WO2019004538A1 - Inertial sensor calibration method - Google Patents

Abstract

The present invention relates to a method of calibrating an inertial sensor, and more particularly, to a method of calibrating a scale factor of an inertial sensor even in a shaded area in which a GNSS signal is not received, To an accurate DR (Dead Reckoning) positioning by calculating a scale factor of an inertia sensor using an indoor map of a map.

Description

Inertial Sensor Calibration Method

The present invention relates to a method of calibrating an inertial sensor, and more particularly, to a method of calibrating a scale factor of an inertial sensor even in a shaded area in which a GNSS signal is not received, The present invention relates to a method for accurately estimating dead reckoning (DR) by calculating a scale factor of an inertial sensor using an indoor map of a map.

In general, a navigation system using a Global Navigation Satellite System (GNSS) signal is widely used. However, since this navigation system does not know the position information when the GNSS signal is not received, a navigation system that uses the inertial sensor or the inertial sensor and the GNSS together to obtain the position information of the vehicle has been developed.

This navigation system can estimate the position of a moving object by using an inertial sensor based on a MEMS (Microelectromechanical Systems) called an Inertial Measurement Unit (IMU). In this navigation system, the position information of the moving object is obtained using a predetermined navigation calculation algorithm. In this case, the position information can be obtained by integrating inertia data (e.g., acceleration, angular velocity, etc.) obtained in the IMU.

The inertial navigation system uses a navigation algorithm to calculate the information of the attitude, speed, and position of the vehicle. The navigation calculation algorithm is based on an output from the inertial measurement unit (IMU) of the body frame Sensor output value is used. The assumption is that the coordinate system of the inertial measurement unit (IMU), which consists of a three-axis accelerometer and a three-axis gyro, should be mounted exactly in line with the vehicle's body frame.

However, in the case of an inertial measurement unit (IMU) mounted on a vehicle, there is a possibility that there is a deviation between the body coordinate system and the sensor coordinate system due to a close coincidence in the snow or a movement and / or vibration of the vehicle. , ≪ / RTI > and / or location information.

As a technique for improving such errors or inaccuracies, a navigation system using sensor frame calibration and a method for providing the same is proposed in Korean Patent Publication No. 2011-0130775, which is shown in FIG.

This conventional technique includes the IMU 110, the calibration module 120, and the navigation calculation module 130 in the navigation system 100 using the sensor frame calibration. The navigation system 100 using the sensor frame calibration may further include a GPS module 140. The navigation calculation module 130 may be an inertial navigation system that calculates positional information of a moving object using only the inertial data output from the IMU 110. The GPS module 140 may include a navigation system 100 using sensor frame calibration, It may be a navigation system that calculates the position information of the moving object by using the inertia data output from the IMU 110 and the GPS information output from the GPS module 140. [

However, such a conventional technique includes both the acceleration sensor 111 and the gyro sensor 112 when only the inertial data output from the IMU is used, and in the case of including the GPS module that receives the GPS information from the satellite, And GPS information received from the GPS module to perform calibration. In the case of using only inertia data in the case of a GPS shaded area, an acceleration sensor should be additionally provided, If the GPS module is included, there is a problem that the inertial sensor can not be calibrated.

In addition, the position error of the vehicle caused by the inertial sensor corresponds to a position error that is negligible when the driver directly drives the vehicle. However, in the case of a vehicle capable of autonomous driving other than the driver, the position error causes a serious situation .

It is an object of the present invention to enable precise DR (dead reckoning) positioning by correcting the scale factor of the gyro sensor in the reception shadow area of the GNSS data as well as in the open space.

An object of the present invention is to provide a method of calibrating an inertial sensor, comprising: determining whether a vehicle has an indoor map when entering a GNSS shaded area; Determining reference data to be compared with the rotation angle of the gyro sensor and storing an azimuth angle of the shaded area entry point when the vehicle does not have the indoor map; Accumulating rotational angles obtained by integrating angular velocity values of the gyro sensor according to running of the vehicle; Determining whether a rotation angle of the gyro sensor is greater than or equal to a critical angle, and storing an azimuth angle of the shaded region entry point if the angle is greater than a critical angle; Calculating a difference between an azimuth angle of the entry point and an azimuth angle of the entry point; Converting the accumulated rotation angle of the gyro sensor to a 360 degree reference; Calculating a scale factor error by dividing a difference value between the azimuth of the entry point and the azimuth of the entry point by the rotation angle of the gyro sensor converted to 360 degrees reference, And the inertial sensor calibration method is characterized in that the calibration is carried out by an erroneous vehicle.

The present invention has the effect of enabling precise DR positioning by correcting the scale factor of the gyro sensor by using an ingress / egress link, GNSS data, or indoor map when there is rotation in the trajectory of the vehicle in the reception shadow area of the GNSS data have.

1 is a schematic configuration diagram of a navigation system using frame calibration according to a conventional technique,

2 is a schematic configuration diagram for inertial sensor calibration according to the present invention,

3 is a flow chart for inertial sensor calibration according to the present invention,

4 is a detailed flowchart for an approach azimuth angle resolution according to the present invention.

The terms and words used in the present specification and claims should not be construed as limited to ordinary or dictionary terms and the inventor may appropriately define the concept of the term in order to best describe its invention It should be construed as meaning and concept consistent with the technical idea of the present invention.

Therefore, the embodiments described in this specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention and do not represent all the technical ideas of the present invention. Therefore, It is to be understood that equivalents and modifications are possible.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

2 is a schematic block diagram for inertial sensor calibration according to the present invention. 2, the present invention includes a GNSS receiver, a gyro sensor, an outdoor precision leader, an indoor precision leader, a DR processor, and a vehicle position output unit.

The GNSS receiver receives the GNSS satellite signal, measures the reliability of the calculated azimuth information, and transmits the calculated azimuth information to the DR processor when the reliability is higher than the threshold reliability, and the gyro sensor transmits the angular velocity of the gyro sensor to the DR fusion processor.

The outdoor precision leadership determines whether there is an entry / exit link at the time of entering the shade section, and when it is held, the azimuth angle of the entry / exit link is transmitted to the DR processing section. When the driving vehicle enters the shade section, And if the interior precision map is held, calculates the cumulative sag of the map according to the driving trajectory while the vehicle is traveling inside the building (shaded area), and transfers the accumulated sag angle to the DR processing unit.

Here, the outdoor precision leader and the indoor precision leader are examples, and the outdoor leader and the indoor leader may be constructed instead of the precision map.

In addition, the DR processor receives the entrance / exit heading angle or the indoor map cumulative rotation angle from the outdoor precision leader, the indoor precision leader, and the GNSS receiver when entering the shade section, compares the value with the rotation angle calculated from the accumulated gyro sensor angular velocity, Calculates a factor, and calculates a precise position.

The vehicle position output unit receives the precise position from the DR processing unit and outputs the precise position to a screen or the like.

Figure 3 shows a flow chart for inertial sensor calibration according to the present invention. As shown in FIG. 3, the inertial sensor calibration method of the present invention determines whether a vehicle has an indoor map when it enters a shaded area of a GNSS (S101) (S102).

If the vehicle does not have the indoor map (No in S102), the reference data to be compared with the rotation angle of the gyro sensor is determined and the azimuth of the shadow area entry point (start) is stored (S103).

Then, the rotation angle obtained by integrating the angular velocity values of the gyro sensor due to the running of the vehicle is accumulated (SIGMA PS) (S104), and it is determined whether the rotation angle of the accumulated gyro sensor is equal to or greater than the critical angle (S105) Stores the azimuth angle of the entry point (end), and calculates the difference? H between the azimuth of the entry point and the azimuth of the entry point (S106 and S107).

The rotation angle? Of the gyro sensor is converted to 360 degrees (??) (S108). The conversion to the 360 degree reference is 40 degrees when the accumulated angle is 400 degrees, 600 degrees when the accumulated angle is 400 degrees To 240 degrees.

Subsequently, the scale factor error is calculated by dividing the difference (? H) between the azimuth of the entry point and the azimuth of the entry point by the rotation angle ?? of the gyro sensor (S108) ), The gyro sensor is calibrated by the calcu- lated factor of the kale factor (S116).

If the vehicle has an indoor map (Yes in S102), the angular velocity value of the gyro sensor due to the running of the vehicle from the time when the vehicle enters the turning point (S110) to the time when the turning point advances (S114) (S111). Then, the turning radius at which the turning has occurred in the running locus of the vehicle is calculated, and the turning radius is compared with the critical turning radius. The cumulative rotation angle is compared with the critical angle and the rotation angle [Sigma] [phi] on the indoor map accumulated only when the rotation angle is smaller than the critical rotation radius and the accumulated rotation angle is larger than the critical angle (S112 and S113) And the gyro sensor is calibrated by the calculated scale factor error (S116).

In this case, the entrance of the rotation section and the advancement of the rotation section are determined using the link linearity of the indoor map, and the entry of the rotation section is performed at a point 180 where the previous dynamic characteristic of the indoor map is straight and the interpolation point angle of the link is bent (180 degrees) at which the previous dynamic characteristic of the indoor map is rotated and the interpolation point angle of the link is changed to the straight line based on the vehicle position, Hold) is judged to advance into the rotation section.

Here, the turning radius is divided into the rotation of the spiral rotation section, which is equal to or greater than the pitch threshold of the vehicle, and the rotation of the parking space, which is equal to or less than the pitch threshold value.

This division is divided into a spiral rotation section (uphill or downhill) and a parking section (flat section). The spiral rotation section has a large amount of rotation, so that the scale factor can be accurately calculated. However, It is distinguished because an error may occur because the distance is lengthened.

Here, if the pitch value of the vehicle, which is a body calculated by the values of the acceleration sensor and the gyro sensor, is equal to or greater than the threshold value, it is determined to be the spiral rotation section. If the pitch value is less than the threshold value, , It is determined whether or not the cumulative shedding angle is greater than the critical angle only when the running distance is less than the threshold or when the running time is less than or equal to the threshold time.

FIG. 4 is a detailed flowchart for entering azimuth angle determination according to the present invention, which is a concrete embodiment of 'reference data determination and entry azimuth storage step (S103)' of FIG. As shown in Fig. 4, the reference data is determined differently depending on whether an entry / exit link exists (S117).

If there is an entry / exit link on the outdoor map, the reference data is stored as the entry azimuth of the entry link (S118).

If there is no entry / exit link on the outdoor map, the reference data is stored with the azimuth based on the incoming GNSS data by the GNSS data as the entry azimuth (S120) when the GNSS data is above the threshold reliability (S119) .

Here, although the entering azimuth angle is described, it goes without saying that the entering azimuth angle is also stored in the same manner.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is clearly understood that the same is by way of illustration and example only and is not to be taken by way of limitation, Various changes and modifications will be possible.

Claims (18)

In the inertial sensor calibration method, Accumulating a rotation angle obtained by integrating the angular velocity of the gyro sensor according to the running of the vehicle when the vehicle enters the GNSS shaded area; Calculating a scale factor error by comparing the accumulated angle of rotation of the gyro sensor with a reference angle based on map or GNSS data if the accumulated angle of rotation of the gyro sensor is greater than or equal to a critical angle; And And calibrating the gyro sensor by the calculated scale factor error. The method according to claim 1, Further comprising the step of determining whether the indoor map is held or not and determining reference data to be compared with the rotation angle of the gyro sensor when the vehicle does not have the indoor map and storing the azimuth angle of the shaded area entry point, Wherein the step of calculating the scale factor error comprises: Storing an azimuth angle of the shaded area entry point when the accumulated rotation angle of the gyro sensor is greater than or equal to the critical angle; And  Calculating a difference between an azimuth angle of the entry point and an azimuth angle of the entry point, Wherein the difference between the azimuth angle of the entry point and the azimuth angle of the entry point is the reference angle. 3. The method of claim 2, Wherein the step of calculating the scale factor error comprises: Converting the accumulated rotation angle of the gyro sensor to a 360 degree reference; And Further comprising the step of calculating a scale factor error by dividing the difference between the azimuth of the entry point and the azimuth of the entry point by the rotation angle of the gyro sensor converted to the 360 degree reference. 3. The method of claim 2, Wherein the reference data is an azimuth angle of the entry / exit link when an entry / exit link exists on the outdoor map. 3. The method of claim 2, Wherein the reference data is an azimuth angle based on GNSS data based on the GNSS data when the GNSS data is equal to or more than the threshold reliability. The method according to claim 1, The method according to claim 1, further comprising: determining whether the vehicle has an indoor map; and, when the vehicle has the indoor map, calculating the angular velocity of the gyro sensor Accumulates the rotation angles obtained by integrating the values, And the rotation angle on the indoor map according to the traveling of the vehicle from the entry of the rotation section to the advancement of the rotation section to the reference angle is accumulated. The method according to claim 6, Further comprising calculating a turning radius at which the turning has occurred in the running locus of the vehicle and comparing the turning radius to the critical turning radius, Calculating the scale factor error may include calculating a rotation angle on the indoor map when the rotation radius is less than the critical rotation radius and the rotation angle accumulated is greater than the critical angle, And calculating a scale factor error by dividing the scale factor by a predetermined factor. 8. The method of claim 7, Wherein the turning radius is divided into a rotation of a spiral rotation section that is equal to or greater than a pitch threshold value of the vehicle and a rotation of a parking range that is equal to or less than the pitch threshold value. 9. The method of claim 8, Wherein the gyro sensor determines whether the cumulative rotational angle of the gyro sensor is equal to or greater than the critical angle when the vehicle travels by a parking distance less than or equal to the pitch threshold value and the travel distance or travel time of the vehicle is equal to or less than a threshold value. 9. The method of claim 8, Wherein the entering of the rotation section and the advancement of the rotation section are determined using the link linearity of the indoor map. In the inertial sensor calibration method, Determining whether the vehicle has an indoor map when entering the GNSS shaded area; Determining reference data to be compared with the rotation angle of the gyro sensor and storing an azimuth angle of the shaded area entry point when the vehicle does not have the indoor map; Accumulating rotational angles obtained by integrating angular velocity values of the gyro sensor according to running of the vehicle; Determining whether a rotation angle of the gyro sensor is greater than or equal to a critical angle, and storing an azimuth angle of the shaded region entry point if the angle is greater than a critical angle; Calculating a difference between an azimuth angle of the entry point and an azimuth angle of the entry point; Converting the accumulated rotation angle of the gyro sensor to a 360 degree reference; Calculating a scale factor error by dividing a difference value between the azimuth angle of the entry point and the azimuth angle of the entry point by the rotation angle of the gyro sensor converted to 360 degrees reference; And And calibrating the gyro sensor by the calculated scale factor error. 12. The method of claim 11, Wherein the reference data is an azimuth angle of the entry / exit link when an entry / exit link exists on the outdoor map. 12. The method of claim 11, Wherein the reference data is an azimuth angle based on GNSS data based on the GNSS data when the GNSS data is equal to or more than the threshold reliability. 12. The method of claim 11, The rotational angle obtained by integrating the angular velocity values of the gyro sensor along the travel of the vehicle from the entrance of the rotational section to the advancement of the rotational section and the rotational angles on the indoor map are accumulated when the vehicle has the indoor map Calculating a turning radius at which the turning has occurred in the driving trajectory of the vehicle, comparing the turning radius with a critical turning radius, and comparing the accumulated turning angle with a critical angle; And Calculating a scale factor error by dividing the accumulated rotation angle on the indoor map by the rotation angle of the accumulated gyro sensor when the rotation angle is smaller than the critical rotation radius and the rotation angle accumulated is greater than the critical angle Wherein the inertial sensor calibration method comprises the steps of: 15. The method of claim 14, Wherein the turning radius is divided into a rotation of a spiral rotation section that is equal to or greater than a pitch threshold value of the vehicle and a rotation of a parking range that is equal to or less than the pitch threshold value. 16. The method of claim 15, Wherein the gyro sensor determines whether the cumulative rotational angle of the gyro sensor is equal to or greater than the critical angle when the vehicle travels by a parking distance less than or equal to the pitch threshold value and the travel distance or travel time of the vehicle is equal to or less than a threshold value. 16. The method of claim 15, Wherein the entering of the rotation section and the advancement of the rotation section are determined using the link linearity of the indoor map. In the inertial sensor calibration method, Determining whether the vehicle has an indoor map when entering the GNSS shaded area; The rotational angle obtained by integrating the angular velocity values of the gyro sensor along the travel of the vehicle from the entrance of the rotational section to the advancement of the rotational section and the rotational angles on the indoor map are accumulated when the vehicle has the indoor map Calculating a turning radius at which the turning has occurred in the driving trajectory of the vehicle, comparing the turning radius with a critical turning radius, and comparing the accumulated turning angle with a critical angle; Calculating a scale factor error by dividing the accumulated rotation angle on the indoor map by the rotation angle of the accumulated gyro sensor when the rotation angle is smaller than the critical rotation radius and the rotation angle accumulated is greater than the critical angle; And And calibrating the gyro sensor by the calculated scale factor error.

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