signal strength up to the second time point and a plurality of peaks detected on the map. By comparing the plurality of peaks most similar to the plurality of peaks detected on the map among the plurality of peaks detected in the pattern of changing the signal strength up to the second time point based on the initial position in the map, A wireless positioning method, characterized in that a portion having a pattern most similar to a change pattern of signal strength up to a second time point is found. The method of claim 12,
The step of determining the location of the mobile node is a location of a map indicated by a portion having the pattern most similar to the change pattern of signal strength up to the second time point, and uses the locations of occurrence of the plurality of similar peaks found in step 630. Wireless positioning method, characterized in that to determine the location of the mobile node. According to claim 1,
The step of finding a portion having a pattern most similar to the pattern of change in signal strength up to the second time point is a pattern most similar to the pattern of change in signal strength up to the second time point, using the initial position as the starting point of color search in the map Wireless positioning method, characterized in that for finding the portion having. A computer-readable recording medium recording a program for executing the method of any one of claims 1, 3 to 14 on a computer. A change pattern of at least one signal strength represented by a continuous sequence of strengths of at least one signal received multiple times at multiple locations of a mobile node from at least one fixed node up to a first time point. A pattern generator configured to generate a change pattern of at least one signal strength according to a relative change in position;
A signal comparator for detecting a portion having a pattern most similar to a change pattern of signal strength up to the first viewpoint in a map in the form of a distribution pattern of signal strength in an area where the mobile node is located;
An initial position setting unit configured to set an initial position of the mobile node based on a similarity between a pattern of change in signal strength up to the first time point and the extracted part; And
And a location processor configured to determine the location of the mobile node using the location of the map indicated by the portion having the pattern most similar to the pattern of change in signal strength up to the second time point,
The pattern generation unit is the second pattern as a change pattern of at least one signal strength represented by a continuous sequence of at least one signal strength received multiple times at multiple locations of the mobile node from at least one fixed node until the second time point. Generating a change pattern of at least one signal strength according to the relative change of the position of the mobile node until the time point,
A wireless positioning apparatus characterized in that a portion having a pattern most similar to a pattern of a change in signal strength up to the second viewpoint based on the initial position is found in the map.

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