JP6868846B2 - Sensors and methods - Google Patents

Description

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

As a method of knowing the position, behavior, etc. of a person, a method of using a wireless signal has been studied (see, for example, 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 the person. Patent Document 2 discloses a method of grasping the head and limbs of a living body using THz waves. Patent Document 3 discloses a method of estimating the size of an object by a radio wave radar. Patent Document 4 discloses a method of measuring a trajectory of a position of an object by a millimeter-wave radar. Patent Document 5 discloses a method of determining whether or not an object is a human by RCS measurement of a Doppler radar. Patent Document 6 discloses a method of estimating the position and state of a living body by machine learning based on channel information of a plurality of antennas and various sensor information. Patent Document 7 discloses a method of determining a person's lying position or sitting position based on the measurement result of the FMCW radar.

Japanese Unexamined Patent Publication No. 2015-184149 Japanese Unexamined Patent Publication No. 2006-81771 Japanese Unexamined Patent Publication No. 2001-159678 Japanese Unexamined Patent Publication No. 2013-160730 Japanese Unexamined Patent Publication No. 2004-340729 Japanese Unexamined Patent Publication No. 2014-190724 Japanese Unexamined Patent Publication No. 2016-135233

However, further improvement is required to improve the system for estimating the movement of living organisms by using wireless signals.

In order to achieve the above object, the antenna according to one embodiment of the present invention is a sensor, each of which transmits N transmission signals to a predetermined range in which a living body can exist (N is a natural number of 3 or more). A transmitting antenna having the transmitting antenna element of the above, and N receiving signals including a reflected signal in which a part of the N transmitting signals transmitted by the N transmitting antenna elements is reflected by the living body. A receiving antenna having M receiving antenna elements, each of which receives a signal (M is a natural number of 3 or more), a circuit, a vertical position which is a position in the vertical direction in which the living body exists with respect to the sensor, and RCS ( Radar cross-section) A memory that stores information indicating the correspondence between the temporal change of the value and the operation of the living body is provided, and at least three of the N transmitting antenna elements are transmitted antenna elements. Are arranged at different positions in the vertical and horizontal directions, respectively, and at least three of the M receiving antenna elements are arranged at different positions in the vertical direction and the horizontal direction, respectively. Is between each of the N transmitting antenna elements and each of the M receiving antenna elements from each of the N receiving signals received in each of the M receiving antenna elements in a predetermined period. By calculating the first matrix of N × M having each complex transmission function showing the propagation characteristics as a component and extracting the second matrix corresponding to the predetermined frequency range in the first matrix, the respiration and heartbeat of the living body. And the second matrix corresponding to the component affected by the vital activity including at least one of the body movements is extracted, and the second matrix is used to be the three-dimensional position where the living body exists with respect to the sensor. , The three-dimensional position including the vertical position is estimated, and the distance between the living body and the transmitting antenna is determined based on the estimated three-dimensional position, the position of the transmitting antenna, and the position of the receiving antenna. The first distance shown and the second distance indicating the distance between the living body and the receiving antenna were calculated, and the RCS value for the living body was calculated and estimated using the first distance and the second distance. The movement of the living body is estimated using the three-dimensional position, the temporal change of the calculated RCS value, and the information indicating the correspondence relationship stored in the memory.

According to the present invention, by using a wireless signal, it is possible to estimate the movement of a living body in a short time and with high accuracy.

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

(Knowledge that became the basis of the present invention)
The inventors have conducted a detailed study on the prior art for estimating the state of a living body using a wireless signal. As a result, it was found that the method of Patent Document 1 can detect the presence or absence of a person, but has a problem that it is difficult to detect the direction, position, state, movement, etc. of the person.

Further, in the method of Patent Document 2, it is possible to detect the head and limbs of a person and estimate the direction, position, state, etc. of the person, but there is a problem that the cost is high because a terahertz band device is used. all right.

Further, it has been found that the method of Patent Document 3 has a problem that it is possible to estimate the size of an object, but 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 it is possible to estimate the locus of the position of the target living body, but it is difficult to estimate the state of the living body.

Further, it has been found that the method of Patent Document 5 has a problem that it is possible to estimate whether or not the object is a person by RCS, but it is difficult to estimate the state of a living body such as a person.

Further, in Patent Document 6, it was found that there is a problem that machine learning needs to be performed for each 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.

As a result of repeated research on the above problems, the inventors have propagated a reflected signal transmitted from a transmitting antenna including a plurality of antenna elements placed at different positions in the vertical direction and the horizontal direction and reflected by a living body. We have found that it is possible to estimate the direction, position, size, posture, motion, etc. of a living body in a short time and with high accuracy by using the characteristics and the scattering cross section, and have reached the present invention. ..

Furthermore, in order to estimate the position of a living body at rest, the position is estimated mainly based on the respiratory and heartbeat components of the living body, so data of about several seconds is required to estimate the movement of the living body. Therefore, for example, it was found that estimation of a fast-moving motion such as a fall requires estimation using short data of less than 1 second, and the living body is stationary, the living body is moving, or is stationary and moving. It was found that it is necessary to estimate the position and posture of the living body by using different time data lengths for one measurement data in order to estimate the posture of the living body in both cases.

That is, the sensor according to one aspect of the present invention is a sensor and has N transmitting antenna elements (N is a natural number of 3 or more) in which transmission signals are transmitted to a predetermined range in which a living body can exist. Each of the transmitting antenna and the N transmitting signals transmitted by the N transmitting antenna elements receive N receiving signals including a reflected signal reflected by the living body. A receiving antenna having M (M is a natural number of 3 or more), a circuit, a vertical position which is a position in the vertical direction in which the living body exists with respect to the sensor, and an RCS (Radar cross-section) value. A memory that stores information indicating a correspondence relationship between the temporal change of the living body and the operation of the living body is provided, and at least three of the N transmitting antenna elements are in the vertical direction, respectively. And at different positions in the horizontal direction, at least three of the M receiving antenna elements are arranged at different positions in the vertical and horizontal directions, respectively, and the circuit is composed of the M receiving antenna elements. Each complex showing propagation characteristics between each of the N transmitting antenna elements and each of the M receiving antenna elements from each of the N received signals received in each of the receiving antenna elements in a predetermined period. By calculating the first matrix of N × M having the transmission function as a component and extracting the second matrix corresponding to the predetermined frequency range in the first matrix, at least one of the breathing, heartbeat, and body movement of the living body. The second matrix corresponding to the component affected by the vital activity including the antenna is extracted, and the second matrix is used to be the three-dimensional position where the living body exists with respect to the sensor and includes the vertical position. A first distance indicating the distance between the living body and the transmitting antenna based on the estimated three-dimensional position, the position of the transmitting antenna, and the position of the receiving antenna, and , The second distance indicating the distance between the living body and the receiving antenna is calculated, the RCS value with respect to the living body is calculated using the first distance and the second distance, and the estimated three-dimensional position and the above-mentioned three-dimensional position and , The operation of the living body is estimated by using the calculated RCS value with time and the information indicating the correspondence relationship stored in the memory.

Therefore, by using the wireless signal, it is possible to estimate the movement of the living body in a short time and with high accuracy.

In addition, the movement of the living body associated with the information indicating the correspondence relationship includes falling, sitting on a chair, sitting on the floor, standing up from the chair, standing up from the floor, jumping, and changing direction. In the circuit, the living body falls over using the estimated three-dimensional position, the temporal change of the calculated RCS value, and the information indicating the correspondence relationship stored in the memory. , Sitting on a chair, sitting on a floor, standing up from a chair, standing up from the floor, jumping, and turning.

Therefore, the movement of the living body can be estimated in a shorter time.

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

Therefore, the processing load required for estimating the operation of the living body can be reduced.

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

Therefore, it is possible to estimate the movement of the living body with higher accuracy.

Further, the vertical position and the RCS value, which are associated with the movement of the living body in the information indicating the correspondence, are set in advance by the living body in the predetermined range of one of the movements of the living body. When this is done, 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. It is shown by the direction code obtained by the above, and the circuit is a temporal change in the extracted operation period in the estimation of the operation of the living body, and the circuit is obtained from the estimated three-dimensional position. The direction code is calculated by converting the vertical position and the temporal change of the calculated RCS value into a direction vector using a predetermined method, and normalizing the converted direction vector, and the calculated direction code. And the information indicating the correspondence relationship may be used to estimate the movement of the living body.

Therefore, it is possible to estimate the movement of the living body with higher accuracy.

Further, in the second operation period following the first operation period, the circuit may estimate the operation of the living body by using the posture of the living body at the end of the first operation period.

Therefore, the next movement of the living body can be estimated by using the estimated movement of the living body. Therefore, the movement of the living body can be estimated more effectively.

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

Therefore, the horizontal movement of the living body can be estimated in a short time and with high accuracy.

Further, the circuit may further estimate the height of the living body by using the vertical position included in the three-dimensional position when the living body is estimated to be moving in the horizontal direction.

Therefore, the height of the living body can be estimated in a short time and with high accuracy. As a result, for example, if a plurality of organisms that can exist in a predetermined range are known in advance and the heights of the plurality of organisms are different, which of the plurality of organisms exists or is operating. Can be used to identify.

Further, the circuit may further estimate the size of the body of the living body by using the RCS value when it is estimated that the living body is moving in the horizontal direction.

Therefore, the size of the body of the living body can be estimated in a short time and with high accuracy. As a result, for example, if a plurality of organisms that can exist in a predetermined range are known in advance and the body sizes of the plurality of organisms are different, which organism among the plurality of organisms exists will operate. It can be used to identify if it is.

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

Therefore, 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 by such a sensor, or as a method in which processing means constituting the device is used as a step. Can be realized as a program that causes a computer to execute, or can be realized as information, data, or a signal indicating the program. Then, the 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. It should be noted that all of the embodiments described below show a preferred specific example of the present invention. Numerical values, shapes, materials, components, arrangement positions and connection forms of components, steps, order of steps, etc. shown in the following embodiments are examples, and are not intended to limit the present invention. Further, among the components in the following embodiments, the components not described in the independent claims indicating the highest level concept of the present invention will be described as arbitrary components constituting the more preferable form. In the present specification and the drawings, components having substantially the same functional configuration are designated by the same reference numerals, so that duplicate description will be omitted.

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

As shown in FIG. 1, the sensor 10 includes a transmitting antenna 20, a receiving antenna 30, a circuit 40, and a memory 41. The sensor 10 emits microwaves from the transmitting antenna 20 to the living body 50 such as a human, and receives the reflected waves reflected by the living body 50 by the receiving antenna 30. _{Here, let φ T} be the angle formed by the first reference direction, which is a direction on the horizontal plane arbitrarily set with respect to the transmitting antenna 20, and the first living body direction, which is the direction from the transmitting antenna 20 to the living body 50. .. Further, the elevation angle of the living body 50, which is the angle formed by the vertical direction and the first living body direction, is set to θ _T. Further, the elevation angle of the living body 50, which is the angle formed by the second reference direction, which is a direction on the horizontal plane arbitrarily set with respect to the receiving antenna 30, and the second living body direction, which is the direction from the receiving antenna 30 to the living body 50. _Let φ R. Further, the angle formed by the vertical direction and the second living body direction is θ _R. Assuming that the central coordinates of the part where the living body 50 is performing vital activity are (x _b , y _b , z _{b ), the directions (θ T} , θ _R , depending on the positional relationship between the transmitting antenna 20, the receiving antenna 30, and the living body 50) φ _T , φ _R ) and coordinates (x _b , y _b , z _b ) can be converted to each other.

The transmitting antenna 20 has N transmitting 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} ) It has an array antenna composed of the transmitting antenna element 21 of the above. That is, at least three of the N transmitting antenna elements 21 are arranged at different positions in the vertical direction and the horizontal direction. Each of the N transmitting antenna elements 21 transmits a transmission signal to a predetermined range in which a living body can exist. That is, the transmitting antenna 20 transmits N transmission signals to a predetermined range from different N positions. The predetermined range in which 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 transmitting antenna elements 21 emits microwaves as transmission signals to a living body 50 such as a human being. The N transmitting antenna elements 21 may transmit a signal subjected to different modulation processing for each transmitting antenna element 21 as a transmitting signal. Further, each of the N transmitting antenna elements 21 may sequentially switch and transmit a modulated signal or an unmodulated signal. The modulation process may be performed by the transmitting antenna 20. In this way, by setting the transmission signals transmitted from the N transmission antenna elements 21 to different transmission signals for each of the N transmission antenna elements 21, the transmission signal received by the reception antenna 30 is transmitted. The antenna element 21 can be specified. As described above, the transmitting antenna 20 may include a circuit for performing the modulation process.

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} ) It has an array antenna composed of the receiving antenna element 31 of the above. That is, at least three of the M receiving antenna elements 31 are arranged at different positions in the vertical direction and the horizontal direction. Each of the M receiving antenna elements 31 receives N reception signals including a reflection signal which is a signal reflected by the living body 50 among the N transmission signals. The receiving antenna 30 frequency-converts a received signal composed of microwaves and converts it into a low-frequency signal. The receiving antenna 30 outputs the signal obtained by converting it into a low frequency signal to the circuit 40. That is, the receiving antenna 30 may include a circuit for processing the received signal.

The circuit 40 executes various processes for operating the sensor 10. The circuit 40 is composed of, 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, 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 may be 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, for example, information used for various processes for operating the sensor 10.

Next, the 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 according to an 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 an operation estimation unit 450.

The complex transfer function calculation unit 410 calculates the complex transfer function from the received signal converted into the low frequency signal. The complex transfer function represents the 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 an M × N component when the number of transmitting antenna elements is N and the number of receiving antenna elements is M. Hereinafter, this complex matrix will be 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 has N transmission antenna elements 21 and M reception antenna elements from each of the plurality of reception signals received in each of the M reception antenna elements 31 in a predetermined period. 31 A first matrix of N × M is calculated, which is composed of each complex transfer function showing the propagation characteristics with each of them.

The biological component calculation unit 420 separates the complex transfer function matrix component obtained from the received signal passing through the living body 50 and the complex transfer function matrix component obtained from the received signal not passing through the living body 50. The component that has passed through the living body 50 is a component that fluctuates with time due to biological activity. Therefore, the component that has passed through the living body 50 is, for example, 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, assuming that the components other than the living body 50 are stationary. Can be extracted by taking out. Further, the component that has passed through the living body 50 can be extracted, for example, by extracting a component whose difference from the result observed when the living body 50 does not exist in a predetermined range exceeds a predetermined threshold value. In this way, 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 passing through the living body 50. .. That is, the biological component calculation unit 420 extracts the second matrix corresponding to the predetermined frequency range in the first matrix, and thereby, the component affected by the vital activity including at least one of the respiration, heartbeat, and body movement of the living body. The second matrix corresponding to is extracted. The predetermined frequency range is, for example, a frequency derived from vital activity including at least one of the above-mentioned respiration, heartbeat, and body movement of a living body. The predetermined frequency range is, for example, a frequency in the range of 0.1 Hz or more and 3 Hz or less. This makes it possible to extract biological components affected by vital activity of 50 parts of the living body due to the movement of the heart, lungs, diaphragm, and internal organs, or vital activity of hands, feet, and the like. The parts of the living body 50 due to the movement of the heart, lungs, diaphragm, and internal organs are, for example, the epigastrium of a human being.

Here, the biological component is a matrix having an M × N component, and is extracted from the complex transfer function obtained from the received signal observed by the receiving antenna 30 in a predetermined period. Therefore, it is assumed that the biological component has frequency response or time response information. The predetermined period is approximately half the period 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 components. That is, the position estimation processing unit 430 estimates the three-dimensional position where the living body 50 exists with respect to the sensor 10 and includes the vertical position where the living body exists with respect to the sensor 10 by using the second matrix. The position estimation, both angle and departure angle theta _T and the arrival angle theta _R to the receiving antenna 30 from the transmitting antenna 20 is estimated, biological 50 by trigonometry from the departure angle theta _T were estimated and the arrival angle theta _R Estimate the position of.

For position estimation, the first distance between the living body 50 and the transmitting antenna 20 to be observed, or the second distance between the living body 50 and the receiving antenna 30, constitutes the transmitting antenna 20 or the receiving antenna 30. When the antennae are close to each other to the same extent as the opening of the living body 50, the position of the living body 50 may be estimated using what is called a spherical wave mode vector. This is because the departure angle or the arrival angle is different for each of the array antenna elements constituting the transmitting antenna 20 or the receiving antenna 30. In this case, since the departure angle or the arrival angle cannot be defined like 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. The steering vector described later is defined.

The position estimation processing unit 430 estimates the position of the stationary living body 50 from the measurement data obtained by measuring in the first measurement period of, for example, 3 seconds or more, depending on the application, and for example, 1 The position of the living body 50 in operation may be estimated using the measurement data obtained by measuring in the second measurement period shorter than the first measurement period such as seconds and 0.5 seconds. The concept at this time is shown in FIGS. 4A and 4B.

FIG. 4A is a diagram for explaining an example of the position resolution of the sensor measuring in different measurement periods.

As shown in FIG. 4A, for example, the 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 the range is 8 m × 8 m. In the case of space, a plurality of regions when measured in the first measurement period with a resolution of 100 cm square are shown. Further, when the plurality of quadrangular regions formed by the grid 302 indicate a predetermined range in which the entire range of the grid 302 is the measurement range of the sensor 10 and the space is the same as the grid 301 in the range of 8 m × 8 m. Multiple 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. Further, in order to measure each of the plurality of regions separated by the grid 301 in the first measurement period and each of the plurality of regions separated by the grid 302 in the second measurement period. The required second period is a period that overlaps with each other. That is, the process of measuring each of the plurality of regions separated by the grid 301 and the process of measuring each of the plurality of regions separated by the grid 302 are executed by parallel processing.

The process of measuring the living body 50 in different measurement periods may be performed as follows.

FIG. 4B is a diagram for explaining another example of the position resolution of the sensor measuring in different measurement periods.

As shown in FIG. 4B, for example, the 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, 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. Further, the plurality of quadrangular regions formed by the grid 303 are 30 cm in a space of 4 m × 4 m, which is a region in which the entire range of the grid 303 includes the position of the living body 50 detected by the measurement of the plurality of regions by the grid 301. A plurality of regions when measured in the second measurement period with four-sided resolution are shown. Further, the plurality of quadrangular regions formed by the lattice 304 are 10 cm in a space having a range of 2 m × 2 m, in which the entire range of the lattice 304 includes the position of the living body 50 detected by the measurement of the plurality of areas by the lattice 303. A plurality of regions when measured in a third measurement period shorter than the second measurement period with four-sided resolution are 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 order to further improve 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 the 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 living body 50 based on the estimated three-dimensional position, the position of the transmitting antenna 20, and the position of the receiving antenna 30 in order to calculate the scattering cross section. The distance RT indicating the first distance to the antenna 20 and the distance RR indicating the 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. The position of the transmitting antenna 20 and the position of the receiving antenna 30 may be stored in the memory 41 in advance.

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

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

When the operation period extraction unit 451 extracts the operation period using, for example, a height position that is a vertical position or an RCS value, in order to avoid the influence of instantaneous noise, the operation period extraction unit 451 is a time series of the obtained three-dimensional position or RCS value. For the data, for example, a median filter, an FIR filter, an average value, etc. are used to remove the noise component of the height position and the RCS value, and the change section of the height information and the RCS change section after the filtering process are set to the living body. It may be extracted as the operation period of. 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 or a plurality of RCS values obtained in a time series using a predetermined filter. , The operating period may be extracted. FIG. 4 shows, as an example, a state in which the height position and the RCS value are measured using measurement data having a measurement period of about 0.6 seconds, a state after performing a predetermined filter process, and a state of extraction as an operation period. 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 it is not always necessary to provide the operation period extraction unit 451. That is, when performing state estimation 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 is a vertical position (height position) obtained from the estimated three-dimensional position and a calculated RCS value. The temporal change of 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 locus in the time change, the distance ΔP of the locus and the direction θ of the locus Is calculated. The direction code calculation unit 452 is, for example, from the height position H1 at the first timing and the height at the second timing following the first timing from the first coordinates p1 (H1, R1) indicated by the RCS value R1. 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). It is converted into a direction vector by calculating the distance ΔP and the direction θ when the second coordinates p2 (H2, R2) are viewed from the first coordinates p1 (H1, R1). FIG. 6 is a diagram for explaining a 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. 7. For example, the direction code calculation unit 452 specifies the direction code closest to the direction θ among the direction codes shown in 1 to 8. FIG. 7 is a diagram showing an example of a direction code table.

The direction code calculation unit 452 obtains time-series data of the direction code as shown in FIG. 8 by calculating the direction code and the distance ΔP as described above. FIG. 8 is a diagram showing 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-series 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, thereby indicating the correspondence relationship in the information 42. The motion of the living body 50 is estimated by specifying the motion 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 of the living body 50 with respect to the sensor 10 in the vertical direction and the temporal change of the RCS value, and the living body. It is information which shows the correspondence relation with the operation of 50. Further, as shown in FIG. 9, the movements of the living body 50 associated with the information 42 indicating the correspondence relationship include falling, sitting on a chair, sitting on the floor, standing up from the chair, standing up from the floor, and jumping. , And change direction. That is, the motion estimation unit 450 determines the three-dimensional position estimated by the position estimation processing unit 430, 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 performed a fall, sitting on a chair, sitting on the floor, standing up from the chair, standing up from the floor, jumping, or changing direction. To do. The model code is represented as time-series data as shown in FIG.

In the circuit 40, time-series data is obtained by repeatedly performing the processes in the respective units 41 to 450 described above at a plurality of different timings. For example, the circuit 40 is a time series consisting of a plurality of three-dimensional positions in the time series and a plurality of RCS values in the time series by repeating the process at a predetermined sampling cycle as described with reference to FIG. 4A or FIG. 4B. Get the data.

Next, the details of the operating principle of the sensor 10 of the embodiment will be described using a mathematical formula. Here, a method of extracting a biological component using a 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 equation 1.

Here, t represents the observation time, and h _ij, which is the (i, j) th element, represents the channel response from the j-th transmitting antenna element 21 to the i-th receiving antenna element 31.

_{M R} × M T MIMO array _is capable of converting into _{M R M T × 1SIMO (Single} -Input Multiple-Output) MIMO virtual array represented in the configuration. In this case, _{M R} × _M T MIMO channel h (t) is converted into _M R _{M T} × 1 virtual SIMO channel represented by the following formula 2.

Here, {・} ^T represents transpose. Here, the difference time T is used, and the difference channel h _sb (t, T) is defined as the following equation 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 eliminates all reflected waves that do not pass through the living body by the difference calculation. Will be done. Therefore, the complex channel contains only the reflected wave derived from the living body.

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

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

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

Here, U is an eigenvector and Λ is an eigenvalue corresponding to the eigenvector, and it is assumed that the order is shown by the following equation 8.

L is the number of incoming waves, that is, the number of living organisms to be detected. In the following description, it is assumed that the distance to the living body to be detected is relatively short compared to the opening of the array antenna constituting the transmitting antenna 20 or the receiving antenna 30. Therefore, it is assumed that a spherical wave is observed in the array antenna. Even when the distance from the living body to be detected is sufficiently long, the following mathematical formula holds, so that there is no problem in detection. If it is known that the distance is sufficiently large, _{the position of the target may be estimated using the starting angle θ T} and the arrival angle θ _R, which has the advantage of making the calculation relatively simple. The steering vector of the array antenna on the transmitting antenna 20 side is defined by the following equations 9 to 11.

Similarly, the steering vector of the array antenna on the receiving antenna 30 side is also defined by the following equations 12 to 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 the phase lag, and λ indicates the wavelength.

Further, the transmission / reception steering vector is multiplied, and as shown in the following equation 15, the steering vector is defined in consideration of the angle information of both transmission / reception.

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 represented by the following equation 16 using this steering vector.

Here, since this search is performed on the coordinates of space (x, y, z), 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 the frequency response matrix F (ω) obtained by Fourier transforming the observed propagation channel matrix H (t) and vectorizing it, 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 to 20.

In this case, R _R represents a distance to the position of the biometric 50 estimated from the received antenna 30, the R _T shows the distance to the position of the biological 50 estimated from the transmitting antenna 20. 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 biological activity, and ω 2} indicates the maximum frequency of biological activity.

In this way, only the reflected power from the living body can be extracted by extracting only the components corresponding to the frequencies 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, so the RCS fluctuates. By modeling the orbits of the estimated height z of the living body and the scattering cross section σ, it is possible to estimate the movement of the living body.

The method of motion estimation will be described below.

By continuously estimating the scattering cross section σ and height z of the living body at a plurality of different timings by the above-mentioned method, the locus of the σ−z characteristic can be observed. At this time, when the living body is in a resting state, there is almost no change in the RCS value. Let ΔPi be the amount of movement of the locus point, which is the distance between the i-1st locus point and the i-th locus point with respect to this locus point group, and the i-1st locus point and the i-th locus point. The angle formed between them is defined as the angle parameter αi, and is defined as the following equations 21 and 22, respectively.

Next, the direction code is assigned to the moving direction of the locus point using the value of the angle parameter. The direction code is assigned to the angle by dividing 360 ° into eight parts and assigning numbers 1 to 8 in each direction. At this time, in order to prevent the cord from changing frequently when moving in the vertical and horizontal directions, the boundary of the cord may not be provided in that direction. Since there are individual differences in the speed of movement, normalization of the direction code that takes into account the difference in speed of movement in order to avoid misrecognition due to the difference in the number of locus points depending on the speed of movement even for the same movement It may be converted. For example, from the original direction code sequence c _j (j = 1 to j _max ) obtained by direction estimation, a normalized code sequence consisting of K terms is taken into consideration in consideration of the ratio of the locus point movement amount to the total locus point movement amount. To generate. Here, j _max is the number of locus points and varies depending on the operating time. The normalized code sequence C _k (k = 1, 2, ..., K) is created from the i-th locus movement amount ΔPi and the sum total of the locus point movement amounts ΔP _{sum as} follows.

1) In j = 1, the normalized code string in the range of k satisfying the following equation 23 is the code of j = 1 in the original direction code string.

2) In the range where j is 2 to j _max , the normalized code string in the range of k that satisfies the following equation 24 is the code for each j. However, ΔP _sum satisfies the following equation 25.

The motion is estimated by comparing the normalized sequence (test data) consisting of K terms created from the locus point data with the model data sequence consisting of K terms corresponding to each of the plurality of motions. In the model data sequence, the motion is measured multiple times while each of the plurality of motions is performed in advance, and the most directional code in each term of the normalized code sequence obtained by the measurement of the multiple motions is used. Use the model data in that section. Since the direction code is circular, the maximum difference is 4. In order to calculate the difference between the direction code number and the actual difference, the following equation 26 is used. However, when δC _i > 4, the following equation 27 is used.

_{However, C test, i} denotes an element of the _i-th term of the test data _{sequence, C model, i} denotes an element of the i-th term of the model data strings. Next, the sum of squares of the direction code differences between the test data and the model data is calculated as the deviation shown by the following equation 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 showing test data obtained by measurement and model data which is a model code.

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

Next, the operation of the sensor 10 in the embodiment will be described with reference to a flowchart.

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

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

The M receiving antenna elements 31 of the receiving antenna 30 receive the N receiving signals including the plurality of reflected signals reflected by the living body 50 from the N transmitting signals transmitted by the transmitting antenna 20 (S12).

In the circuit 40, from each of the N received signals received in each of the M receiving antenna elements 31 in a predetermined period, between each of the N transmitting antenna elements 21 and each of the M receiving antenna elements 31. The first matrix of N × M is calculated with each complex transfer function showing the propagation characteristics of (S13) as a component (S13).

The circuit 40 extracts a second matrix corresponding to a predetermined frequency range in the first matrix, and thereby corresponds to a component affected by 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 of the living body 50 with respect to the sensor 10 using the second matrix (S15).

The circuit 40 has 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. The distance r2 indicating the 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 by using the calculated RCS value and the information 42 stored in the memory 41 indicating the correspondence between the RCS value and the operation of the living body 50 (S18).

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

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

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

The circuit 40 converts the time change in the extracted operation period, the vertical position obtained from the estimated three-dimensional position, and the time 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 is associated with the time-series data in the information 42 indicating the correspondence by comparing the calculated time-series data of the direction code with the information 42 indicating the correspondence stored in the memory. By specifying the movement, the movement of the living body 50 is estimated (S23).

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

FIG. 13 is a flowchart showing 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 means (not shown) (S31). As a result, the circuit 40 recognizes that the operation performed during the predetermined period is the operation indicated by the received input.

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

According to the sensor 10 according to the present embodiment, it is possible to estimate the position where the living body 50 exists and the movement of the living body at the position in a short time and with high accuracy.

The sensor 10 detects the presence of the living body 50 by detecting a moving part. Therefore, for example, by using this, a human being is alive and falls, sits on a chair, sits on a floor, stands up from a chair, stands up from the floor, jumps, and changes direction. It is possible to estimate which operation of the throat was performed. This makes it possible to effectively confirm the survival of humans. In addition, since it is possible to confirm the survival of a human without analyzing the image captured by the camera, it is possible to confirm the survival of a human while protecting the privacy of the human.

Although the sensor 10 according to one or more aspects of the present invention has been described above based on the embodiment, the present invention is not limited to this embodiment. As long as it does not deviate from the gist of the present invention, one or more of the present embodiments may be modified by those skilled in the art, or may be constructed by combining components in different embodiments. It may be included within the scope of the embodiment.

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

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

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

The circuit 40 of the sensor 10 determines, for example, whether or not the fluctuation in the horizontal direction is a fluctuation of a predetermined distance or more from the time series data of the three-dimensional position of the living body 50, and the fluctuation 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 presume that the living body 50 is running when the horizontal fluctuation is larger than a predetermined threshold value, or presume that the living body 50 is walking when it is smaller than the predetermined threshold value. You may. Therefore, the horizontal movement of the living body 50 can be estimated in a short time and with high accuracy.

Further, the circuit 40 of the sensor 10 may further estimate the height of the living body 50 by using the vertical position included in the three-dimensional position when the living body 50 is estimated to be moving in the horizontal direction. .. In this case, the circuit 40 may specifically 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 can be obtained. Therefore, for example, the height of the living body 50 can be obtained 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 his / her height by multiplying it by a predetermined coefficient as described above on the premise that he / she is in a standing state.

As a result, for example, if a plurality of organisms that can exist in a predetermined range are known in advance and the heights of the plurality of organisms are different, which of the plurality of organisms exists or is operating. Can be used to identify. For example, if a predetermined range is a room in a house and the person who lives in the house is decided, refer to the height size of the person who lives in the house from the obtained vertical position. Therefore, it can be used to identify who the obtained living body 50 is among the people living in the house.

Further, the circuit 40 of the sensor 10 may further estimate the size of the body of the living body 50 by using the RCS value when the living body 50 is estimated to be moving in the horizontal direction. As a result, for example, if a plurality of organisms that can exist in a predetermined range are known in advance and the body sizes of the plurality of organisms are different, which organism among the plurality of organisms exists will operate. It can be used to identify if it is. In other words, it can be used to identify who exists, as in the case of height.

The present invention can be used as a sensor and a method for estimating the direction and position of a moving body using a radio signal. In particular, the direction estimation method and direction mounted on measuring instruments that measure the direction and position of moving objects including living bodies and machines, home appliances that control according to the direction and position of moving objects, and monitoring devices that detect the intrusion of moving objects. It can be used for estimation methods, position estimation methods, and at most estimation devices using scattered cross sections.

10 Sensor 20 Transmitting antenna 21 Transmitting antenna element 30 Receiving antenna 31 Receiving antenna element 40 Circuit 41 Memory 42 Information indicating correspondence 50 Living body 301-304 Grid 410 Complex transfer function calculation unit 420 Biological component calculation unit 430 Position estimation processing unit 440 RCS Calculation unit 450 Operation estimation unit 451 Operation period extraction unit 452 Direction code calculation unit 453 Operation comparison unit

Claims (11)

It ’s a sensor,
A transmitting antenna having N (N is a natural number of 3 or more) transmitting antenna elements, each of which transmits a transmission signal to a predetermined range in which a living body can exist, and a transmitting antenna.
A part of the N transmission signals transmitted by the N transmission antenna elements receives N reception signals including a reflection signal reflected by the living body (M). Is a receiving antenna having a receiving antenna element (3 or more natural numbers) and
Circuit and
A memory that stores information indicating the correspondence between the vertical position, which is the position of the living body in the vertical direction with respect to the sensor, and the temporal change of the RCS (Radar cross-section) value, and the movement of the living body. And with
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 of the M receiving antenna elements are arranged at different positions in the vertical direction and the horizontal direction, respectively.
The circuit
Propagation characteristics between each of the N transmitting antenna elements and each of the M receiving antenna elements from each of the N received signals received in each of the M receiving antenna elements in a predetermined period. Calculate the first matrix of N × M with each complex transfer function indicating
By extracting the second matrix corresponding to the predetermined frequency range in the first matrix, the second matrix corresponding to the component affected by the vital activity including at least one of the respiration, heartbeat and body movement of the living body. Extract and
Using the second matrix, the three-dimensional position where the living body exists with respect to the sensor, including the vertical position, is estimated.
Based on the estimated three-dimensional position, the position of the transmitting antenna, and the position of the receiving antenna, a first distance indicating the distance between the living body and the transmitting antenna, and the living body and the receiving antenna. Calculate the second distance indicating the distance to and
Using the first distance and the second distance, the RCS value for the living body was calculated.
The movement of the living body is estimated by using the estimated three-dimensional position, the temporal change of the calculated RCS value, and the information indicating the correspondence relationship stored in the memory.
sensor. The movements of the living body associated with the information indicating the correspondence include falling, sitting on a chair, sitting on the floor, standing up from the chair, standing up from the floor, jumping, and changing direction.
In the circuit, the living body falls over using the estimated three-dimensional position, the temporal change of the calculated RCS value, and the information indicating the correspondence relationship stored in the memory. The sensor according to claim 1, which estimates whether the movement of sitting on a chair, sitting on the floor, standing up from a chair, standing up from the floor, jumping, or changing direction is performed. The circuit is used in estimating the movement of the living body.
The period in which the estimated vertical position or the time change of the calculated RCS value is larger than the predetermined value is extracted as the operating period in which the living body is operating.
The extracted temporal change in the operation period, 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 estimate the behavior of the living body,
The sensor according to claim 1 or 2. The circuit uses time-series data obtained by removing an instantaneous noise component from a plurality of the vertical positions or a plurality of the RCS values obtained in a time series using a predetermined filter to perform the operation. The sensor according to claim 3, wherein the period is extracted. The vertical position and the RCS value, which are associated with the movement of the living body in the information indicating the correspondence, are obtained by the living body performing one of the movements of the living body in the predetermined range in advance. Occasionally, 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 by using a predetermined method, and the converted direction vector is normalized. Indicated by the direction code obtained in
The circuit is used in estimating the movement of the living body.
The extracted temporal change in the operation period, 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 by using a predetermined method. And
The direction code is calculated by normalizing the converted direction vector.
The sensor according to claim 3 or 4, which estimates the movement of the living body by using the calculated direction code and the information indicating the correspondence relationship. The circuit of claims 1 to 5 estimates the movement of the living body by using the posture of the living body at the end of the first operating period in the second operating period following the first operating period. The sensor according to any one item. The circuit further presumes that the living body is moving in the horizontal direction when the horizontal fluctuation at the estimated three-dimensional position is a fluctuation of a predetermined distance or more. Or the sensor described in item 1. The sensor according to claim 7, wherein the circuit further estimates the height of the living body by using the vertical position included in the three-dimensional position when the living body is estimated to be moving in the horizontal direction. The sensor according to claim 7 or 8, wherein the circuit further estimates the size of the body of the living body by using the RCS value when it is estimated that the living body is moving in the horizontal direction. The sensor according to any one of claims 1 to 9, wherein the predetermined period is approximately half of at least one cycle of respiration, heartbeat, and body movement of the living body. It is a method of estimating the movement of a living body by a sensor.
The sensor is a transmitting antenna having N (N is a natural number of 3 or more) transmitting antenna elements, a receiving antenna having M receiving antenna elements (M is a natural number of 3 or more), a circuit, and the sensor. It is provided with a memory that stores information indicating a vertical position, which is a position in the vertical direction in which a living body exists, an RCS (Radar cross-section) value, and information indicating a correspondence relationship between the movements 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 of the M receiving antenna elements are arranged at different positions in the vertical direction and the horizontal direction, respectively.
The method is
N transmission signals are transmitted using the N transmission antennas in a predetermined range in which a living body can exist.
A part of the transmitted signals of the N transmitted signals received the N received signals including the reflected signal reflected by the living body by using each of the M receiving antenna elements.
Propagation characteristics between each of the N transmitting antenna elements and each of the M receiving antenna elements from each of the N received signals received in each of the M receiving antenna elements in a predetermined period. Calculate the first matrix of N × M with each complex transfer function indicating
By extracting the second matrix corresponding to the predetermined frequency range in the first matrix, the second matrix corresponding to the component affected by the vital activity including at least one of the respiration, heartbeat and body movement of the living body. Extract and
Using the second matrix, the three-dimensional position where the living body exists with respect to the sensor, including the vertical position, is estimated.
Based on the estimated three-dimensional position, the position of the transmitting antenna, and the position of the receiving antenna, a first distance indicating the distance between the living body and the transmitting antenna, and the living body and the receiving antenna. Calculate the second distance indicating the distance to and
Using the first distance and the second distance, the RCS value for the living body was calculated.
The movement of the living body is estimated by using the estimated three-dimensional position, the temporal change of the calculated RCS value, and the information indicating the correspondence relationship stored in the memory.
Method.

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