JP2018112540A - Sensors and methods - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a sensor or the like capable of estimating the operation of a living body in a short time and with high accuracy by using a wireless signal. SOLUTION: The sensor 10 has a transmitting antenna 20 having N transmitting antenna elements 21 for transmitting a transmitting signal, and N receiving signals including a reflected signal reflected by a living body among the N transmitting signals. Each of the receiving antennas 30 having M receiving antenna elements 31 for receiving the above, the circuit 40, and the memory 41, the circuit comprises each transmitting antenna element and each receiving antenna element from each received signal. A second matrix corresponding to a predetermined frequency range is extracted from the N × M first matrix showing the propagation characteristics between antennas, the position where the living body exists is estimated using the second matrix, and the estimated position and transmission and reception are performed. The RCS (Radar cross-section) value for the living body is calculated based on the position of the antenna, and the movement of the living body is estimated using the calculated RCS value and the information indicating the correspondence between the RCS value and the movement of the living body. do. [Selection diagram] Fig. 2

Description

  The present invention relates to a sensor and a method for estimating a behavior of a living body using a radio signal.

  As a method of knowing the position, action, etc. of a person, a method using a radio signal has been studied (for example, see Patent Documents 1 to 7). Specifically, Patent Document 1 discloses a method of monitoring the movement of a person based on the amount of change in received radio waves and determining the presence or absence of a person. Patent Document 2 discloses a method for grasping the head and limbs of a living body using THz waves. Patent Document 3 discloses a method for estimating the size of an object using a radio wave radar. Patent Document 4 discloses a method of measuring the locus of the position of an object using a millimeter wave radar. Patent Document 5 discloses a method for determining whether or not an object is a person by RCS measurement of Doppler radar. Patent Document 6 discloses a method for estimating the position and state of a living body by machine learning based on channel information of various antennas and various sensor information. Patent Document 7 discloses a method of determining a person's supine position or sitting position from the measurement result of the FMCW radar.

Japanese Patent Laying-Open No. 2015-184149 JP 2006-81771 A JP 2001-159678 A JP2013-160730A JP 2004-340729 A JP 2014-190724 A Japanese Patent Laid-Open No. 2006-135233

  However, further improvement is required to improve the system for estimating the movement of a living body by using a radio signal.

  In order to achieve the above object, a sensor according to an aspect of the present invention is a sensor, and each N transmits a transmission signal to a predetermined range in which a living body can exist (N is a natural number of 3 or more). A transmission antenna having a plurality of transmission antenna elements, and N receptions including a reflection signal in which some of the N transmission signals transmitted by the N transmission antenna elements are reflected by the living body. A receiving antenna having M receiving antenna elements each receiving a signal (M is a natural number of 3 or more), a circuit, a vertical position that is a position in the vertical direction where the living body exists with respect to the sensor, and RCS ( A memory storing information indicating a correspondence relationship between a temporal change in a Radar cross-section) value and the movement of the living body, and at least of the N transmitting antenna elements. The three transmitting antenna elements are arranged at different positions in the vertical direction and the horizontal direction, respectively, and at least three receiving antenna elements among the M receiving antenna elements are different in the vertical direction and the horizontal direction, respectively. Arranged in position, the circuit from each of the N received signals received in a predetermined period at each of the M receive antenna elements, and each of the N transmit antenna elements and the M receive signals. By calculating an N × M first matrix having components of complex transfer functions indicating propagation characteristics between the antenna elements and extracting a second matrix corresponding to a predetermined frequency range in the first matrix. Extracting the second matrix corresponding to a component affected by vital activity including at least one of respiration, heartbeat and body movement of the living body, and the second matrix Using the three-dimensional position where the living body is present with respect to the sensor, including the vertical position, and estimating the three-dimensional position, the position of the transmitting antenna, and the position of the receiving antenna. Based on the position, a first distance indicating a distance between the living body and the transmitting antenna and a second distance indicating a distance between the living body and the receiving antenna are calculated, and the first distance and the second distance are calculated. Calculating an RCS value for the living body using a distance, the estimated three-dimensional position, a temporal change of the calculated RCS value, and information indicating the correspondence relationship stored in the memory; Is used to estimate the behavior of the living body.

  According to the present invention, by using a radio signal, it is possible to estimate a biological operation in a short time and with high accuracy.

FIG. 1 is a block diagram illustrating an example of a configuration of a sensor in the embodiment. FIG. 2 is a diagram illustrating an installation example of the sensor in the embodiment. FIG. 3 is a block diagram showing a functional configuration of a circuit and a memory in the embodiment. FIG. 4A is a diagram for describing an example of position resolution of a sensor that is measured in different measurement periods. FIG. 4B is a diagram for describing another example of the position resolution of the sensor that is measured in different measurement periods. FIG. 5 is a diagram for describing an example in which an operation period is extracted from time-series data of a height position (Height) or an RCE value. FIG. 6 is a diagram for explaining the process of converting into a direction vector. FIG. 7 is a diagram illustrating an example of a direction code table. FIG. 8 is a diagram illustrating an example of time-series data of the calculated direction code and distance. FIG. 9 is a diagram illustrating an example of information indicating the correspondence relationship. FIG. 10 is a diagram illustrating test data obtained by measurement and model data which is a model code. FIG. 11 is a flowchart illustrating an example of the operation of the sensor according to the embodiment. FIG. 12 is a flowchart illustrating an example of details of the estimation process. FIG. 13 is a flowchart illustrating an example of the operation of the sensor in the pre-learning process.

(Knowledge that became the basis of the present invention)
The inventors conducted a detailed study on the prior art related to biological state estimation using a radio signal. As a result, it has been found that the method of Patent Document 1 can detect the presence / absence of a person, but it is difficult to detect the direction, position, state, action, etc. of the person.

  In addition, the method of Patent Document 2 can detect the head and limbs of a person and estimate the direction, position, state, etc. of the person, but it uses a terahertz band device and has a problem of high cost. all right.

  Further, it has been found that the method of Patent Document 3 has a problem that although it is possible to estimate the size of an object, it is difficult to estimate the state of a living body such as a person.

  Further, it has been found that the method of Patent Document 4 has a problem that although it is possible to estimate the locus of the position of the target living body, it is difficult to estimate the state of the living body.

  Further, in the method of Patent Document 5, it is possible to estimate whether the object is a person by RCS, but it has been found that there is a problem that it is difficult to estimate the state of a living body such as a person.

  Moreover, in patent document 6, it turned out that there exists a subject that it is necessary to perform machine learning for every user.

  Further, in Patent Document 7, it has been found that there is a problem that it is difficult to estimate the movement of a person.

  The inventors have conducted research on the above problems, and as a result, propagated reflected signals transmitted from a transmitting antenna including a plurality of antenna elements placed at different positions in the vertical and horizontal directions and reflected by a living body. By using the characteristics and the scattering cross section, it was found that the direction, position, size, posture, movement, etc. of the living body can be estimated in a short time and with high accuracy, and the present invention has been achieved. .

  Further, in order to estimate the position of a living body at rest, position estimation is mainly performed based on the respiration and heartbeat components of the living body, and therefore, data of several seconds is required to estimate the movement of the living body. For this reason, for example, it is understood that estimation of fast motion such as a fall requires estimation using short data of less than 1 second, while the living body is stationary, while the living body is moving, or while still and moving It has been found that for the estimation of the posture of the living body in both cases, it is necessary to estimate the position and posture of the living body using different time data lengths for one measurement data.

  That is, the sensor according to one embodiment of the present invention is a sensor, and includes N (N is a natural number of 3 or more) transmission antenna elements each transmitting a transmission signal to a predetermined range in which a living body can exist. Each of the transmission antenna and N reception signals including a reflection signal obtained by reflecting a part of the N transmission signals transmitted from the N transmission antenna elements by the living body is received. A receiving antenna having M receiving antenna elements (M is a natural number of 3 or more), a circuit, a vertical position that is a position in the vertical direction where the living body exists with respect to the sensor, and an RCS (Radar cross-section) value And a memory storing information indicating a correspondence relationship between the temporal change of the living body and the operation of the living body, and at least three transmission antennas of the N transmission antenna elements are included. The tener elements are respectively disposed at different positions in the vertical direction and the horizontal direction, and at least three reception antenna elements among the M reception antenna elements are disposed at different positions in the vertical direction and the horizontal direction, respectively. The circuit includes, from each of the N received signals received in a predetermined period by each of the M receiving antenna elements, each of the N transmitting antenna elements and each of the M receiving antenna elements. By calculating a first matrix of N × M having each complex transfer function indicating a propagation characteristic between them as a component, and extracting a second matrix corresponding to a predetermined frequency range in the first matrix, respiration of the living body , Extracting the second matrix corresponding to the component affected by the vital activity including at least one of heartbeat and body movement, and using the second matrix, the second matrix is extracted. A three-dimensional position where the living body is present with respect to a sir, and a three-dimensional position including the vertical position is estimated, and the estimated three-dimensional position, the position of the transmitting antenna, and the position of the receiving antenna are Based on the first distance indicating the distance between the living body and the transmitting antenna and the second distance indicating the distance between the living body and the receiving antenna, and using the first distance and the second distance. Calculating the RCS value for the living body, using the estimated three-dimensional position, the temporal change of the calculated RCS value, and the information indicating the correspondence stored in the memory, The movement of the living body is estimated.

  For this reason, a biological signal can be estimated in a short time and with high accuracy by using a radio signal.

  Further, the movement of the living body associated in the information indicating the correspondence includes falling, sitting on a chair, sitting on a floor, standing from a chair, standing from the floor, jumping, and turning. The circuit uses the estimated three-dimensional position, the temporal change of the calculated RCS value, and the information indicating the correspondence relationship stored in the memory to cause the living body to fall. It may be estimated whether the sitting on the chair, the sitting on the floor, the standing from the chair, the standing from the floor, the jump, or the direction change is performed.

  For this reason, estimation of the operation | movement of a biological body can be performed in a shorter time.

  Further, in the estimation of the movement of the living body, the circuit sets a period in which the temporal change of the estimated vertical position or the calculated RCS value is larger than a predetermined value as an operation period in which the living body is operating. Extracted and extracted temporal changes in the operation period, the estimated three-dimensional position and the calculated temporal change of the RCS value, and information indicating the correspondence stored in the memory And the movement of the living body may be estimated.

  For this reason, the processing load concerning estimation of the operation | movement of a biological body can be reduced.

  In addition, the circuit uses time-series data obtained by removing instantaneous noise components using a predetermined filter from the plurality of vertical positions obtained in time series or the plurality of RCS values. The operation period may be extracted.

  For this reason, it is possible to estimate the movement of the living body with higher accuracy.

  In addition, the vertical position and the RCS value associated with the movement of the living body in the information indicating the correspondence relationship are determined in advance so that the living body moves one of the movements of the living body within the predetermined range. When performed, the vertical position estimated by the circuit and the temporal change of the RCS value calculated by the circuit are converted into a direction vector using a predetermined method, and the converted direction vector is normalized. The direction code is obtained by performing the estimation of the movement of the living body, and the circuit is a temporal change in the extracted movement period, and is obtained from the estimated three-dimensional position. The vertical position and the temporal change of the calculated RCS value are converted into a direction vector using a predetermined method, and the direction vector is normalized by normalizing the converted direction vector. It calculates, and the direction code calculated, using, and information indicating the correspondence relationship may estimate the operation of the living body.

  For this reason, it is possible to estimate the movement of the living body with higher accuracy.

  The circuit may estimate the movement of the living body using the posture of the living body at the end of the first operation period in the second operation period after the first operation period.

  For this reason, it is possible to estimate the next movement of the living body using the estimated movement of the living body. Therefore, the movement of the living body can be estimated more effectively.

  The circuit may further estimate that the living body is moving in the horizontal direction when the estimated variation in the horizontal direction at the three-dimensional position is a variation of a predetermined distance or more.

  For this reason, the movement of the living body in the horizontal direction can be estimated in a short time and with high accuracy.

  The circuit may further estimate the height of the living body using the vertical position included in the three-dimensional position when the living body is estimated to move in the horizontal direction.

  For this reason, the height of the living body can be estimated with high accuracy in a short time. Thus, for example, if a plurality of living bodies that can exist in a predetermined range are known in advance, and the heights of the plurality of living bodies are different from each other, which living body of the plurality of living bodies exists or is operating. Can be used to identify

  The circuit may further estimate the body size of the living body using the RCS value when the living body is estimated to be moving in the horizontal direction.

  For this reason, the size of the body of a living body can be estimated in a short time and with high accuracy. Thus, for example, if a plurality of living bodies that can exist in a predetermined range are known in advance and the body sizes of the plurality of living bodies are different from each other, which living body of the plurality of living bodies exists is operated. It can be used to identify whether or not

  Further, the predetermined period may be approximately half of at least one cycle of respiration, heartbeat, and body movement of the living body.

  For this reason, it is possible to effectively estimate the movement of the living body.

  The present invention is not only realized as a sensor, but also realized as an integrated circuit provided with processing means provided in such a sensor, or realized as a method using the processing means constituting the apparatus as a step. Can be realized as a program for causing a computer to execute, or as information, data, or a signal indicating the program. These programs, information, data, and signals may be distributed via a recording medium such as a CD-ROM or a communication medium such as the Internet.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. Each of the embodiments described below shows a preferred specific example of the present invention. The numerical values, shapes, materials, constituent elements, arrangement positions and connecting forms of the constituent elements, steps, order of steps, and the like shown in the following embodiments are merely examples, and are not intended to limit the present invention. In addition, among the constituent elements in the following embodiments, constituent elements that are not described in the independent claims indicating the highest concept of the present invention are described as optional constituent elements that constitute a more preferable embodiment. In addition, in this specification and drawing, about the component which has the substantially same function structure, duplication description is abbreviate | omitted by attaching | subjecting the same code | symbol.

(Embodiment)
FIG. 1 is a block diagram illustrating an example of a configuration of a sensor in the embodiment. FIG. 2 is a diagram illustrating an installation example of the sensor in the embodiment.

As shown in FIG. 1, the sensor 10 includes a transmission antenna 20, a reception antenna 30, a circuit 40, and a memory 41. The sensor 10 emits a microwave from the transmitting antenna 20 to a living body 50 such as a human and receives a reflected wave reflected by the living body 50 by the receiving antenna 30. Here, an angle formed by a first reference direction that is a direction on the horizontal plane arbitrarily set with respect to the transmission antenna 20 and a first biological direction that is a direction from the transmission antenna 20 to the living body 50 is defined as φ _T. . Further, the vertical direction, the elevation of the living body 50 is to angle for the first biological direction and theta _T. In addition, the elevation angle of the living body 50 that is an angle formed by a second reference direction that is a direction on the horizontal plane that is arbitrarily set with respect to the receiving antenna 30 and a second living body direction that is the direction from the receiving antenna 30 to the living body 50. It is referred to as φ _R. Further, the vertical direction, the angle between the second living direction and theta _R. Assuming that the center coordinates of the part where the living body 50 is performing vital activity is (x _b , y _b , z _b ), the direction (θ _T , θ _R , φ _T , φ _R ) and coordinates (x _b , y _b , z _b ) can be converted into each other.

The transmission antenna 20 has N transmission antenna elements 21. Transmitting antenna 20, lined _{N x} pieces in the horizontal direction (x-direction), and vertical direction _{N z} number in (z direction) is rectangular arranged side by side, N number _{(N = N x × N z} ) The transmission antenna element 21 has an array antenna. That is, at least three transmission antenna elements 21 out of the N transmission antenna elements 21 are arranged at different positions in the vertical direction and the horizontal direction. Each of the N transmission antenna elements 21 transmits a transmission signal to a predetermined range where a living body can exist. That is, the transmission antenna 20 transmits N transmission signals from different N positions to a predetermined range. The predetermined range where the living body can exist is a detection range in which the sensor 10 detects the presence of the living body.

  Specifically, each of the N transmission antenna elements 21 emits a microwave as a transmission signal to a living body 50 such as a human. The N transmission antenna elements 21 may transmit, as transmission signals, signals that have been subjected to different modulation processing for each transmission antenna element 21. Further, each of the N transmission antenna elements 21 may sequentially switch and transmit a modulated signal or an unmodulated signal. The modulation process may be performed by the transmission antenna 20. In this way, for each of the N transmission antenna elements 21, the transmission signal transmitted from the N transmission antenna elements 21 is set to be a different transmission signal, thereby transmitting the transmission signal received by the reception antenna 30. The antenna element 21 can be specified. Thus, the transmission antenna 20 may include a circuit for performing modulation processing.

The receiving antenna 30 has M receiving antenna elements 31. Receiving antenna 30, lined _{M x} pieces in the horizontal direction (x-direction), and vertical _{M z} number in (z direction) is rectangular arranged side by side, M pieces _{(M = M x × M z} ) The receiving antenna element 31 has an array antenna. That is, at least three receiving antenna elements 31 among the M receiving antenna elements 31 are arranged at different positions in the vertical direction and the horizontal direction. Each of the M reception antenna elements 31 receives N reception signals including a reflection signal that is a signal reflected by the living body 50 among the N transmission signals. The receiving antenna 30 converts the frequency of a reception signal made of microwaves into a low frequency signal. The receiving antenna 30 outputs a signal obtained by converting into a low frequency signal to the circuit 40. That is, the receiving antenna 30 may include a circuit for processing a received signal.

The circuit 40 executes various processes for operating the sensor 10. The circuit 40 includes, for example, a processor that executes a control program and a volatile storage area (main storage device) that is used as a work area used when the control program is executed. The volatile storage area is, for example, a RAM (Random Access Memory). The circuit 40 may be configured by a dedicated circuit for performing various processes for operating the sensor 10. That is, the circuit 40 may be a circuit that performs software processing or a circuit that performs hardware processing.

  The memory 41 is a non-volatile storage area (auxiliary storage device), and is, for example, a ROM (Read Only Memory), a flash memory, an HDD (Hard Disk Drive), or the like. The memory 41 stores information used for various processes for operating the sensor 10, for example.

  Next, a functional configuration of the circuit 40 will be described with reference to FIG.

  FIG. 3 is a block diagram showing a functional configuration of a circuit and a memory in the embodiment.

  The circuit 40 includes a complex transfer function calculation unit 410, a biological component calculation unit 420, a position estimation processing unit 430, an RCS calculation unit 440, and a motion estimation unit 450.

  The complex transfer function calculation unit 410 calculates a complex transfer function from the received signal converted into the low frequency signal. The complex transfer function represents propagation loss and phase rotation between each transmitting antenna element 21 and each receiving antenna element 31. The complex transfer function is a complex matrix having M × N components when the number of transmitting antenna elements is N and the number of receiving antenna elements is M. Hereinafter, this complex matrix is referred to as a complex transfer function matrix. The estimated complex transfer function matrix is output to the biological component calculation unit 420. That is, the complex transfer function calculation unit 410 receives each of the N transmission antenna elements 21 and the M reception antenna elements from the plurality of reception signals received in each of the M reception antenna elements 31 in a predetermined period. A first matrix of N × M is calculated with each complex transfer function indicating the propagation characteristics between each of them as a component.

  The biological component calculation unit 420 separates a complex transfer function matrix component obtained from a received signal that has passed through the living body 50 and a complex transfer function matrix component obtained from a received signal that has not passed through the living body 50. The component passing through the living body 50 is a component that varies with time due to biological activity. Therefore, the component that passed through the living body 50 is a component other than the direct current from the component obtained by Fourier-transforming the component of the complex transfer function matrix in the time direction, for example, when the components other than the living body 50 are stationary. It is possible to extract by taking out. In addition, a component that has passed through the living body 50 can be extracted by, for example, extracting a component whose difference from a result observed when the living body 50 is not in a predetermined range exceeds a predetermined threshold. As described above, the biological component calculation unit 420 calculates the extracted complex transfer function matrix component as a biological component by extracting the complex transfer function matrix component obtained from the received signal including the reflected signal that has passed through the living body 50. . In other words, the biological component calculation unit 420 extracts the second matrix corresponding to the predetermined frequency range in the first matrix, so that the component affected by the vital activity including at least one of respiration, heartbeat, and body movement of the living body. A second matrix corresponding to is extracted. The predetermined frequency range is, for example, a frequency derived from vital activity including at least one of respiration, heartbeat, and body movement of the living body described above. The predetermined frequency range is, for example, a frequency in a range of 0.1 Hz to 3 Hz. As a result, it is possible to extract a biological component affected by vital activity of a part of the living body 50 due to the heart, lungs, diaphragm, or built-in movement, or vital activity such as a hand or a foot. In addition, the part of the living body 50 by the heart, the lungs, the diaphragm, and the built-in movement is, for example, a human pit.

Here, the biological component is a matrix having M × N components, and is extracted from a complex transfer function obtained from a received signal observed at the receiving antenna 30 during a predetermined period. For this reason, the biological component has frequency response or time response information. The predetermined period is a period substantially half of at least one cycle of respiration, heartbeat, and body movement of the living body.

The biological component calculated by the biological component calculation unit 420 is output to the position estimation processing unit 430. The position estimation processing unit 430 estimates the position of the living body using the calculated biological component. That is, the position estimation processing unit 430 uses the second matrix to estimate a three-dimensional position where the living body 50 exists with respect to the sensor 10 and includes a vertical position where the living body exists with respect to the sensor 10. In the position estimation, both the starting angle θ _T from the transmitting antenna 20 and the arrival angle θ _R to the receiving antenna 30 are estimated, and the living body 50 is triangulated from the estimated starting angle θ _T and arrival angle θ _R. Is estimated.

  For position estimation, the first distance between the living body 50 to be observed and the transmission antenna 20 or the second distance between the living body 50 and the reception antenna 30 is an array antenna that constitutes the transmission antenna 20 or the reception antenna 30. In the case where they are close enough to be approximately the same as the opening, the position of the living body 50 may be estimated using a so-called spherical wave mode vector. This is because the departure angle or the arrival angle is different for each array antenna element constituting the transmission antenna 20 or the reception antenna 30. In this case, since the starting angle or the arrival angle cannot be defined as in the case of a plane wave, two-dimensional or three-dimensional coordinates representing the positional relationship between the array antenna element constituting the transmitting antenna 20 or the receiving antenna 30 and the target living body 50 are used. Then, a steering vector described later is defined.

  The position estimation processing unit 430 estimates the position of the stationary living body 50 based on the measurement data obtained by measurement in the first measurement period of, for example, 3 seconds or more according to the use. The position of the living body 50 in operation may be estimated using measurement data obtained by measurement in a second measurement period shorter than the first measurement period such as seconds or 0.5 seconds. The concept at this time is shown in FIGS. 4A and 4B.

  FIG. 4A is a diagram for describing an example of position resolution of a sensor that is measured in different measurement periods.

  As shown in FIG. 4A, for example, a plurality of quadrangular regions formed by the grid 301 indicate a predetermined range in which the entire range of the grid 301 is the measurement range of the sensor 10, and is in a range of 8 m × 8 m, for example. In the case of a space, a plurality of regions when measured in the first measurement period with a resolution of 100 cm square are shown. In addition, a plurality of rectangular areas formed by the grid 302 indicate a predetermined range in which the entire range of the grid 302 is a measurement range of the sensor 10 and is the same 8 m × 8 m range as the grid 301. A plurality of regions when measured in the second measurement period with a resolution of 5 cm square are shown. As described above, the first measurement period is, for example, 3 seconds, and the second measurement period is, for example, 0.5 seconds. In addition, the first period required for measuring each of the plurality of regions divided by the lattice 301 in the first measurement period and the second period for measuring each of the plurality of regions divided by the grating 302 The required second period is a period overlapping each other. That is, the process of measuring each of the plurality of areas partitioned by the grid 301 and the process of measuring each of the plurality of areas partitioned by the grid 302 are executed by parallel processing.

  You may perform the process which measures the biological body 50 in a different measurement period as follows.

  FIG. 4B is a diagram for describing another example of the position resolution of the sensor that is measured in different measurement periods.

  As shown in FIG. 4B, for example, a plurality of square areas formed by the grid 301 indicate a predetermined range in which the entire range of the grid 301 is the measurement range of the sensor 10, as in the description of FIG. 4A. In the case of a space in the range of 8 m × 8 m, a plurality of regions when measured in the first measurement period with a resolution of 100 cm square are shown. In addition, a plurality of quadrangular regions formed by the lattice 303 is 30 cm in a space of 4 m × 4 m, which is a region including the position of the living body 50 in which the entire range of the lattice 303 is detected by measuring the plurality of regions using the lattice 301. A plurality of regions when measured in the second measurement period with four-way resolution are shown. In addition, a plurality of quadrangular regions formed by the lattice 304 is 10 cm in a space of 2 m × 2 m, in which the entire range of the lattice 304 includes a position of the living body 50 detected by measuring the plurality of regions using the lattice 303. A plurality of regions in the case where measurement is performed in a third measurement period shorter than the second measurement period with four-way resolution is shown. The first measurement period is, for example, 3 seconds, the second measurement period is, for example, 1 second, and the third measurement period is, for example, 0.5 seconds. In addition, when improving the detection accuracy of the position of the living body 50 at rest, the first measurement period may be set to a time longer than 3 seconds such as 10 to 20 seconds.

  The RCS calculation unit 440 calculates a scattering cross section (RCS: Radar Cross Section) using the biological component and the estimated position. Specifically, the RCS calculation unit 440 transmits the living body 50 and the transmission based on the estimated three-dimensional position, the position of the transmission antenna 20, and the position of the reception antenna 30 in order to calculate the scattering cross section. A distance RT indicating a first distance from the antenna 20 and a distance RR indicating a second distance between the living body 50 and the receiving antenna 30 are calculated. The RCS calculation unit 440 calculates the propagation distance from the calculated distance RT and the distance RR, and calculates the RCS using the calculated propagation distance and the intensity of the biological component. Note that the position of the transmission antenna 20 and the position of the reception antenna 30 may be stored in the memory 41 in advance.

  The motion estimation unit 450 is stored in advance in the memory 41 and time-series data indicating the three-dimensional position estimated by the position estimation processing unit 430 and the temporal change of the RCS value calculated by the RCS calculation unit 440. The operation of the living body 50 is estimated using the information 42 indicating the correspondence relationship. The motion estimation unit 450 includes a motion period extraction unit 451, a direction code calculation unit 452, and a motion comparison unit 453.

  As shown in FIG. 5, the movement period extraction unit 451 has a predetermined change width of the three-dimensional position of the living body 50 estimated by the position estimation processing unit 430 or the temporal change of the RCS value calculated by the RCS calculation unit 440. A period larger than the value is extracted as an operation period. FIG. 5 is a diagram for describing an example in which an operation period is extracted from time-series data of a height position (Height) or an RCE value.

  For example, when the operation period is extracted using the height position or the RCS value that is the vertical position, the operation period extraction unit 451 avoids the influence of instantaneous noise, so that the time series of the obtained three-dimensional position or the RCS value is obtained. For example, a median filter, an FIR filter, an average value, or the like is used for the data to remove the noise component of the height position and the RCS value. The operation period may be extracted. That is, the operation period extraction unit 451 uses time series data obtained by removing an instantaneous noise component from a plurality of vertical positions obtained in time series or a plurality of RCS values using a predetermined filter. The operation period may be extracted. In FIG. 4, as an example, the height position and the RCS value are measured using measurement data having a measurement period of about 0.6 seconds, a predetermined filter process is performed, and an operation period is extracted. The operation period extraction unit 451 is effective when it is desired to limit the period to be estimated for the purpose of reducing the amount of calculation, but is not necessarily provided. In other words, when state estimation is performed for all sections, it goes without saying that the operation period extraction unit 45 may be omitted and estimation may be performed for all sections.

  The direction code calculation unit 452 is a temporal change in the operation period extracted by the operation period extraction unit 451, and the vertical position (height position) obtained from the estimated three-dimensional position, and the calculated RCS value Is converted into a direction vector using a predetermined method. Specifically, the direction code calculation unit 452 plots the height position and the RCS value two-dimensionally as shown in FIG. 6, and in the trajectory over time, the trajectory distance ΔP and the trajectory direction θ. Is calculated. For example, the direction code calculation unit 452 calculates the height at the second timing next to the first timing from the first coordinate p1 (H1, R1) indicated by the height position H1 and the RCS value R1 at the first timing. In the locus to the second coordinate p2 (H2, R2) indicated by the position H2 and the RCS value R2, between the first coordinate p1 (H1, R1) and the second coordinate p2 (H2, R2) The distance ΔP and the direction θ when the second coordinate p2 (H2, R2) is viewed from the first coordinate p1 (H1, R1) are calculated to convert it into a direction vector. FIG. 6 is a diagram for explaining the process of converting into a direction vector.

  Next, the direction code calculation unit 452 calculates the direction code by normalizing the converted direction vector. Specifically, the direction code calculation unit 452 calculates the direction code by referring to the direction code table shown in FIG. For example, the direction code calculation unit 452 specifies the direction code having the closest direction θ among the direction codes indicated by 1 to 8. FIG. 7 is a diagram illustrating an example of a direction code table.

  The direction code calculation unit 452 calculates the direction code and the distance ΔP as described above to obtain the time code data of the direction code as shown in FIG. FIG. 8 is a diagram illustrating an example of time-series data of the calculated direction code and distance. At this time, the direction code calculation unit 452 may normalize the direction code in order to avoid the influence of individual differences.

  The operation comparison unit 453 compares the time code data of the direction code calculated by the direction code calculation unit 452 with the information 42 indicating the correspondence relationship stored in the memory, so that the information 42 indicating the correspondence relationship The action of the living body 50 is estimated by specifying the action associated with the time series data.

  The information 42 indicating the correspondence relationship stored in the memory 41 includes a plurality of model codes indicating the vertical position and the RCS value with respect to the sensor 10 in the vertical direction where the living body 50 exists, and the living body 50 This is information indicating a correspondence relationship with 50 operations. Further, as shown in FIG. 9, the movement of the living body 50 associated in the information 42 indicating the correspondence relationship includes falling, sitting on the chair, sitting on the floor, standing from the chair, standing from the floor, and jumping. And including turnaround. That is, the motion estimation unit 450 uses the three-dimensional position estimated by the position estimation processing unit 430 and the temporal change of the RCS value calculated by the RCS calculation unit 440 and the correspondence relationship stored in the memory 41 in advance. Using the information 42 shown, it is estimated whether the living body 50 has fallen, seated on the chair, seated on the floor, standing from the chair, standing from the floor, jumping, or turning. To do. The model code is expressed as time series data as shown in FIG.

  In the circuit 40, time series data is obtained by repeatedly performing the processing in each of the units 410 to 450 described above at a plurality of different timings. For example, the circuit 40 repeats the process at a predetermined sampling period as described with reference to FIG. 4A or FIG. 4B, so that the time series includes a plurality of time-series three-dimensional positions and a plurality of time-series RCS values. Get the data.

Next, details of the operation principle of the sensor 10 of the embodiment will be described using mathematical expressions. Here, a method for extracting a biological component using Fourier transform will be described. The process described here is performed by the circuit 40. In indoor environments where L person is present, _{M T} elements to the transmission antenna 20 is measured when using a planar array antenna of _{M R} element to the receiving antenna 30 _{M R} × _{M T} when variation MIMO channel H (t) is It is expressed as the following formula 1.

Here, t represents the observation time, and h _{ij as} the (i, j) element represents the channel response from the jth transmission antenna element 21 to the ith reception antenna element 31.

The M _R × M _T MIMO array can be converted into a MIMO virtual array represented by an M _R M _T × 1 SIMO (Single-Input Multiple-Output) configuration. At this time, the M _R × M _T MIMO channel h (t) is converted into an M _R M _T × 1 virtual SIMO channel expressed by the following Equation 2.

Here, {•} ^T represents transposition. Here, using the difference time T, the difference channel h _sb (t, T) is defined as the following Expression 3.

  The actual complex channel includes reflected waves that do not pass through the living body, such as direct waves and reflected waves derived from fixed objects, but the difference channel matrix erases all reflected waves that do not pass through the living body due to the difference calculation. Is done. For this reason, only the reflected wave derived from a living body is included in the complex channel.

Here, using the difference channel h _sb (t, T), an instantaneous correlation matrix R (t, T) of the difference time T at a certain observation time t is defined as the following Expression 4.

Here, {•} ^H represents a complex conjugate transpose. Although the rank of this instantaneous correlation matrix is 1, it is possible to restore the rank of the correlation matrix by averaging, thereby enabling simultaneous estimation of a plurality of incoming waves.

  Next, a method for estimating a three-dimensional direction of a living body using a correlation matrix obtained from a difference channel matrix will be described. Here, an estimation method based on the MUSIC algorithm will be described. When the previous correlation matrix R is decomposed into eigenvalues, the following equations 5 to 7 can be written.

  Here, U is an eigenvector, Λ is an eigenvalue corresponding to the eigenvector, and is in the order shown in the following equation (8).

L is the number of incoming waves, that is, the number of living bodies to be detected. In the following description, the description will be made on the assumption that the distance from the living body to be detected is relatively close compared to the opening of the array antenna that constitutes the transmitting antenna 20 or the receiving antenna 30. Therefore, it is assumed that a spherical wave is observed with the array antenna. Even if the distance from the living body that is the detection target is sufficiently far away, the following formula is satisfied, and there is no problem in detection. If it is known that the distance is sufficiently far, the position of the target may be estimated using the starting angle θ _T and the arrival angle θ _R, and an advantage is obtained that the calculation is relatively simple. The steering vector of the array antenna on the transmission antenna 20 side is defined as the following equations 9-11.

  Similarly, the steering vector of the array antenna on the receiving antenna 30 side is defined as the following equations 12-14.

_{Here, d mxmy,} d _nxny is the wave source, i.e. represents the distance between the living body and the _{m x m y, n x n} y th array _{element, d mxcmyc,} d _nxcnyc represents the distance between the wave source and the reference element , Θ _nxny , Φ _nxny indicate phase lag, and λ indicates wavelength.

  Furthermore, the steering vector of transmission / reception is multiplied, and a steering vector considering the angle information of both transmission / reception is defined as shown in the following Expression 15.

  When the MUSIC method is applied to this, the direction of the incoming wave is estimated by searching for the maximum value of the evaluation function expressed by the following equation 16 using this steering vector.

  Here, since this search is performed on the coordinates (x, y, z) in space, a three-dimensional search process is performed.

  Furthermore, the scattering cross section (RCS) from the living body is calculated using the position information (x, y) obtained by the search.

Using a frequency response matrix F (ω) obtained by performing Fourier transform on the observed propagation channel matrix H (t) and vectorizing, the received power P _γ (ω) is expressed by the following equation (17).

  At this time, the scattering cross section σ of the living body can be expressed by the following equations 18-20.

At this time, R _R indicates the distance from the receiving antenna 30 to the estimated position of the living body 50, and R _T indicates the distance from the transmitting antenna 20 to the estimated position of the living body 50. Also, _{G R} represents a gain of the receiving antenna 30, _{G T} is received, indicating the gain of the transmission antenna 20. Further, ω ₁ indicates the minimum frequency of life activity, and ω ₂ indicates the maximum frequency of life activity.

  Thus, only the reflected power from the living body can be extracted by extracting only the component corresponding to the frequency corresponding to the biological activity. Since the body surface area seen from the antenna looks different depending on the posture of the living body, it is possible to estimate the state of the living body, and when the living body behaves, the frequency component due to body movement increases and the RCS fluctuates. By modeling the trajectory of the estimated living body height z and scattering cross section σ, it is possible to estimate the motion of the living body.

  Hereinafter, a method of motion estimation will be described.

  When the scattering cross section σ and the height z of the living body are continuously estimated at a plurality of different timings by the above-described method, the locus of the σ-z characteristic can be observed. At this time, when the living body is in a stationary state, there is almost no change in the RCS value. Therefore, when the living body is acting, that is, a flow of trajectory points with large fluctuations in the RCS value is extracted. A trajectory point movement amount which is a distance between the i-1 th trajectory point and the i th trajectory point with respect to this trajectory point group is denoted by ΔPi, and the i−1 th trajectory point and the i th trajectory point The angle formed between them is defined as an angle parameter αi, which is defined as the following Expression 21 and Expression 22, respectively.

Next, a direction code is assigned to the movement direction of the locus point using the value of the angle parameter. The direction code is assigned to the angle by dividing 360 ° into 8 and assigning numbers 1 to 8 to each direction. At this time, a code boundary may not be provided in the direction so that the code does not change frequently when moving in the vertical and horizontal directions. Because the speed of movement varies from person to person, even if the movement is the same, the direction code normalization that takes into account the difference in the speed of movement to avoid misrecognition due to the number of trajectory points differing depending on the speed of movement May also be performed. For example, from the original direction code sequence c _j (j = 1 to j _max ) obtained by the direction estimation, a normalized code sequence composed of K terms is considered in consideration of the ratio of the trajectory point movement amount to the total of the trajectory point movement amounts. Is generated. Here, j _max is the number of trajectory points and varies depending on the operation time. The normalized code string C _k (k = 1, 2,..., K) is created as follows from the i-th trajectory movement amount ΔPi and the total ΔP _sum of the trajectory point movement amounts.

  1) When j = 1, a normalized code string in a range of k that satisfies the following Expression 23 is a code of j = 1 in the original direction code string.

2) When j is in the range of 2 to j _max , the normalized code string in the range of k satisfying the following expression 24 is a code in each j. However, ΔP _sum satisfies the following Expression 25.

The motion estimation is performed by comparing a normalized number sequence (test data) composed of K terms created from the trajectory point data with a model data number sequence composed of K terms corresponding to each of a plurality of motions. In the model data sequence, the number of direction codes in each term of the normalized code sequence obtained by performing the measurement of the operation multiple times while performing each of the plurality of operations in advance and obtained by the measurement of the plurality of operations is The model data for that term. Since the direction code is annular, the maximum difference is 4. In order to calculate the direction code number and the actual difference, the following equation 26 is used. However, when δC _i > 4, the following Expression 27 is established.

Here, C _{test, i} represents the element of the _i-th term of the test data string, and C _{model, i} represents the element of the _i-th term of the model data string. Next, the sum of squares of the direction code difference between the test data and the model data is calculated as a deviation represented by the following Expression 28. For example, as shown in FIG. 10, the deviation is calculated by comparing the test data with the model data. FIG. 10 is a diagram illustrating test data obtained by measurement and model data which is a model code.

  Then, an action corresponding to the model data string having the smallest deviation is output as a recognition result.

  Next, the operation of the sensor 10 in the embodiment will be described using a flowchart.

  FIG. 11 is a flowchart illustrating an example of the operation of the sensor according to the embodiment.

  In the sensor 10, the N transmission antenna elements 21 of the transmission antenna 20 transmit N transmission signals using the N transmission antenna elements 21 to a predetermined range in which the living body 50 can exist (S11).

  The M reception antenna elements 31 of the reception antenna 30 receive N reception signals including a plurality of reflection signals in which N transmission signals transmitted from the transmission antenna 20 are reflected by the living body 50 (S12).

  The circuit 40 is configured to connect each of the N transmission antenna elements 21 and each of the M reception antenna elements 31 from the N reception signals received in each of the M reception antenna elements 31 in a predetermined period. An N × M first matrix having each complex transfer function indicating the propagation characteristic of the component as a component is calculated (S13).

  The circuit 40 extracts the second matrix corresponding to the predetermined frequency range in the first matrix, and thereby the second matrix corresponding to the component affected by the vital activity including at least one of respiration, heartbeat, and body movement of the living body 50. Two matrices are extracted (S14).

  The circuit 40 estimates the three-dimensional position where the living body 50 exists with respect to the sensor 10 using the second matrix (S15).

  The circuit 40 includes a distance r1 indicating the distance between the living body 50 and the transmitting antenna 20 based on the estimated three-dimensional position, the position of the transmitting antenna 20, and the position of the receiving antenna 30, and the living body 50 and the receiving antenna. A distance r2 indicating a distance from 30 is calculated (S16).

  The circuit 40 calculates the RCS value for the living body 50 using the first distance and the second distance (S17).

  The circuit 40 estimates the operation of the living body 50 using the calculated RCS value and the information 42 indicating the correspondence relationship between the RCS value and the operation of the living body 50 stored in the memory 41 (S18).

  Next, details of the estimation process for estimating the operation of the living body 50 will be described.

  FIG. 12 is a flowchart illustrating an example of details of the estimation process.

  The circuit 40 extracts a vertical position of the estimated three-dimensional position or a period in which the temporal change of the calculated RCS value is larger than a predetermined value as an operation period in which the living body 50 is operating (S21).

  The circuit 40 converts the temporal change in the extracted operation period, that is, the vertical position obtained from the estimated three-dimensional position and the temporal change of the calculated RCS value into a direction vector using a predetermined method. The direction code is calculated by normalizing the converted direction vector (S22).

  The circuit 40 compares the time-series data of the calculated direction code with the information 42 indicating the correspondence relationship stored in the memory, thereby associating with the time-series data in the information 42 indicating the correspondence relationship. By specifying the motion, the motion of the living body 50 is estimated (S23).

  Next, the pre-learning operation of the sensor 10 for acquiring the information 42 indicating the correspondence will be described.

  FIG. 13 is a flowchart illustrating an example of the operation of the sensor in the pre-learning process.

  The circuit 40 receives an input for designating a predetermined operation by an input unit (not shown) (S31). Thereby, the circuit 40 recognizes that the operation performed during the predetermined period is an operation indicated by the received input.

  Next, processes similar to those in steps S11 to S17 and steps S21 and S22 of the operation of the sensor 10 described above are sequentially performed.

  Next, the circuit 40 stores, as teacher data, information indicating the correspondence obtained by associating the operation indicated by the input received in step S31 with the time-series data of the calculated direction code in the memory 41 (S32). ).

  According to the sensor 10 according to the present embodiment, the position where the living body 50 exists and the motion of the living body at the position can be estimated in a short time with high accuracy.

  The sensor 10 detects the presence of the living body 50 by detecting a moving part. For this reason, for example, by using this, a human is alive and falls, sits on a chair, sits on the floor, stands from the chair, stands from the floor, jumps, and changes direction. It is possible to estimate which of the actions has been performed. Thereby, human survival confirmation can be performed effectively. In addition, since the existence of a human can be confirmed without analyzing the image captured by the camera, the existence of a human can be confirmed while protecting the privacy of the person.

  Although the sensor 10 according to one or more aspects of the present invention has been described based on the embodiment, the present invention is not limited to this embodiment. Unless it deviates from the gist of the present invention, one or more of the present invention may be applied to various modifications that can be conceived by those skilled in the art, or forms constructed by combining components in different embodiments. It may be included within the scope of the embodiments.

  According to the embodiment described above, the sensor 10 assumes that the information 42 indicating the correspondence relationship is information in which the model code in which the vertical position and the RCS value are direction-coded and the action are associated with each other. Not limited to. For example, as information indicating the correspondence relationship, information in which the vertical position itself and the temporal change itself of the RCS value itself are associated with the motion may be employed. In this case, the motion estimation unit 450 of the circuit 40 may not include the direction code calculation unit 452.

  According to the embodiment, the circuit 40 of the sensor 10 may estimate the next action performed by the living body 50 using the estimated action. That is, the circuit 40 may estimate the operation of the living body 50 using the posture of the living body 50 at the end of the first operation period in the second operation period after the first operation period. For example, when the circuit 40 estimates that the living body 50 has stood up, it is clear that the living body 50 has already been in a standing position, and therefore determines that the living body 50 cannot stand up next. When comparing with the information 42 indicating, the operation that stands up from the operation to be compared with the information 42 indicating the correspondence may be excluded. Thereby, the motion of the living body 50 can be estimated with higher accuracy.

  According to the above embodiment, the sensor 10 estimates the motion of the living body 50 from the data obtained using the wireless signal, but is not limited to estimating the motion.

  For example, the circuit 40 of the sensor 10 determines whether or not the variation in the horizontal direction from the time-series data of the three-dimensional position of the living body 50 is a variation of a predetermined distance or more, and the variation is a predetermined distance or more. In this case, it may be estimated that the living body 50 is moving in the horizontal direction. In this case, the circuit 40 may estimate that the living body 50 is running when the variation in the horizontal direction is larger than the predetermined threshold value, and estimates that the living body 50 is walking when the fluctuation is smaller than the predetermined threshold value. May be. For this reason, the movement of the living body 50 in the horizontal direction can be estimated in a short time and with high accuracy.

  The circuit 40 of the sensor 10 may further estimate the height of the living body 50 using, for example, the vertical position included in the three-dimensional position when it is estimated that the living body 50 is moving in the horizontal direction. . In this case, specifically, the circuit 40 may estimate the height of the living body 50 by multiplying the obtained vertical position by a predetermined coefficient. As described above, as the vertical position of the living body 50, for example, the vertical position of the abdomen is obtained. For example, the height of the living body 50 is increased by multiplying a predetermined coefficient by a coefficient in the range of 1.5 to 2.0. Can be estimated. When moving in the horizontal direction, the person who is the living body 50 estimates the height by multiplying the predetermined coefficient as described above on the assumption that the person is standing.

  Thus, for example, if a plurality of living bodies that can exist in a predetermined range are known in advance, and the heights of the plurality of living bodies are different from each other, which living body of the plurality of living bodies exists or is operating. Can be used to identify For example, if the predetermined range is a room in the house and the person living in the house is determined, refer to the height of the person living in the house from the obtained vertical position. Thus, the obtained living body 50 can be used to identify who is the person living in the house.

  Further, the circuit 40 of the sensor 10 may further estimate the body size of the living body 50 using, for example, an RCS value when it is estimated that the living body 50 is moving in the horizontal direction. Thus, for example, if a plurality of living bodies that can exist in a predetermined range are known in advance and the body sizes of the plurality of living bodies are different from each other, which living body of the plurality of living bodies exists is operated. It can be used to identify whether or not That is, as in the case of height, it can be used to specify who is present.

  INDUSTRIAL APPLICABILITY The present invention can be used for a sensor and a method for estimating the direction and position of a moving object using radio signals. In particular, a measuring device that measures the direction and position of a moving object including a living body and a machine, a home appliance that performs control according to the direction and position of the moving object, a direction estimation method that is mounted on a monitoring device that detects the intrusion of a moving object, and the direction This method can be used for an estimation method, a position estimation method, and an at most estimation device using a scattering cross section.

DESCRIPTION OF SYMBOLS 10 Sensor 20 Transmission antenna 21 Transmission antenna element 30 Reception antenna 31 Reception antenna element 40 Circuit 41 Memory 42 Information which shows correspondence 50 Living body 301-304 Grid 410 Complex transfer function calculation part 420 Biological component calculation part 430 Position estimation process part 440 RCS Calculation unit 450 Motion estimation unit 451 Motion period extraction unit 452 Direction code calculation unit 453 Motion comparison unit

Claims (11)

A sensor,
A transmission antenna having N (N is a natural number of 3 or more) transmission antenna elements each transmitting a transmission signal to a predetermined range in which a living body can exist;
M (M) each of which receives N reception signals including a reflection signal in which some of the N transmission signals transmitted by the N transmission antenna elements are reflected by the living body. Is a receiving antenna having a receiving antenna element of a natural number of 3 or more,
Circuit,
Memory that stores information indicating the correspondence between the vertical position, which is the position in the vertical direction where the living body exists with respect to the sensor, and the temporal change of the RCS (Radar cross-section) value, and the movement of the living body. And comprising
Of the N transmitting antenna elements, at least three transmitting antenna elements are arranged at different positions in the vertical direction and the horizontal direction, respectively.
At least three receiving antenna elements among the M receiving antenna elements are arranged at different positions in the vertical direction and the horizontal direction, respectively.
The circuit is
Propagation characteristics between each of the N transmission antenna elements and each of the M reception antenna elements from each of the N reception signals received in a predetermined period by each of the M reception antenna elements. N × M first matrix having each complex transfer function as a component is calculated,
By extracting a second matrix corresponding to a predetermined frequency range in the first matrix, the second matrix corresponding to a component affected by vital activity including at least one of respiration, heartbeat and body movement of the living body. Extract
Using the second matrix, estimating a three-dimensional position of the living body with respect to the sensor, including the vertical position;
Based on the estimated three-dimensional position, the position of the transmitting antenna, and the position of the receiving antenna, a first distance indicating a distance between the living body and the transmitting antenna, and the living body and the receiving antenna A second distance indicating the distance between and
RCS value for the living body is calculated using the first distance and the second distance,
Using the estimated three-dimensional position, the temporal change of the calculated RCS value, and the information indicating the correspondence stored in the memory, to estimate the movement of the living body,
sensor. The movement of the living body associated in the information indicating the correspondence includes falling, sitting on a chair, sitting on the floor, standing from the chair, standing from the floor, jumping, and turning.
The circuit uses the estimated three-dimensional position, the temporal change of the calculated RCS value, and the information indicating the correspondence stored in the memory, so that the living body falls. The sensor according to claim 1, wherein it is estimated whether a sitting on a chair, sitting on a floor, standing from a chair, standing from a floor, jumping, or turning is performed. In the estimation of the operation of the living body, the circuit
Extracting the estimated vertical position or a period in which the temporal change of the calculated RCS value is larger than a predetermined value as an operation period in which the living body is operating;
A temporal change in the extracted operation period, the estimated three-dimensional position, a temporal change of the calculated RCS value, and information indicating the correspondence relationship stored in the memory; Using to estimate the behavior of the living body,
The sensor according to claim 1 or 2. The circuit uses the time series data obtained by removing an instantaneous noise component from a plurality of the vertical positions obtained in time series or a plurality of the RCS values by using a predetermined filter. The sensor according to claim 3 which extracts a period. The vertical position and the RCS value associated with the movement of the living body in the information indicating the correspondence relationship are determined in advance so that the living body performs one of the movements of the living body within the predetermined range. Sometimes, the vertical position estimated by the circuit and the temporal change of the RCS value calculated by the circuit are converted into a direction vector using a predetermined method, and the converted direction vector is normalized. Is indicated by the direction code obtained in
In the estimation of the operation of the living body, the circuit
The extracted temporal change in the operation period, and the vertical position obtained from the estimated three-dimensional position and the temporal change of the calculated RCS value are converted into a direction vector using a predetermined method. And
A direction code is calculated by normalizing the converted direction vector,
The sensor according to claim 3 or 4, wherein the motion of the living body is estimated using the calculated direction code and information indicating the correspondence relationship. 6. The circuit according to claim 1, wherein the circuit estimates the movement of the living body using the posture of the living body at the end of the first movement period in the second movement period next to the first movement period. The sensor according to any one of the above. The circuit further estimates that the living body is moving in the horizontal direction when the estimated variation in the horizontal direction at the three-dimensional position is a variation of a predetermined distance or more. The sensor according to claim 1. The sensor according to claim 7, wherein the circuit further estimates the height of the living body using the vertical position included in the three-dimensional position when it is estimated that the living body is moving in a horizontal direction. The sensor according to claim 7 or 8, wherein the circuit further estimates the body size of the living body using the RCS value when the living body is estimated to move in a horizontal direction. The sensor according to any one of claims 1 to 9, wherein the predetermined period is substantially half of at least one cycle of respiration, heartbeat, and body movement of the living body. A method for estimating the movement of a living body using a sensor,
The sensor includes a transmission antenna having N (N is a natural number of 3 or more) transmission antenna elements, a reception antenna having M (M is a natural number of 3 or more) reception antenna elements, a circuit, and the sensor. A vertical position that is a position in a vertical direction where a living body exists, an RCS (Radar cross-section) value, and a memory that stores information indicating a correspondence relationship of the movement of the living body,
Of the N transmitting antenna elements, at least three transmitting antenna elements are arranged at different positions in the vertical direction and the horizontal direction, respectively.
At least three receiving antenna elements among the M receiving antenna elements are arranged at different positions in the vertical direction and the horizontal direction, respectively.
The method
N transmission signals are transmitted using the N transmission antennas to a predetermined range in which a living body can exist,
Receiving N reception signals including a reflection signal in which a part of transmission signals of the transmitted N transmission signals are reflected by the living body using each of the M reception antenna elements,
Propagation characteristics between each of the N transmission antenna elements and each of the M reception antenna elements from each of the N reception signals received in a predetermined period by each of the M reception antenna elements. N × M first matrix having each complex transfer function as a component is calculated,
By extracting a second matrix corresponding to a predetermined frequency range in the first matrix, the second matrix corresponding to a component affected by vital activity including at least one of respiration, heartbeat and body movement of the living body. Extract
Using the second matrix, estimating a three-dimensional position of the living body with respect to the sensor, including the vertical position;
Based on the estimated three-dimensional position, the position of the transmitting antenna, and the position of the receiving antenna, a first distance indicating a distance between the living body and the transmitting antenna, and the living body and the receiving antenna A second distance indicating the distance between and
RCS value for the living body is calculated using the first distance and the second distance,
Using the estimated three-dimensional position, the temporal change of the calculated RCS value, and the information indicating the correspondence stored in the memory, to estimate the movement of the living body,
Method.

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