JP6751923B2 - program - Google Patents

Description

The present invention relates to a program for executing an estimation method for estimating the direction and position of a moving body using a radio signal.

As a method of knowing the position of a person or the like, a method of using a wireless signal has been studied (see, for example, Patent Documents 1 to 3). Patent Document 1 discloses a method for detecting a living body using a Doppler sensor, and Patent Document 2 discloses a method for detecting human movements and biological information using a Doppler sensor and a filter. Patent Document 3 discloses that the position and state of a person to be detected can be known by analyzing a component including a Doppler shift using a Fourier transform.

Special Table 2014-512526 Gazette International Publication No. 2014/141319 Japanese Unexamined Patent Publication No. 2015-117772 Japanese Unexamined Patent Publication No. 2015-072173 Japanese Unexamined Patent Publication No. 2015-119770 International Publication No. 2012/125100 Japanese Unexamined Patent Publication No. 2014-215200 Japanese Unexamined Patent Publication No. 2015-117961 International Publication No. 2012/115220

F. Adib, Z. Kabelac, D. Katabi, and R. Miller, “3D trackingvia body radio reflections”, 11th USENIX Symp. Net. Systems Design \ & Impl. (USENIX NSDI’14), Apr. 2014. Dai Sasakawa, Keita Konno, Naoki Honma, Kentaro Nishimori, Nobuyasu Takemura, Tsutomu Mitsui, “Fast Simulation Algorithm for Living Body Radar,” 2014 International Symposium on Antennas and Propagation (ISAP 2014), FR3D, pp.583-584, Dec. 2014

However, in the methods of Patent Documents 1 and 2, there is a problem that the presence or absence of a person can be detected, but the direction or position where the person exists cannot be detected.

Further, the method of Patent Document 3 has a problem that it is difficult to detect the direction in which a living body such as a person exists and the position where the living body exists in a short time and with high accuracy. This is because the frequency change due to the Doppler effect derived from biological activity is extremely small, and in order to observe this frequency change by Fourier transform, it is essential to observe for a long time (for example, several tens of seconds) while the living body is stationary. Also, in general, the living body does not maintain the same posture or position for several tens of seconds.

The present invention has been made in view of the above circumstances, and is a program or the like for executing an estimation method capable of estimating the direction in which a moving object exists by using a wireless signal in a short time and with high accuracy. The purpose is to provide.

In order to achieve the above object, the program according to one embodiment of the present invention is a received signal received by each of the N receiving antenna elements, transmitted from one transmitting antenna element, and is a moving object. Among the received signals including the reflected signal reflected by the above, the received signals observed for the first period corresponding to the period derived from the activity of the moving object are acquired, and the plurality of received signals observed in the first period are obtained. From the above, a plurality of complex transmission functions representing the propagation characteristics between the transmitting antenna element and each of the N receiving antenna elements are calculated, and (i) the calculated complex transmitting functions are combined with the plurality of received signals. Is sequentially recorded in a time series in the order of observation, and (ii) difference information indicating the difference between two complex transfer functions at two time points at predetermined intervals among the plurality of complex transfer functions, and is an N-dimensional vector. A process of calculating two or more difference information represented by the above, and using the two or more calculated difference information, estimating the direction in which the moving object exists with the device having at least N receiving antenna elements as a reference of the direction. To execute.

Further, in order to achieve the above object, the estimation device according to one embodiment of the present invention is an estimation device that estimates the position where a moving object exists, from M (M is a natural number of 2 or more) transmitting antenna elements. A receiving antenna unit consisting of a transmitting antenna unit, N receiving antenna elements (N is a natural number of 2 or more), and a receiving signal received by each of the N receiving antenna elements, which is the M. A receiving unit that observes a received signal including a reflected signal transmitted from each of the transmitting antenna elements and reflected by the moving body for a first period corresponding to a period derived from the activity of the moving body, and a receiving unit that observes the received signal during the first period. A complex transmission function calculation unit that calculates a plurality of complex transmission functions representing propagation characteristics between each of the M transmitting antenna elements and each of the N receiving antenna elements from the plurality of received signals, and ( i) The calculated multiple complex transfer functions
It is difference information that sequentially records the plurality of received signals in a time series in the order in which they are observed, and (ii) indicates the difference between the two complex transfer functions at two time points at predetermined intervals among the plurality of complex transfer functions. A difference information calculation unit that calculates two or more difference information represented by an M × N-dimensional matrix, and a position estimation processing unit that estimates the position where the moving object exists using the two or more difference information. Be prepared.

According to the present invention, it is possible to estimate the direction in which a moving object exists by using a wireless signal in a short time and with high accuracy.

FIG. 1 is a block diagram showing an example of the configuration of the estimation device according to the first embodiment. FIG. 2 is a diagram showing an example of a detection target of the estimation device shown in FIG. FIG. 3 is a diagram conceptually showing a state of signal wave transmission in the antenna portion shown in FIG. FIG. 4 is a conceptual diagram showing an example of two time points of a predetermined interval used when calculating the difference information in the first embodiment. FIG. 5 is a conceptual diagram showing an example of two time points at predetermined intervals different from those in FIG. FIG. 6 is a flowchart showing an estimation process of the estimation device according to the first embodiment. FIG. 7 is a block diagram showing an example of the configuration of the estimation device according to the second embodiment. FIG. 8 is a diagram showing an example of a detection target of the estimation device shown in FIG. 7. FIG. 9 is a flowchart showing an estimation process of the estimation device according to the second embodiment. FIG. 10 is a diagram showing the concept of an experiment using the estimation method according to the second embodiment. FIG. 11 is a diagram showing experimental results using the estimation method according to the second embodiment. FIG. 12 is a diagram showing another experimental result using the estimation method according to the second embodiment.

(Knowledge that became the basis of the present invention)
As a method of knowing the position of a person, a method of using a wireless signal is being studied.

For example, Patent Document 1 discloses a method for detecting a living body using a Doppler sensor, and Patent Document 2 discloses a method for detecting human movements and biological information using a Doppler sensor and a filter.

Further, for example, Patent Document 3 discloses that a radio signal is transmitted to a predetermined region, the radio signal reflected by a detection target is received by a plurality of antennas, and a complex transfer function between the transmitting and receiving antennas is estimated. There is. The complex transfer function is a complex number function that represents the relationship between input and output, and here it represents the propagation characteristics between the transmitting and receiving antennas. The number of elements of this complex transfer function is equal to the product of the number of transmitting antennas and the number of receiving antennas.

Patent Document 3 further discloses that the position and state of a person to be detected can be known by analyzing a component including a Doppler shift using a Fourier transform. More specifically, the time change of the element of the complex transfer function is recorded, and the time waveform is Fourier transformed. Living organisms such as humans have a slight Doppler effect on reflected waves due to biological activities such as respiration and heartbeat. Therefore, the components containing the Doppler shift include the influence of the person. On the other hand, the component without Doppler shift is not influenced by the person, that is, it corresponds to the reflected wave from the fixed object and the direct wave between the transmitting and receiving antennas. From the above, Patent Document 3 discloses that the position and state of a person to be detected can be known by analyzing a component containing Doppler shift.

Similarly, for example, in Patent Documents 4 to 9, the Doppler component derived from a person (living body) is extracted by Fourier transforming the observed signal. Then, it is disclosed that the position of the living body and the state such as the heartbeat and respiration of the living body are sensed by analyzing this.

Further, for example, Non-Patent Document 1 discloses a method of detecting the human body direction and position without performing a Fourier transform. In Non-Patent Document 1, the propagation response of the unmanned state is measured in advance, and the position of the person is estimated by analyzing the difference component assuming that the difference between the unmanned state and the manned state is caused by the person. More specifically, in the position estimation method disclosed in Non-Patent Document 1, different locations are obtained by observing a frequency response in a wide band of 1 GHz or more and calculating the propagation time of the extracted reflected wave derived from a person. Estimate the distances from multiple antennas placed in, and estimate the position of the person using the estimated distances. In Non-Patent Document 1, the time response of the complex propagation channels when manned is observed, and the reflection components from the fixed objects such as walls and fixtures are removed by subtracting the complex propagation channels at different times. Extract only the reflected wave.

Further, for example, Non-Patent Document 2 and Patent Document 6 disclose a method of estimating the direction of a living body by removing an unnecessary component from a manned complex transfer function. More specifically, in order to remove the reflected wave from the fixed object and the direct wave between the transmitting and receiving antennas from the complex transfer function, the unmanned complex transfer function is measured in advance. Since the manned complex transfer function includes the reflected wave from a fixed object and the direct wave between the transmitting and receiving antennas, unnecessary components are removed by subtracting the unmanned complex transfer function from the manned complex transfer function. To do.

However, with the methods of Patent Documents 1 and 2 described above, the presence or absence of a person can be detected, but the direction or position where the person exists cannot be detected.

Further, in the method of Patent Document 3 described above, an observation time of several tens of seconds is required to perform the Fourier transform. Therefore, it is difficult to detect the direction and position of a person in a short time and with high accuracy. This is because the frequency change due to the Doppler effect derived from biological activity is extremely small, and in order to observe this frequency change by Fourier transform, it is essential to observe for a long time (for example, several tens of seconds) while the living body is stationary. In general, living organisms do not continue to have the same posture and position for several tens of seconds, so if the observation time is shortened, it will not be possible to correctly extract signals derived from living organisms by Fourier transform, and the estimation accuracy of the direction and position of a person will be improved. descend.

This problem, that is, the problem of Patent Document 3 described above can also occur in the inventions shown in Patent Documents 4 to 9.

Further, the methods of Patent Document 6 and Non-Patent Documents 1 and 2 have a problem that it is necessary to measure the unmanned complex transfer function in advance. This is because if the propagation environment itself changes, such as when furniture or other furniture moves, the position of the person cannot be estimated. Considering the application to the environment in which a person lives, it is assumed that chairs, desks, etc. move frequently. Therefore, the methods of Patent Document 6 and Non-Patent Documents 1 and 2 described above are applied to the living environment of a person. That is difficult.

As described above, in the prior art, there is a problem that it is not possible to estimate the direction in which a moving object exists by using a wireless signal in a short time and with high accuracy.

In recent years, radar has been studied to estimate the direction of existence of a living body in a radio wave propagation environment in which multiple waves exist, utilizing the feature that the living body causes Doppler shift in radio waves due to some biological activity such as respiration and heartbeat. Has been done. That is, a radar that estimates the living body direction by irradiating the living body with radio waves, removing signal components that do not pass through the living body by Fourier transform of the received signal, and estimating the arrival direction of the radio waves reflected from the living body is being studied.

However, as described above, it is not possible to estimate the biological direction in a short time and with high accuracy by using the Fourier transform.

Therefore, in view of this, the inventors have come up with an estimation device or the like that can estimate the direction in which a moving object exists by using a wireless signal in a short time and with high accuracy.

That is, the estimation device according to one aspect of the present invention is an estimation device that estimates the direction in which a moving object exists, and includes one transmitting antenna element and N (N is a natural number of 2 or more) receiving antenna elements. The received signal received by each of the antenna unit and the N receiving antenna elements, including the reflected signal transmitted from the transmitting antenna element and reflected by the moving body, is derived from the activity of the moving body. Propagation characteristics between the transmitting antenna element and each of the N receiving antenna elements from the receiving unit observed for the first period corresponding to the period and the plurality of received signals observed in the first period. The complex transfer function calculation unit that calculates a plurality of complex transfer functions representing the above, and (i) the calculated complex transfer functions are sequentially recorded in a time series in the order in which the plurality of received signals are observed, and (ii). ) A difference information calculation unit that calculates two or more difference information represented by an N-dimensional vector, which is difference information indicating the difference between two complex transfer functions at two time points at a predetermined interval among the plurality of complex transfer functions. A direction estimation processing unit that estimates the direction in which the moving object exists by using the estimation device as a reference of the direction by using the difference information calculated in two or more.

With this configuration, it is possible to estimate the direction in which the moving body exists with high accuracy by a short observation time corresponding to the period derived from the activity of the moving body. As a result, it is possible to estimate the direction in which the moving object exists by using the radio signal in a short time and with high accuracy.

Here, for example, the start points of the two time points of the predetermined interval in each of the two or more difference information are different times.

As a result, the influence of momentary noise can be weakened by acquiring the average of two or more difference information, so that the accuracy of direction estimation can be further improved.

Further, for example, the moving body may be a living body.

Further, for example, the cycle is a cycle derived from a living body including at least one of respiration, heartbeat, and body movement of the living body, and the predetermined interval may be substantially half of the cycle derived from the living body.

This makes it possible to estimate the direction in which the living body exists from the observation in the first period corresponding to at least one cycle of respiration, heartbeat, and body movement.

Further, for example, the direction estimation processing unit calculates and calculates an instantaneous correlation matrix, which is a correlation matrix of the difference time at two time points of the predetermined interval in the difference information, from each of the two or more calculated difference information. Using the instantaneous correlation matrix, the arrival direction of the reflected signal may be estimated by a predetermined arrival direction estimation method, and the direction in which the moving object exists may be estimated based on the estimated arrival direction of the reflected signal. ..

Here, for example, the predetermined arrival direction estimation method is an estimation method based on the MUSIC (MUltiple SIgnal Classification) algorithm.

Further, the estimation device according to one aspect of the present invention is an estimation device that estimates the position where a moving object exists, and includes an transmission antenna unit composed of M transmission antenna elements (M is a natural number of 2 or more) and N units. The received signal received by each of the receiving antenna unit (N is a natural number of 2 or more) and the N receiving antenna elements, and is transmitted from each of the M transmitting antenna elements. From the receiving unit that observes the received signal including the reflected signal reflected by the moving object for the first period corresponding to the period derived from the activity of the moving object, and the plurality of received signals observed in the first period. A complex transmission function calculation unit that calculates a plurality of complex transmission functions representing propagation characteristics between each of the M transmitting antenna elements and each of the N receiving antenna elements, and (i) the plurality of calculated complex transmission functions. The complex transfer functions are sequentially recorded in a time series in the order in which the plurality of received signals are observed, and (ii) the difference between the two complex transfer functions at two time points at predetermined intervals among the plurality of complex transfer functions is recorded. Position estimation that estimates the position where the moving object exists by using the difference information calculation unit that calculates two or more difference information represented by the M × N dimension matrix and the two or more difference information. It is provided with a processing unit.

With this configuration, it is possible to estimate the position where the moving body exists with high accuracy by the short observation time corresponding to the period derived from the activity of the moving body. As a result, it is possible to estimate the position where the moving object exists by using the wireless signal in a short time and with high accuracy.

Here, for example, the start points of the two time points of the predetermined interval in each of the two or more difference information are different times.

As a result, the influence of momentary noise can be weakened by acquiring the average of two or more difference information, so that the accuracy of position estimation can be further improved.

Further, for example, the moving body may be a living body.

Further, for example, the cycle is a cycle derived from a living body including at least one of respiration, heartbeat, and body movement of the living body, and the predetermined interval may be substantially half of the cycle derived from the living body.

As a result, the average of two or more difference information can be obtained, so that the accuracy of position estimation can be further improved by weakening the influence of momentary noise.

Further, for example, the position estimation processing unit calculates and calculates an instantaneous correlation matrix, which is a correlation matrix of the difference time at two time points of a predetermined interval in the difference information, from each of the two or more calculated difference information. Using the instantaneous correlation matrix, the transmission direction of the transmission signal transmitted from the transmission antenna unit to the moving object and the arrival direction of the reflected signal are estimated by a predetermined arrival direction estimation method, and the transmission signal is described. The position where the moving object exists may be estimated based on the transmission direction and the arrival direction of the reflected signal.

Here, for example, the predetermined arrival direction estimation method is an estimation method based on the MUSIC algorithm.

It should be noted that the present invention is not only realized as an apparatus, but also realized as an integrated circuit including processing means provided in such an apparatus, or as a method in which the processing means constituting the apparatus 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. In addition, all the embodiments described below show a preferable 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 1)
In the following, with reference to the drawings, the estimation device 10 in the first embodiment uses the difference information of the complex transfer function observed at two different time points in a predetermined period, and the direction of the moving body (living body) to be detected. Will be described.

[Configuration of estimation device 10]
FIG. 1 is a block diagram showing an example of the configuration of the estimation device 10 according to the first embodiment. FIG. 2 is a diagram showing an example of a detection target of the estimation device 10 shown in FIG.

The estimation device 10 shown in FIG. 1 includes an antenna unit 11, a transmitter 12, a reception unit 13, a complex transfer function calculation unit 14, a difference information calculation unit 15, and a direction estimation processing unit 16. Estimate the direction in which it exists.

[Transmitter 12]
The transmitter 12 generates a high frequency signal used to estimate the direction of the living body 50. For example, as shown in FIG. 2, the transmitter 12 transmits the generated signal (transmitted wave) from one transmitting antenna element included in the antenna unit 11.

[Antenna unit 11]
The antenna unit 11 includes one transmitting antenna element and N receiving antenna elements (N is a natural number of 2 or more). In this embodiment, the antenna unit 11 is composed of a receiving antenna unit 11B and the transmitting antenna unit 11A, the transmitting antenna unit 11A, the transmitting antenna elements and M _R receive antennas elements (receiving a transmitting antenna 1 element It is equipped with an array antenna).

As described above, one transmitting antenna element transmits a signal (transmitted wave) generated by the transmitter 12. For example, as shown in FIG. 2, each of the M _R receive antennas elements, it is transmitted from the one transmit antenna elements, to receive a reflected signal (received signal) by the body 50.

[Receiver 13]
The receiving unit 13 is a received signal received by each of the N receiving antenna elements, and is a period in which the received signal including the reflected signal transmitted from the transmitting antenna element and reflected by the moving body is derived from the activity of the moving body. Observe for the first period corresponding to. Here, the moving body is a living body 50 as shown in FIG. The cycle derived from the activity of the moving body is a cycle derived from the living body (biological fluctuation cycle) including at least one of respiration, heartbeat, and body movement of the living body 50.

In this embodiment, the receiving unit 13, N pieces (M _R number) receivers (receivers 13-1 receiver 1
It consists of 3-N). Each of the receivers 13-1 to 13-N converts the high-frequency signal received by the corresponding receiving antenna element into a low-frequency signal capable of signal processing. The receiving unit 13 transmits the low-frequency signals converted by each of the receivers 13-1 to 13-N to the complex transfer function calculation unit 14 for at least the first period.

[Complex transfer function calculation unit 14]
The complex transfer function calculation unit 14 calculates a plurality of complex transfer functions representing propagation characteristics between the transmitting antenna element and each of the N receiving antenna elements from the plurality of received signals observed in the first period.

Complex in the present embodiment, the complex transfer function calculation unit 14, representing the propagation characteristics between the low frequency signal transmitted from the receiving unit 13, and one transmit antenna elements and M _R receive antennas elements Calculate the transfer function. Hereinafter, a more specific description will be given with reference to FIG.

FIG. 3 is a diagram conceptually showing a state of signal wave transmission in the antenna unit 11 shown in FIG. As shown in FIG. 3, the transmitted wave transmitted from the transmitting antenna element of the transmitting antenna unit 11A is reflected by the living body 50 and reaches the receiving array antenna of the receiving antenna unit 11B. Here, the receiving array antenna consists M _R receive antennas elements, a linear array of element spacing d. Further, let θ be the direction of the living body 50 as seen from the front of the receiving array antenna. The distance between the living body 50 and the receiving array antenna is sufficiently large, and the reflected wave derived from the living body arriving at the receiving array antenna can be regarded as a plane wave.

In this case, the complex transfer function calculation unit 14 determines the complex reception signal vector observed by using the reception array antenna.

から、送信アンテナ素子と受信アレーアンテナとの間の伝搬特性を表す複素伝達関数ベクトルを算出することができる。複素伝達関数ベクトルは、例えば、

により算出できる。ここで、sは複素送信信号であり、既知であるものとする。

From, the complex transfer function vector representing the propagation characteristics between the transmitting antenna element and the receiving array antenna can be calculated. The complex transfer function vector is, for example,

Can be calculated by Here, it is assumed that s is a complex transmission signal and is known.

[Difference information calculation unit 15]
The difference information calculation unit 15 sequentially records the calculated complex transfer functions in a time series in the order in which the plurality of received signals are observed. Then, the difference information calculation unit 15 obtains 2 difference information indicating the difference between the two complex transfer functions at two time points at predetermined intervals among the plurality of complex transfer functions, which is represented by an N-dimensional vector. Calculate above. Here, the starting points of the two time points of the predetermined interval in each of the two or more difference information are different times. Further, the predetermined interval may be approximately half of the cycle derived from the living body 50 (biological fluctuation cycle).

FIG. 4 is a conceptual diagram showing an example of two time points of a predetermined interval used when calculating the difference information in the first embodiment. FIG. 5 is a conceptual diagram showing an example of two time points at predetermined intervals different from those in FIG. In FIG. 4, the vertical axis represents the variable channel value and the horizontal axis represents time. In addition, T _me as indicates the observation time of the received signal. This observation time T _meas is the first period described above. The observation time T _meas corresponds to, for example, the maximum cycle of biological fluctuation including at least one of respiration, heartbeat, and body movement of the living body, that is, the maximum cycle derived from biological fluctuation. In the example shown in FIG. 4, the observation time is set to about 3 seconds, which corresponds to the cycle of respiratory activity of the living body 50.

When a plurality of complex transfer functions calculated from the received signal observed by the receiver 13, that is, time-varying channels are sequentially recorded in the observation time T _meas as shown in FIG. 4, the observation time T _meas corresponds to the maximum period of biological fluctuation. Therefore, the observation time T _meas always includes the maximum value and the minimum value of the fluctuation of the living body 50. Here, assuming that the maximum cycle of biological change is T _max and the minimum cycle derived from biological change (minimum cycle of biological change) is T _min , the time difference between these half cycles, T _max / 2 and T _min / 2, is The time difference corresponds to the fluctuation of the living body 50. Therefore, the predetermined interval T when calculating the difference information of the complex transfer function can be in the range of T _max / 2 ≤ T ≤ T _min / 2. In this way, the predetermined interval T is set to the living body 5
Even if the cycle derived from 0 (biological fluctuation cycle) is approximately half, the components derived from the living body can be extracted from the time fluctuation channel for one cycle of the living body 50.

Further, in the example shown in FIG. 4, the difference information calculation unit 15 calculates, for example, the difference information indicating the difference of the complex transfer function at two time points of the time t and the time t + T, that is, the predetermined interval T. .. Then, the difference information calculation unit 15 calculates the difference information a plurality of times at a predetermined interval T starting from a time shifted by Δt. That is, the difference information calculation unit 15 further calculates such difference information at predetermined intervals T at two different time points (for different sets of complex transfer functions). Here, the difference information is calculated because the complex transfer function component passing through the fixed object other than the living body 50 is removed, and only the complex transfer function component passing through only the living body 50 remains.

と表せ、

である。また、l、mは測定番号を表す正の整数であり、サンプル時間である。 In this embodiment, the receiving antenna element is also a multiple number of plural (M _R number) differential value of the complex transfer function corresponding to the receiving antenna section 11B because of (difference information). These are collectively defined as a complex difference channel vector. If the number of receiving antenna elements is M _R , the complex difference channel vector is

Express it as

Is. In addition, l and m are positive integers representing measurement numbers and are sample times.

は転置を表す。なお、図４に示す例では、Nはチャネル観測回数であり、Ｃ_tやＣ_t+Tなど
時間間隔Tにおける２つの時点を含む台形の頂点（演算に用いたデータ）の数に対応する
。観測時間T_measが３秒で、１００回測定（観測）する場合に、N＝３００となる。

Represents transpose. In the example shown in FIG. 4, N is the number of channel observations, and corresponds to the number of trapezoidal vertices (data used in the calculation) including two time points in the time interval T such as C _t and C _{t + T.} When the observation time T _meas is 3 seconds and the measurement (observation) is performed 100 times, N = 300.

As shown in FIG. 3, the complex transfer function vector calculated by the complex transfer function calculation unit 14 includes reflected waves that do not pass through the living body 50, such as direct waves and reflected waves derived from fixed objects. On the other hand, in the complex difference channel vector, all the reflected waves that do not pass through the living body 50 are eliminated by the difference calculation of the complex transfer function vector at the two time points, and only the reflected waves derived from the living body are included. This difference calculation has the disadvantage that the complex transfer function of the reflected wave derived from the living body 50 is also subtracted, but the amplitude and phase of the reflected wave via the living body 50 constantly fluctuate with time due to biological activities such as respiration and heartbeat. Therefore, the complex difference channel vector is not completely zero. That is, when the complex transfer function vectors at two different time points are subtracted, the complex transfer function vector via the living body 50 multiplied by a coefficient remains.

It should be noted that the difference information calculation unit 15 calculates the difference information for a plurality of sets (complex transfer functions at two different time points) instantaneously by taking an average of a plurality of times as described later. This is to reduce the influence of noise and improve the accuracy of direction estimation. The predetermined interval T when calculating the difference information is not a fixed value as shown in FIG. 4, but is an arbitrary predetermined interval, that is, 2 such as time t'and time t'+ T'as shown in FIG. It may be a predetermined interval T'at one time point.

[Direction estimation processing unit 16]
The direction estimation processing unit 16 estimates the direction in which the moving object exists by using the estimation device 10 as a reference of the direction by using the difference information calculated in two or more. More specifically, the direction estimation processing unit 16 calculates and calculates an instantaneous correlation matrix, which is a correlation matrix of the difference time at two time points of the predetermined interval in the difference information, from each of the two or more calculated difference information. The arrival direction of the reflected signal is estimated by a predetermined arrival direction estimation method using the instantaneous correlation matrix. Then, the direction in which the moving object exists is estimated based on the estimated arrival direction of the reflected signal. Here, the predetermined arrival direction estimation method is an estimation method based on the MUSIC (MUltiple SIgnal Classification) algorithm.

In the present embodiment, the direction estimation processing unit 16 represents a correlation matrix shown in (Equation 1) from the complex difference channel vector calculated by the difference information calculation unit 15 as a plurality of difference information (hereinafter, referred to as “instantaneous correlation matrix”). Is calculated. The difference time between the two time points of the predetermined interval is instantaneous, and is therefore referred to as this.

は、複素共役転置を表す。 here,

Represents a complex conjugate transpose.

Further, the direction estimation processing unit 16 may further average (average calculation) this instantaneous correlation matrix as shown in (Equation 2). This is because, as described above, this makes it possible to reduce the influence of momentary noise and improve the accuracy of direction estimation.

Here, the rank of the instantaneous correlation matrix shown in (Equation 1) is 1. This instantaneous correlation matrix is a 4x4 matrix obtained by converting a 4x1 vector into a 4x4 matrix, and is merely a matrix in which the number of rows obtained by multiplying one row component by an integer is increased. Therefore, the simultaneous equations cannot be solved, that is, the rank is 1.

However, it is possible to recover the rank of the correlation matrix by averaging the instantaneous correlation matrix. That is, by averaging (Equation 1) as in (Equation 2), the eigenvalue (≈ rank) can be increased, so that the variables (targets) that can be solved can be increased. Therefore, the eigenvalues of (Equation 2) are increasing, and the estimation accuracy can be improved. Then, as will be described later, simultaneous estimation of a plurality of incoming waves becomes possible. It should be noted that improving the accuracy by using the averaging calculation is a means often used in the MUSIC method described later, but it is usually performed by the frequency component. On the other hand, the present embodiment differs in that it is averaged in the time direction.

In this way, by recording the complex transfer functions in time series over a certain period and using the recorded multiple complex transfer functions (all), the estimation accuracy can be improved even when the observation period is relatively short (for example, several seconds). The effect of being able to improve is obtained.

The direction estimation processing unit 16 can estimate the arrival direction of the reflected signal by using the instantaneous correlation matrix calculated as described above.

Hereinafter, a method of performing direction estimation using an instantaneous correlation matrix obtained from a complex difference channel vector will be described. Here, an estimation method based on the MUSIC algorithm will be described.

、

、

と書ける。 When the instantaneous correlation matrix shown in (Equation 2) is decomposed into eigenvalues,

,

,

Can be written.

は、要素数がM_Rである固有ベクトル、

は固有ベクトルに対応する固有値であり、

の順であるものとする。Lは到来波の数つまり検出対象の生体数である。 here,

Is an eigenvector whose number of elements is M _R ,

Is the eigenvalue corresponding to the eigenvector

It shall be in the order of. L is the number of incoming waves, that is, the number of living organisms to be detected.

と定義され、これにＭＵＳＩＣ法を適用する。ここで、kは波数である。 The steering vector (direction vector) of the receiving array antenna is

The MUSIC method is applied to this. Where k is the wave number.

That is, the direction estimation processing unit 16 estimates the direction of the incoming wave by searching for the maximum value of the evaluation function P _music (θ) shown below by using the steering vector of the receiving array antenna based on the MUSIC method. be able to.

Since the direction estimation processing unit 16 can estimate the arrival direction of the reflected signal by decomposing the instantaneous correlation matrix into eigenvalues and applying it to the MUSIC method in this way, the direction in which the living body 50 exists is estimated from the estimated arrival direction of the reflected signal. can do. This is because the estimated arrival direction of the reflected signal and the direction in which the living body 50 exists based on the estimation device 10 substantially coincide with each other.

[Operation of estimation device 10]
The operation of the estimation process of the estimation device 10 configured as described above will be described. FIG. 6 is a flowchart showing an estimation process of the estimation device 10 according to the first embodiment.

First, the estimation device 10 observes a received signal including a reflected signal transmitted from one transmitting antenna element and reflected by the living body 50 for a first period corresponding to a cycle derived from the activity of the living body 50 (S10). ).

Then, the estimation unit 10, a plurality of received signals observed in the first period, a plurality of complex transfer function representing the propagation characteristics between each of the one transmit antenna elements and M _R receive antennas elements Calculate (S20). Since the details are as described above, the description thereof is omitted here. The same applies to the following.

Next, the estimation device 10 calculates two or more difference information indicating the difference between the two complex transfer functions at two time points at predetermined intervals among the plurality of complex transfer functions (S30).

Then, the estimation device 10 estimates the direction in which the living body 50 exists by using the difference information of two or more (S40).

[Effects, etc.]
According to the estimation device 10 and the estimation method of the present embodiment, by calculating the difference information described above, only the components derived from the living body are wirelessly transmitted in a faster processing time than when the Fourier transform is used without using the Fourier transform. The signal processing that remains in the signal can be performed. Further, by using a plurality of difference information, it is possible to improve the estimation accuracy. Therefore, it is possible to estimate the direction in which the moving body exists with high accuracy by the short observation time corresponding to the period derived from the activity of the moving body. As a result, it is possible to estimate the direction in which the moving object exists by using the radio signal in a short time and with high accuracy.

(Embodiment 2)
In the first embodiment, the estimation device 10 for estimating the direction in which the moving object (living body) to be detected exists and the estimation method thereof are provided by using the difference information of the complex transfer functions observed at two different time points in a predetermined period. explained. In the second embodiment, the estimation device 20 for estimating the position of the moving object (living body) to be detected after using the same difference information and the estimation method thereof will be described.

[Configuration of estimation device 20]
FIG. 7 is a block diagram showing an example of the configuration of the estimation device 20 according to the second embodiment. FIG. 8 is a diagram showing an example of a detection target of the estimation device 20 shown in FIG. 7. The same elements as those in FIGS. 1 and 2 are designated by the same reference numerals, and detailed description thereof will be omitted.

The estimation device 20 shown in FIG. 7 includes a transmission antenna unit 21A, a reception antenna unit 21B, a transmission unit 22, a reception unit 23, a complex transfer function calculation unit 24, a difference information calculation unit 25, and a position estimation processing unit. With 26, the position of the moving body is estimated. The estimation device 20 shown in FIG. 7 has at least a different number of transmitting antenna elements as compared with the estimation device 10 shown in FIG. 1, whereby the position of a moving body can be estimated.

[Transmission unit 22]
The transmission unit 22 generates a high-frequency signal used for estimating the direction of the living body 50. For example, as shown in FIG. 8, the transmission unit 22 transmits the generated signal (transmission wave), M _T transmit antennas element included in the transmission antenna portion 21A from (transmit array antenna).

[Transmitting antenna unit 21A]
The transmitting antenna unit 21A is composed of M transmitting antenna elements (M is a natural number of 2 or more). In this embodiment, the transmitting antenna unit 21A is provided with M _T transmit antennas elements. As described above, M _T transmit antennas elements, the transmission section 22 transmits the generated signal (transmission wave).

[Receiving antenna unit 21B]
The receiving antenna unit 21B is composed of N receiving antenna elements (receiving array antennas) (N is a natural number of 2 or more). In this embodiment, as in the first embodiment, the receiving antenna unit 21B is provided with M _R receive antennas elements (reception array antenna). Then, for example, as shown in FIG. 8, in each of the M _R receiving antenna elements, the signal transmitted from the M _T transmitting antenna elements (transmitting array antenna) is a signal (reception) reflected by the living body 50. Signal) is received.

[Receiver 23]
The receiving unit 23 is a received signal received by each of the N receiving antenna elements, and receives a received signal including a reflected signal transmitted from each of the M transmitting antenna elements and reflected by the moving body. Observe the first period corresponding to the cycle derived from the activity of. Here, the moving body is a living body 50 as shown in FIG. It corresponds to the cycle derived from the activity of the moving body. The cycle derived from the activity of the moving body is a cycle derived from the living body (biological fluctuation cycle) including at least one of respiration, heartbeat, and body movement of the living body 50.

In this embodiment, the receiving section 23 is composed of M _R-number of receivers. M each of _R receivers, the frequency of the signal received by the corresponding receiving antenna elements, and converts the signal processing is a low frequency signal as possible. Receiving unit 23, at least a first period, a low frequency signal, each converted the M _R-number of receivers, and transmits the complex transfer function calculation unit 24.

[Complex transfer function calculation unit 24]
The complex transfer function calculation unit 24 calculates a plurality of complex transfer functions representing the propagation characteristics between each of the M transmitting antenna elements and the N receiving antenna elements from the plurality of received signals observed in the first period. To do.

In this embodiment, the complex transfer function calculation unit 24, the low frequency signal transmitted from the receiver 23, representing the propagation characteristics between the M _T transmit antennas elements and M _R receive antennas elements Calculate the complex transfer function. Hereinafter, a more specific description will be given with reference to FIG.

In FIG. 8, both the transmitting array antenna and the receiving array antenna are linear arrays having an element spacing d, and the directions of the living body 50 when viewed from the front of each of the transmitting array antenna and the receiving array antenna are θ _T and θ _R. It is assumed that the distance between the living body and the transmitting / receiving array antenna is sufficiently large compared to the opening width of the array antenna, and the signal via the living body departing from the transmitting array antenna and arriving at the receiving array antenna can be regarded as a plane wave.

As shown in FIG. 8, the transmitted wave transmitted from the M _T transmitting antenna elements (transmitting array antennas) of the transmitting antenna unit 21A at an angle θ _T is reflected by the living body 50 and is reflected by the living body 50 at an angle θ _R to the receiving array antenna. To reach.

In this case, the complex transfer function calculation unit 24 can calculate the complex transfer function vector from the complex received signal vector observed by using the reception array antenna. The complex transfer function vector is in the form of a matrix, but can be calculated in the same manner as in the first embodiment. As described above, the calculated complex transfer function matrix includes reflected waves that do not pass through the living body 50, such as direct waves and reflected waves derived from fixed objects.

[Difference information calculation unit 25]
The difference information calculation unit 25 sequentially records the calculated complex transfer functions in a time series in the order in which the plurality of received signals are observed. Then, the difference information calculation unit 25 is difference information indicating the difference between the two complex transfer functions at two time points at predetermined intervals among the plurality of complex transfer functions, and is the difference information represented by an M × N dimension matrix. Is calculated as 2 or more. Here, the starting points of the two time points of the predetermined interval in each of the two or more difference information are different times. Further, the predetermined interval may be approximately half of the cycle derived from the living body 50 (biological fluctuation cycle).

The two time points of the predetermined interval used when calculating the difference information are as described in the first embodiment using FIG. 4 and the like, and thus the description thereof will be omitted here.

Also in this embodiment, the difference information calculation unit 25 calculates the difference information indicating the difference between the two complex transfer functions calculated by the complex transfer function calculation unit 24 at two different time points of the predetermined interval T. To do. Further, the difference information calculation unit 25 also performs the calculation of the difference information at two different time points (a set of different complex transfer functions). Here, the difference information is calculated because, as in the first embodiment, the complex transfer function component passing through the fixed object other than the living body 50 is removed, and only the complex transfer function component passing through only the living body 50 remains. Is.

In the present embodiment, the number of transmitting antenna elements and the number of receiving antenna elements are both plural. Therefore, the number of difference values (difference information) of the complex transfer functions corresponding to the transmitting antenna unit 21A and the receiving antenna unit 21B is the transmitting antenna element × the number of receiving antenna elements (M _R × M _T ), and these are collectively complex differences. Defined as channel matrix H (l, m). The difference information calculation unit 25 calculates the complex difference channel matrix H (l, m) that can be expressed as follows as the difference information. Since all the reflected waves that do not pass through the living body 50 are erased by the difference calculation, the complex difference channel matrix H (l, m) includes only the reflected waves derived from the living body 50.

である。また、l、mは、測定番号を表す正の整数であり、サンプル時間である。 here,

Is. In addition, l and m are positive integers representing measurement numbers and are sample times.

[Position estimation processing unit 26]
The position estimation processing unit 26 estimates the position where the moving body exists by using the difference information calculated for the two or more. More specifically, first, the position estimation processing unit 26 calculates an instantaneous correlation matrix, which is a correlation matrix of the difference time at two time points of a predetermined interval in the difference information, from each of the two or more calculated difference information. .. Next, the position estimation processing unit 26 uses the calculated instantaneous correlation matrix and uses a predetermined arrival direction estimation method to transmit the transmission signal transmitted from the transmission antenna unit 21A to the moving object and the arrival direction of the reflected signal. To estimate. Then, the position estimation processing unit 26 estimates the position where the moving body exists based on the estimated transmission direction of the transmission signal and the estimated arrival direction of the reflected signal. Here, the predetermined arrival direction estimation method is an estimation method based on the MUSIC algorithm.

In the present embodiment, the position estimation processing unit 26 calculates the instantaneous correlation matrix from the complex difference channel matrix calculated by the difference information calculation unit 25 as a plurality of difference information.

More specifically, the position estimation processing unit 26 rearranges the elements of the above complex difference channel matrix H (l, m) calculated by the difference information calculation unit 25, and M _R M _T × shown in (Equation 3). Calculate the complex difference channel to be a vector of 1.

Here, vec (・) means the conversion of a matrix into a vector.

Next, the position estimation processing unit 26 calculates the instantaneous correlation matrix shown in (Equation 4) from this complex difference channel vector.

Further, the position estimation processing unit 26 may further average (average calculation) this instantaneous correlation matrix as shown in (Equation 5). This is because, as described above, this makes it possible to reduce the influence of momentary noise and improve the accuracy of direction estimation.

Here, the rank of the instantaneous correlation matrix in (Equation 4) is 1, but as described in the first embodiment, it is possible to recover the rank of the correlation matrix by averaging the instantaneous correlation matrix. This not only improves the estimation accuracy, but also enables simultaneous estimation of multiple incoming waves.

In this way, by recording the complex transfer functions in time series over a certain period and using the recorded multiple complex transfer functions (all), the estimation accuracy can be improved even when the observation period is relatively short (for example, several seconds). The effect of being able to improve is obtained.

The position estimation processing unit 26 can estimate the position of the living body 50 using the instantaneous correlation matrix calculated as described above.

Next, a method of estimating the direction using the instantaneous correlation matrix obtained from the complex difference channel matrix will be described. The estimation method based on the MUSIC algorithm will also be described in this embodiment.

、

、

と書ける。 When the instantaneous correlation matrix shown in (Equation 5) is decomposed into eigenvalues,

,

,

Can be written.

は、要素数がM_Rである固有ベクトル、

は固有ベクトルに対応する固有値であり、

の順であるものとする。Ｌは到来波の数つまり検出対象の生体数である。 here,

Is an eigenvector whose number of elements is M _R ,

Is the eigenvalue corresponding to the eigenvector

It shall be in the order of. L is the number of incoming waves, that is, the number of living organisms to be detected.

、受信アレーアンテナのステアリングベクトル（方向ベクトル）は、

と定義される。ここで、ｋは波数である。さらに、これらのステアリングベクトルを乗算し、

と、送受信アレーアンテナ双方の角度情報を考慮したステアリングベクトルを定義し、これにＭＵＳＩＣ法を適用する。 In addition, the steering vector (direction vector) of the transmission array antenna is

, The steering vector (direction vector) of the receiving array antenna is

Is defined as Here, k is the wave number. In addition, multiply these steering vectors and

And, a steering vector considering the angle information of both the transmission and reception array antennas is defined, and the MUSIC method is applied to this.

That is, the position estimation processing unit 26 can estimate the direction of the incoming wave by searching for the maximum value with the evaluation function P _music (θ) shown below using the multiplied steering vector based on the MUSIC method. ..

In the present embodiment, since it is necessary to search for the maximum value of the evaluation function for two angles (θ _T, θ _R ), a two-dimensional search process is performed. Then, the position estimation processing unit 26 estimates the transmission direction of the transmitted wave to the living body 50 and the arrival direction of the reflected wave from the living body 50 from the two angles (θ _T, θ _R ) thus obtained. The position of the living body 50 is estimated from the intersection of the two estimated directions.

[Operation of estimation device 20]
The operation of the estimation process of the estimation device 20 configured as described above will be described. FIG. 9 is a flowchart showing an estimation process of the estimation device 20 according to the second embodiment.

First, the estimation device 20 is transmitted from the M _T transmit antennas elements, a reception signal including a reflected signal reflected by the body 50, is observed for the first period corresponding to a period from the activity of the living body 50 ( S10A).

Then, the estimation unit 20, a plurality of received signals observed in the first period, the complex transfer function representing the propagation characteristics between each of M _T transmit antennas elements and M _R receive antennas elements Multiple calculations (S20A). Since the details are as described above, the description thereof is omitted here. The same applies to the following.

Next, the estimation device 20 calculates two or more difference information indicating the difference between the two complex transfer functions at two time points at predetermined intervals among the plurality of complex transfer functions (S30A).

Then, the estimation device 20 estimates the position where the living body 50 exists by using the difference information of two or more (S40A).

[Effects, etc.]
According to the estimation device 20 and the estimation method of the present embodiment, by calculating the difference information described above, only the components derived from the living body are wirelessly transmitted in a faster processing time than when the Fourier transform is used without using the Fourier transform. The signal processing that remains in the signal can be performed. Further, by using a plurality of difference information, it is possible to improve the estimation accuracy. Therefore, it is possible to estimate the direction in which the moving body exists with high accuracy by the short observation time corresponding to the period derived from the activity of the moving body. As a result, it is possible to estimate the position where the moving object exists by using the wireless signal in a short time and with high accuracy.

Here, an experimental evaluation was performed in order to confirm the effect according to the second embodiment, which will be described below.

FIG. 10 is a diagram showing the concept of an experiment using the estimation method according to the second embodiment.

Both the transmitting array antenna (Tx array) and the receiving array antenna (Rx array) shown in FIG. 10 have a 4 × 4 MIMO (Multiple Input Multiple Output) configuration using a 4-element patch array antenna. In addition, an SP4T (Single-Pole-4-Throw) switch was used on the transmitting side, and four receivers were used on the receiving side. Then, in this experiment, MIMO channels were measured using these devices.

Here, the array element spacing of the transmission / reception antenna was set to 0.5 wavelength, the transmission / reception distance D was set to 4.0 m, and the antenna height h was set to 1.0 m, which is the chest height of a human (Living-Body) when standing upright. A 2.47125GHz unmodulated continuous wave (CW) was transmitted from the transmitter, the sampling frequency (channel acquisition speed) was 7.0Hz, and the channel measurement time was 3.3 seconds. At the time of channel measurement, all but the subject were unmanned, and the subject faced the wall on the antenna side.

FIG. 11 is a diagram showing experimental results using the estimation method according to the second embodiment. FIG. 11 shows the result of living body position estimation when there are two subjects. The standing positions of the subjects during the experiment were (X = 1.0m, Y = 2.5m) for subject 1 and (X = 3.0m, Y = 2.0m) for subject 2. In FIG. 11, the actual position of the subject is indicated by ◯, and the position of the subject estimated by searching for the maximum value of the evaluation function is indicated by ◇. As shown in FIG. 11, even in the case of two subjects, the position of the subject estimated by searching for the maximum value of the evaluation function appears near the actual subject (living body). Therefore, it can be seen that the biological positions of a plurality of people can be estimated by the estimation method according to the second embodiment.

FIG. 12 is a diagram showing another experimental result using the estimation method according to the second embodiment. The solid line A in FIG. 12 shows the cumulative probability distribution (CDF: Cumulative Distribution Function) of the position estimation error when the biological position estimation is performed 1500 times when there are two subjects. The dotted line B in FIG. 12 shows the result (cumulative probability of position estimation error) of the biological position estimation method (Patent Document 3 above) using the Fourier transform, which is a conventional method, for the time variation channel of 3.28 seconds, which is the experimental condition. Distribution) is also shown as a comparative example.

From FIG. 12, the CDF 90% value in the case of the comparative example using the Fourier transform is 1.12 m, and the CDF 90% value in the case of using the estimation method according to the second embodiment is 0.39 m. Therefore, Embodiment 2
It can be seen that the estimation method related to is able to estimate 0.73 m more accurately. From this, it was shown that the biological position can be estimated with high accuracy even with a short observation time according to the present embodiment.

As described above, according to the present invention, by calculating the difference information which is the difference between the propagation channels at two different time points in a predetermined period, the processing time is faster than when the Fourier transform is used without using the Fourier transform. It is possible to perform signal processing in which only the components derived from the living body remain in the radio signal. Further, by using a plurality of difference information, it is possible to improve the estimation accuracy. This makes it possible to estimate the direction in which the moving body exists with high accuracy by a short observation time corresponding to the period derived from the activity of the moving body. As a result, it is possible to realize an estimation device and an estimation method that can estimate the direction and position of a moving object by using a wireless signal in a short time and with high accuracy.

Although the estimation device and the estimation method according to one aspect of the present invention have been described above based on the embodiments, the present invention is not limited to these embodiments. As long as the gist of the present invention is not deviated, various modifications that can be conceived by those skilled in the art are applied to the present embodiment, or a form constructed by combining components in different embodiments is also included in the scope of the present invention.

For example, in the first and second embodiments, the direction estimation and the position estimation of the living body 50 have been described as examples, but the living body 50 is not limited to the living body 50. It can be applied to various moving objects (machines, etc.) that give a Doppler effect to reflected waves by their activity when a high-frequency signal is irradiated.

Further, the present invention can be realized not only as an estimation device provided with such characteristic components, but also as an estimation method in which the characteristic components included in the estimation device are steps. it can. It can also be realized as a computer program that causes a computer to execute each characteristic step included in such a method. Needless to say, such a computer program can be distributed via a non-temporary recording medium such as a CD-ROM that can be read by a computer or a communication network such as the Internet.

The present invention can be used as an estimation device and an estimation method for estimating the direction and position of a moving body using a radio signal, and particularly for a measuring device for measuring the direction and position of a moving body including a living body and a machine, and a direction and position of a moving body. It can be used as an estimation device and an estimation method installed in home appliances that control according to the situation, monitoring devices that detect the intrusion of moving objects, and the like.

10, 20 Estimator 11 Antenna section 11A, 21A Transmit antenna section 11B, 21B Receiver antenna section 12 Transmitter 13, 23 Receiver section 14, 24 Complex transfer function calculation section 15, 25 Difference information calculation section 16 Direction estimation processing section 22 Transmission Part 26 Position estimation processing part 50 Living body

Claims (6)

On the computer
A period derived from the activity of the moving body among the received signals received by each of the N receiving antenna elements and including the reflected signal transmitted from one transmitting antenna element and reflected by the moving body. Acquire the received signal observed for the first period corresponding to
From the plurality of received signals observed in the first period, a plurality of complex transfer functions representing the propagation characteristics between the transmitting antenna element and each of the N receiving antenna elements are calculated.
(i) The calculated multiple complex transfer functions are sequentially recorded in a time series in the order in which the plurality of received signals are observed, and (ii) at two time points of the plurality of complex transfer functions at predetermined intervals. Calculate two or more difference information representing the difference between two complex transfer functions and expressed by an N-dimensional vector.
Using the average of the difference information calculated from the two or more, the process of estimating the direction in which the moving body exists is executed with the device having at least the N receiving antenna elements as the reference of the direction.
program. The starting point of the two time points of the predetermined interval in each of the two or more difference information is a different time.
The program according to claim 1. The moving body is a living body,
The program according to claim 1 or 2. The cycle is a cycle derived from a living body including at least one of respiration, heartbeat, and body movement of the living body, and the predetermined interval is approximately half of the cycle derived from the living body.
The program according to claim 3. In the process of estimating the direction in which the moving body exists,
From each of the two or more calculated difference information, an instantaneous correlation matrix, which is a correlation matrix of the difference time at two time points of the predetermined interval in the difference information, is calculated.
Using the calculated instantaneous correlation matrix, the arrival direction of the reflected signal is estimated by a predetermined arrival direction estimation method.
Based on the estimated arrival direction of the reflected signal, the direction in which the moving object exists is estimated.
The program according to any one of claims 1 to 4. The predetermined arrival direction estimation method is an estimation method based on the MUSIC (MUltiple SIgnal Classification) algorithm.
The program according to claim 5.

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