Estimating device, estimating method, and program

Abstract

An estimating device (101): generates a multi-carrier signal; causes a transmission antenna unit (100) having M transmission antenna elements to transmit the multi-carrier signal; observes, for a first period, reception signals received by N reception antenna elements of a reception antenna unit (130), the reception signals including reflected signals resulting from the multi-carrier signal transmitted from the M transmission antenna elements being reflected or scattered by a living body; uses the reception signals observed in the first period to calculate, for each of a plurality of subcarriers, a plurality of complex transfer functions representing propagation characteristics between the M transmission antenna elements and the N reception antenna elements; calculates a correlation matrix on the basis of the plurality of complex transfer functions; calculates biological information extracted from the correlation matrix; calculates a subcarrier phase gradient from the imaginary component of the biological information; and estimates the distance of a propagation path from the transmission antenna to the reception antenna via the living body.

Description

Estimation device, estimation method, and program

[0001] The present disclosure relates to an estimation device and an estimation method for estimating a distance or a position of a living body using a wireless signal.

[0002] Methods using wireless signals have been considered as a method for determining the location of a person (see, for example, Patent Documents 1 to 4). Patent Documents 1, 2, and 3 disclose techniques for estimating the location and state of a person to be detected by analyzing components including Doppler shifts using differential calculations. Patent Documents 4 and 5 disclose Doppler sensors using Orthogonal Frequency Division Multiplexing (OFDM) signals.

[0003] JP 2015-117972 A JP 2017-129558 A JP 2018-008021 A JP 2012-088279 A JP 2012-137340 A

[0004] H. Yamada, M. Ohmiya, Y. Ogawa and K. Itoh, “Superresolution techniques for time-domain measurements with a network analyzer,” in IEEE Transactions on Antennas and Propagation, vol. 39, no. 2, pp. 177-183, Feb. 1991

[0005] With conventional methods, it is difficult to estimate the distance from the estimation device to the living body with high accuracy.

[0006] In order to achieve the above object, an estimation device according to one embodiment of the present disclosure is an estimation device that estimates a distance to a living body, and includes: a transmission signal generation unit that generates a multicarrier signal in which a plurality of subcarrier signals are modulated; a transmission antenna unit having M (M is a natural number of 1 or more) transmission antenna elements; a transmission unit that processes the multicarrier signal and outputs it to the transmission antenna unit, thereby transmitting the multicarrier signal to the transmission antenna unit; a reception antenna unit having N (N is a natural number of 1 or more) reception antenna elements; and observation of received signals received by the N reception antenna elements, the received signals including reflected signals formed by the multicarrier signals transmitted from the M transmission antenna elements being reflected or scattered by the living body, for a first period corresponding to a cycle derived from the activity of the living body. The apparatus includes: a receiving unit; a complex transfer function calculation unit that calculates, using the received signals observed in the receiving unit during the first period, a plurality of complex transfer functions representing propagation characteristics between the M transmitting antenna elements and the N receiving antenna elements, for each of a plurality of subcarriers to which the plurality of subcarrier signals respectively correspond; a correlation matrix calculation unit that calculates a correlation matrix based on the plurality of complex transfer functions calculated for each of the plurality of subcarriers; a biological information calculation unit that calculates biological information including biological components extracted from the correlation matrix; and an estimation unit that calculates a subcarrier phase gradient, which is the gradient of the phase of a signal across frequency components corresponding to the plurality of subcarriers, from an imaginary component of the biological information, and estimates the distance of the propagation path from the transmitting antenna unit to the receiving antenna unit via the living body.

[0007] These general or specific aspects may be realized by a system, an integrated circuit, a computer program, or a computer-readable recording medium such as a CD-ROM, or may be realized by any combination of an apparatus, a system, a method, an integrated circuit, a computer program, and a recording medium.

[0008] According to the present disclosure, it is possible to estimate the distance from an estimation device to a living body with higher accuracy.

[0009] FIG. 1 is a block diagram showing an example of the configuration of an estimation device according to an embodiment. FIG. 2 is a conceptual diagram of the imaginary component of the frequency response versus the subcarrier number according to an embodiment. FIG. 3 is a conceptual diagram of the phase gradient versus the subcarrier number. FIG. 4 is a schematic diagram showing the positional relationship between a living body, a transmitting antenna element, and a receiving antenna element, and the position of the living body. FIG. 5 is a flowchart of the estimation process performed by the estimation device according to an embodiment. FIG. 6 is a diagram showing the conditions for a simulation using the estimation method according to an embodiment. FIG. 7 is a diagram showing the environment for a simulation using the estimation method according to an embodiment. FIG. 8 is a diagram showing the imaginary component of the frequency response versus the subcarrier number in a simulation using the estimation method according to an embodiment. FIG. 9 is a diagram showing another simulation result using the estimation method according to an embodiment.

[0010] (Findings that Form the Basis of the Present Disclosure) Methods that utilize wireless signals are being considered as methods for determining the location of a person, etc.

[0011] For example, Patent Documents 1 and 2 disclose a method of transmitting a radio signal to a predetermined area, receiving the radio signal reflected by a detection target using multiple antennas, and estimating a complex transfer function between the transmitting and receiving antennas. The complex transfer function is a function composed of complex numbers that represents the relationship between input and output, and 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. Furthermore, Patent Document 3 discloses a method of estimating the posture of a living body using a radar cross section (RCS) calculated from the received power, using a configuration similar to Patent Document 2. The RCS is an index that represents the area of ​​an object that reflects a transmitted wave, and the RCS of a living body varies depending on the posture of the living body.

[0012] Patent Document 1 further discloses a processing device capable of determining the position or status of a person to be detected by analyzing components including Doppler shift using a Fourier transform. More specifically, the processing device records the time changes of elements of a complex transfer function and performs a Fourier transform on the time waveform. Living organisms, such as people, impart a slight Doppler effect to the reflected waves due to biological activities such as breathing and heartbeat. Therefore, the components including Doppler shift obtained from the reflected waves include the influence of the living organism. On the other hand, the components without Doppler shift obtained from the reflected waves are not influenced by the living organism. In other words, the components without Doppler shift correspond to reflected waves from fixed objects or direct waves between transmitting and receiving antennas. In other words, the position or status of the person to be detected can be obtained by using components included in a predetermined frequency range in the Fourier-transformed waveform.

[0013] Patent Document 2 discloses a method for extracting components containing slight Doppler shifts due to the influence of living organisms by recording the time changes of elements of a complex transfer function and analyzing the difference information. In other words, this method makes it possible to know the position and state of a person to be detected using the difference information.

[0014] On the other hand, Patent Document 3 discloses an OFDM Doppler radar that transmits pulses using OFDM signals and detects the Doppler shift caused by a target moving object. Also, Patent Document 4 discloses a high-speed processing method for OFDM Doppler radar that does not require Fourier transform.

[0015] Furthermore, Patent Documents 4 and 5 disclose techniques for improving the estimation accuracy of the complex transfer function between transmitting and receiving antennas by transmitting an OFDM signal. Patent Document 4 discloses that the received noise component can be reduced by averaging the complex transfer function for each subcarrier. Patent Document 5 discloses that the received noise component can be reduced by selecting the subcarrier with the maximum received power.

[0016] However, the methods of Patent Documents 1, 2, and 3 transmit unmodulated waves, making it difficult to use commercially available devices and requiring dedicated hardware. In other words, currently popular communication devices cannot be used, and users must install dedicated hardware in addition to their existing communication devices.

[0017] Furthermore, in the methods of Patent Documents 4 and 5, in order to obtain sufficient accuracy, the transmission pulse needs to be steep, which requires a wide frequency band, and therefore the hardware costs are higher than those of communication devices for consumer use.

[0018] The technology of Non-Patent Document 1 can estimate the ToF (Time of Flight) between a transmitting antenna and a receiving antenna, or the distance that can be calculated from the ToF, by transmitting and receiving signals of multiple frequencies using a measuring device such as a network analyzer. This utilizes the property that, similar to a range sensor using FMCW (Frequency Modulated Continuous Wave) radar, when two signals of different frequencies are transmitted with the same phase, the phase received by the receiving antenna changes depending on the frequency difference of the signals and the distance they propagate between the antennas. The technology of Non-Patent Document 1 further improves resolution by performing ToF estimation using the MUSIC (Multiple Signal Classification) method.

[0019] However, this technology requires that the transmitter and receiver operate on the same reference frequency or be highly synchronized, making it difficult to apply to home devices such as wireless LANs. Also, it can only estimate the distance between antennas, making it difficult to estimate the distance between a device and, for example, a living body that does not have a special device.

[0020] Therefore, the inventors have come up with an estimation device that can estimate the position of a living body with higher accuracy.

[0021] That is, an estimation device according to a first aspect of the present disclosure is an estimation device that estimates a distance to a living body, and includes: a transmission signal generation unit that generates a multicarrier signal obtained by modulating a plurality of subcarrier signals; a transmission antenna unit having M (M is a natural number of 1 or more) transmission antenna elements; a transmission unit that processes the multicarrier signal and outputs it to the transmission antenna unit, thereby causing the multicarrier signal to be transmitted by the transmission antenna unit; a reception antenna unit having N (N is a natural number of 1 or more) reception antenna elements; and a reception unit that observes, for a first period corresponding to a cycle derived from activity of the living body, reception signals received by the N reception antenna elements, the reception signals including reflected signals formed by the multicarrier signals transmitted from the M transmission antenna elements being reflected or scattered by the living body. a complex transfer function calculation unit that calculates a plurality of complex transfer functions representing propagation characteristics between the M transmitting antenna elements and the N receiving antenna elements for each of a plurality of subcarriers to which the plurality of subcarrier signals respectively correspond, using the received signals observed in the first period in the receiving unit; a correlation matrix calculation unit that calculates a correlation matrix based on the plurality of complex transfer functions calculated for each of the plurality of subcarriers; a biological information calculation unit that calculates biological information including biological components extracted from the correlation matrix; and an estimation unit that calculates a subcarrier phase gradient, which is the gradient of the phase of a signal across frequency components corresponding to the plurality of subcarriers, from an imaginary component of the biological information, and estimates the distance of the propagation path from the transmitting antenna unit to the receiving antenna unit via the living body.

[0022] This allows the distance of the propagation path to the living body to be accurately estimated based on the frequency characteristics by analyzing the phase gradient of the signal across multiple subcarriers.

[0023] Furthermore, it is possible to realize a biometric radar that measures the position of a living body by utilizing an existing communication device that uses a multicarrier signal such as OFDM as a transmission signal. For example, receivers of multicarrier signals such as OFDM are already widely used in mobile phones, television broadcast receivers, wireless LAN devices, etc., and it is possible to realize a biometric radar that measures the position of a living body at lower cost than when using an unmodulated signal.

[0024] An estimation device according to a second aspect of the present disclosure is the estimation device according to the first aspect, wherein the bioinformation calculation unit extracts only components in a specific frequency domain corresponding to fluctuation components as the biocomponents from a transformation matrix obtained by transforming the correlation matrix into a frequency domain.

[0025] This makes it possible to extract only the signal components corresponding to the fluctuation components, thereby reducing the influence of unnecessary components and improving the accuracy of estimating the distance to the living body.

[0026] An estimation device according to a third aspect of the present disclosure is the estimation device according to the first aspect, wherein the bioinformation calculation unit extracts only components in a specific frequency domain derived from the movement of the biologic body as the biologic components from a transformation matrix obtained by transforming the correlation matrix into a frequency domain.

[0027] This makes it possible to extract signal components corresponding only to components derived from the movement of the living body, thereby reducing the influence of unnecessary components and improving the accuracy of estimating the distance to the living body.

[0028] An estimation device according to a fourth aspect of the present disclosure is the estimation device according to the second aspect, wherein the specific frequency range includes only positive frequency components.

[0029] According to this, by limiting to positive frequency components, signal processing can be performed based on information in a specific frequency band derived from a living body, and the accuracy of the estimation processing can be improved.

[0030] An estimation device according to a fifth aspect of the present disclosure is the estimation device according to the third aspect, wherein the specific frequency range includes only positive frequency components.

[0031] According to this, by limiting to positive frequency components, signal processing can be performed based on information in a specific frequency band derived from a living body, and the accuracy of the estimation processing can be improved.

[0032] An estimation device according to a sixth aspect of the present disclosure is an estimation device according to any one of the first to fifth aspects, wherein the estimation unit calculates the subcarrier phase gradient using one of a sine wave fitting of an imaginary component of the biological component of the correlation matrix, second-order differentiation, a MUSIC (MUltiple SIgnal Classification) method, a Capon method, an FFT (Fast Fourier Transform), and a DFT (Discrete Fourier Transform), thereby estimating a third distance which is the sum of a first distance from the transmitting antenna unit to the biological component and a second distance from the biological component to the receiving antenna unit.

[0033] According to this, by performing calculations using any one of the processing methods suitable for analyzing the phase gradient, it is possible to estimate the third distance based on the imaginary component of the complex transfer function with high accuracy.

[0034] An estimation device according to a seventh aspect of the present disclosure is the estimation device according to the sixth aspect, wherein at least one of the M transmitting antenna elements and the N receiving antenna elements includes two antenna elements, and the estimation unit further calculates two or more ellipses whose focal points are the positions of the M transmitting antenna elements and the N receiving antenna elements and whose major axis length is the third distance, and estimates the intersection of the two or more calculated ellipses as the position of the living body.

[0035] This makes it possible to geometrically identify the position of a living body within a plane or space depending on the arrangement of the transmitting antenna section and the receiving antenna section, thereby improving the accuracy of position estimation.

[0036] An estimation method according to an eighth aspect of the present disclosure is an estimation method executed by an estimation device that estimates a distance to a living body, the estimation method comprising: generating a multicarrier signal in which a plurality of subcarrier signals are modulated; processing the multicarrier signal and outputting it to a transmitting antenna unit having M (M is a natural number of 1 or more) transmitting antenna elements, thereby transmitting the multicarrier signal from the transmitting antenna unit; observing received signals received by N or more (N is a natural number of 1 or more) receiving antenna units, the received signals including reflected signals formed by the multicarrier signals transmitted from the M transmitting antenna elements being reflected or scattered by the living body, for a first period corresponding to a cycle derived from activity of the living body; and using the received signals observed in the first period, For each of M×N combinations of M transmitting antenna elements and each of the N receiving antenna elements, a plurality of complex transfer functions representing the propagation characteristics between the transmitting antenna element and the receiving antenna element in that combination are calculated for each of a plurality of subcarriers to which the plurality of subcarrier signals respectively correspond, a correlation matrix is ​​calculated based on the plurality of complex transfer functions calculated for each of the plurality of subcarriers, biological information including biological components extracted from the correlation matrix is ​​calculated, and a subcarrier phase gradient, which is the gradient of the phase of the signal across frequency components corresponding to the plurality of subcarriers, is calculated from the imaginary component of the biological information, and the distance of the propagation path from the transmitting antenna unit to the receiving antenna unit via the biological body is estimated.

[0037] This allows the distance of the propagation path to the living body to be accurately estimated based on the frequency characteristics by analyzing the phase gradient of the signal across multiple subcarriers.

[0038] A program according to a ninth aspect of the present disclosure is a program for causing a computer to execute the estimation method according to the eighth aspect.

[0039] These comprehensive or specific aspects may be realized as a system, an integrated circuit, a computer program, or a recording medium such as a computer-readable CD-ROM, or may be realized as any combination of an apparatus, a system, a method, an integrated circuit, a computer program, and a recording medium.

[0040] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. Note that each of the embodiments described below represents a preferred specific example of the present disclosure. The numerical values, shapes, materials, components, component placement and connection configurations, steps, and step order shown in the following embodiments are merely examples and are not intended to limit the present disclosure. Furthermore, among the components in the following embodiments, components that are not described in the independent claims that represent the highest concept of the present disclosure will be described as optional components that constitute a more preferred embodiment. Note that in this specification and drawings, components having substantially the same functional configuration will be assigned the same reference numerals to avoid redundant description.

[0041] In this embodiment, a method for detecting a living body will be described for a single input single output (SISO) system in which both the transmitting antenna unit and the receiving antenna unit have a single antenna element. Note that the method described in this embodiment can also be applied to a MIMO system in which there are multiple transmitting antennas and multiple receiving antennas, or a SIMO or MISO system in which there are multiple transmitting antennas or multiple receiving antennas, by extracting elements of a specific transmitting / receiving pair from multiple pairs of transmitting / receiving antennas and performing the same processing as in the SISO system.

[0042] [Configuration of Estimation Apparatus 101] FIG. 1 is a block diagram showing an example of the configuration of an estimation apparatus according to an embodiment.

[0043] The estimation device 101 shown in FIG. 1 includes a transmitting antenna unit 100, a transmitting unit 110, a transmitting signal generating unit 120, a receiving antenna unit 130, a receiving unit 140, a complex transfer function calculating unit 150, a correlation matrix calculating unit 160, a biological information calculating unit 180, and an estimation unit 190. The estimation device 101 estimates the position of a living organism 20. The estimation device 101 may estimate, as information related to the living organism 20, the position of the living organism 20 in a target space, the posture of the living organism 20, determine whether the living organism 20 exists in the target space, identify the living organism 20 based on information (complex transfer function matrix) registered in advance for each individual living organism 20, or estimate the movement of the living organism 20. In other words, the estimation device 101 performs processing (estimation processing) on ​​the estimation target, such as the position, posture, presence, identification, and movement, for the living organism 20.

[0044] [Transmitting Antenna Unit 100] The transmitting antenna unit 100 has M transmitting antenna elements. Here, M is a natural number equal to or greater than 1, and is 1 in this embodiment. As described above, the transmitting antenna elements transmit multicarrier signals (transmitting waves) generated by the transmitting unit 110, which will be described later.

[0045] [Transmitting Unit 110] The transmitting unit 110 performs appropriate processing on the signal generated by the transmitting signal generating unit 120 (described later) to generate a transmission wave. Examples of processing performed here include up-conversion, which converts the signal from an intermediate frequency (IF) frequency band to a radio frequency (RF) frequency band, and amplification, which amplifies the signal to an appropriate transmission level. The transmitting unit 110 outputs the processed multicarrier signal to the transmitting antenna unit 100, causing the transmitting antenna unit 100 to transmit the multicarrier signal. As a result, the multicarrier signal is transmitted from M transmitting antenna elements provided in the transmitting antenna unit 100.

[0046] [Transmission Signal Generator 120] The transmission signal generator 120 generates a multicarrier signal in which multiple subcarrier signals are modulated. Specifically, the transmission signal generator 120 generates multiple subcarrier signals corresponding to multiple subcarriers in different frequency bands, and multiplexes the generated multiple subcarrier signals to generate a multicarrier signal. In this embodiment, the transmission signal generator 120 generates an OFDM signal consisting of S subcarriers, which has high frequency band utilization efficiency, as the multicarrier signal. Note that the transmission signal generator 120 is not limited to generating an OFDM signal in which the subcarriers are orthogonal, as long as the multicarrier signal is obtained by multicarrier modulation, and may also generate other multicarrier signals, such as a simple FDM (Frequency Division Multiplexing) signal.

[0047] Furthermore, the signal generated by the transmission signal generation unit 120 may be shared with a signal used for communication such as a wireless LAN. That is, the transmission signal used for sensing the living body 20 may be used exclusively for sensing the living body 20, or may be used for both sensing the living body 20 and information communication.

[0048] [Receiving Antenna Unit 130] The receiving antenna unit 130 has N receiving antenna elements, where N is a natural number equal to or greater than 1, and is 1 in this embodiment. The N receiving antenna elements receive signals (received signals, described later) transmitted from the M transmitting antenna elements and reflected by the living body 20.

[0049] [Receiving unit 140] The receiving unit 140 observes received signals received by N receiving antenna elements, including reflected signals resulting from the multicarrier signals transmitted from M transmitting antenna elements being reflected or scattered by the living organism 20, for a first period corresponding to a cycle derived from the activity of the living organism 20. The cycle derived from the activity of the living organism is a cycle derived from the living organism (biological variation cycle) that is a time period equal to or longer than half the cycle of any one of the cycles of breathing, heartbeat, and body movement of the living organism 20.

[0050] The receiver 140 converts the high-frequency signals received by the N receiving antenna elements into low-frequency signals that can be processed, and then demodulates the OFDM signals into S subcarrier signals (IQ symbols).

[0051] The receiving unit 140 further outputs all or part of M×N sets of S subcarrier signals (IQ symbols) corresponding to each combination of M transmitting antenna elements and N receiving antenna elements to the complex transfer function calculating unit 150. In this embodiment, M is 1 and N is 1, so all or part of one set of S subcarrier signals is output to the complex transfer function calculating unit 150.

[0052] The receiver 140 may constantly monitor the signals received by the receiving antenna 130 and continuously or periodically transmit S low-frequency signals (IQ symbols).

[0053] [Complex Transfer Function Calculation Unit 150] The complex transfer function calculation unit 150 calculates a complex transfer function using a plurality of received signals observed during a first period. Specifically, for each of M×N combinations, which are combinations of M transmitting antenna elements and N receiving antenna elements, the complex transfer function calculation unit 150 may calculate a plurality of complex transfer functions, each representing a propagation characteristic between the transmitting antenna element and the receiving antenna element in the combination, for each of a plurality of subcarriers to which a plurality of subcarrier signals correspond, or may calculate the complex transfer functions for only one or more combinations of the M×N combinations.

[0054] The M×N combinations are all possible combinations when M transmitting antenna elements and N receiving antenna elements are combined one-to-one. In this embodiment, only one of the M×N combinations will be used hereafter. When more than one combination is used, the following processing can be performed in parallel to increase the noise resistance of the estimation result and improve accuracy.

[0055] In this embodiment, the complex transfer function calculation unit 150 uses S subcarrier signals to calculate N×M×S sets of complex transfer functions representing propagation characteristics between each transmitting antenna element and each receiving antenna element for each of the S subcarrier signals. As a result, the receiving unit 140 may generate a complex transfer function matrix having N×M×S elements. The calculated complex transfer function matrix also includes reflected waves that do not pass through the living body 20, such as direct waves and reflected waves from fixed objects.

[0056] The complex transfer function calculation unit 150 may constantly calculate a complex transfer function vector using each of a plurality of subcarrier signals that are continuously or periodically output. With this configuration, when the estimation device 101 shares the hardware of a communication device, the complex transfer function vector that is constantly calculated for use in processing by the communication device can also be used by the estimation device 101.

[0057] In this embodiment, the complex transfer function calculation unit 150 calculates, from the S subcarrier signals transmitted from the receiving unit 140, a complex transfer function vector h(t) representing the propagation characteristics between M transmitting antenna elements and N receiving antenna elements for the s-th subcarrier during the observation time t, which is expressed as a complex transfer function matrix as shown in (Equation 1).

[0058]

[0059] [Correlation Matrix Calculation Unit 160] The correlation matrix calculation unit 160 calculates a correlation matrix of each element of the complex transfer function vector h(t) calculated by the complex transfer function calculation unit 141. That is, the correlation matrix calculation unit 160 calculates the correlation matrix based on a plurality of complex transfer functions calculated for each of a plurality of subcarriers.

[0060] The calculation of the correlation matrix will be specifically explained below using mathematical expressions. The element corresponding to the subcarrier s in the above-mentioned complex transfer function vector h(t) is defined as h ｓ Then, as shown in (Equation 2), the element h ｓis expressed as the sum of two propagation components that are a function of time t. The two propagation components include a direct wave component between the transmitting antenna unit 100 and the receiving antenna unit 130 and a propagation path component that is reflected by the living body 20 from the transmitting antenna unit 100 and received by the receiving antenna unit 130.

[0061]

[0062] Here, h ｓｄ represents a direct wave component between the transmitting antenna unit 100 and the receiving antenna unit 130 that does not pass through the living body 20, and h ｓｖ e ｉθｖ（ｔ） represents the component of the propagation path from the transmitting antenna unit 100, reflected by the living body 20, and received by the receiving antenna unit 130. ｖ (t) is a phase component that changes with the movement of the living body 20, and represents the time-dependent phase change contained in the signal reflected by the living body 20. ｅ (t) represents a non-periodic random phase error caused by clock mismatch between the transmitter and receiver or mismatch within the device. Here, i is the imaginary unit (i ２ =-1).

[0063] Next, the diagonal elements of the correlation matrix r calculated based on the above-mentioned complex transfer function vector h(t) can be expressed as in (Equation 3). Among these diagonal elements, if we focus on the element corresponding to the subcarrier s (i.e., the sth diagonal element), the random phase error component θ ｅ (t) can be cancelled (removed).

[0064]

[0065]

[0066] In (Equation 3) and (Equation 4), * indicates a complex conjugate. In other words, it means the conjugate complex number of a complex number (a complex number in which the real part remains the same and the sign of the imaginary part is inverted). For example, the complex conjugate of a + bi is a - bi.

[0067] [Biometric Information Calculation Unit 180] The biological information calculation unit 180 calculates biological information including the biological component extracted from the correlation matrix. Specifically, the biological information calculation unit 180 sequentially records, for each of the plurality of subcarriers, the values ​​of r, which are diagonal elements of the correlation matrix of the complex transfer function calculated by the correlation matrix calculation unit 160, in a time series that corresponds to the order in which the plurality of received signals were observed. Then, the biological information calculation unit 180 extracts components attributable to the living organism 20 from the time series data of the diagonal elements of the correlation matrix observed during a first period, which are sequentially recorded in time series, for each of the plurality of subcarriers. Then, the biological information calculation unit 180 calculates, for each of the plurality of subcarriers, a biological component transfer function vector represented by an S-dimensional vector based on each extracted component.

[0068] Here, the biological component transfer function vector is obtained by extracting signal components contained in the received signal that correspond to reflected or scattered waves (biological components) that have passed through the living body 20. These biological components are extracted based on fluctuations in the diagonal elements of a correlation matrix recorded in time series during a first period. Specific extraction methods include, for example, the Fourier transform described in Patent Document 1 and the method using time series difference information described in Patent Document 2.

[0069] For example, in a method using Fourier transform, a Fourier transform is performed on the diagonal elements of the correlation matrix recorded in time series during the observation period (i.e., the first period) with the observation time (slow time) as the time axis, to extract only the components contained in a specific frequency band. This frequency band can be, for example, the range from 0.1 Hz to 3 Hz, where effects due to periodic activities (biological activities) such as breathing and heartbeat of the living organism 20 are believed to appear. This processing allows a biological component transfer function vector to be calculated for each of the multiple frequency components within the frequency band. Here, the signal components that have passed through the living organism 20 are calculated using the aforementioned θ ｖ Since the frequency component varies depending on (t), by extracting only the frequency component corresponding to biological activity by Fourier transform, θ ｖ This effectively extracts the signal components related to (t), which results in the extraction of the second and third terms of the terms shown in (Equation 4).

[0070] Here, the second and third terms of (Equation 4) will be explained. Assuming that the surface of the living body 20 moves in simple harmonic motion with an angular frequency ω, e in (Equation 4) ｉθｖ（ｔ） represents the time fluctuation of the signal phase due to the vital component (for example, periodic motion such as breathing or heartbeat). This fluctuation can be expressed as θ using the amplitude a of the vital component and the angular frequency ω of the vital component. ｖ (t) = acos(ωt). At this time, e included in (Equation 4) ｉθｖ（ｔ） The exponential term is the Bessel function of the first kind J ｎ By using the above, it can be expressed as shown in (Equation 5).

[0071]

[0072] Here, n represents the nth harmonic. Generally, the first harmonic (first harmonic: n = ±1) is dominant in the vital component, so in this embodiment, only the component n = ±1 is considered approximately. Note that the first kind of Bessel function has the following features: －１ (a) = -J １ (a), J １ (-a) = -J １ By using these properties, (Equation 5) can be approximately expressed as (Equation 6) below.

[0073]

[0074]

[0075] From the above, the first harmonic corresponding to the second and third terms in (Equation 4) is composed of only the imaginary component. In order to observe this, in this embodiment, as shown in (Equation 8) and (Equation 9), the time series data (time response) at the observation site is Fourier transformed in the time direction for the s-th diagonal element in (Equation 3). That is, the frequency response corresponding to the vital component is calculated by the Fourier transform, and the frequency component with the maximum amplitude is extracted from that, thereby determining the frequency component r ｑ (s, f) is found, and −4q shown in (Equation 7) ｓ J １(a) A component corresponding to cosωt can be obtained. To observe such a term, the time response of (Equation 3) is Fourier transformed as shown in (Equation 8) and only the corresponding component is extracted.

[0076]

[0077] Here, F[·] is the Fourier transform, and f is the frequency after Fourier transform in the time direction. ｑ The frequency f is selected as the frequency at which (s, f)| is maximum.

[0078] In this embodiment, the first harmonic (n = ±1) of the n-th harmonic is used approximately as the first harmonic, but any harmonic component (e.g., second harmonic, third harmonic, etc.) may be used for calculation as needed.

[0079] Furthermore, a method has been shown in which a frequency response corresponding to a vital component is extracted using (Equation 8) and an imaginary component with the maximum amplitude in the response is calculated, but this is not limiting, and a frequency response corresponding to any frequency component may be extracted, and the result may be used as R ｑ It may be used as (s, f).

[0080] [Estimation unit 190] The estimation unit 190 estimates the vital component r based on the imaginary component of the frequency response calculated by the biological information calculation unit 180. ｑ 2 shows the vital component r of the frequency response to the subcarrier number in this embodiment. ｑ 1 is a conceptual diagram of the imaginary components of the frequency response. Among the imaginary components of the frequency response, the vital component 210 exhibits a sinusoidal waveform relative to the subcarrier number, while the non-vital component 200 exhibits a linear waveform relative to the subcarrier number. Based on these characteristics, the estimation unit 190 distinguishes between the vital component and the non-vital component, and performs estimation processing on the estimation target derived from the vital component by evaluating the consistency with a sinusoidal wave model using a fitting processing described below.

[0081] The estimation unit 190 estimates the vital component r based on the imaginary component of the frequency response. ｑThe subcarrier frequency direction components included in are fitted with a sine wave model A sin(Bs+C) using amplitude A, subcarrier phase gradient B, and phase shift C. Here, in order to evaluate the consistency with the sine wave model, the estimation unit 190 fits the vital component r calculated by (Equation 8) ｑ The estimator 190 performs fitting with the sinusoidal wave model A sin (Bs + C) for the subcarrier frequency direction component of the signal. That is, the estimator 190 performs fitting with the sinusoidal wave model A sin (Bs + C) for the vital component r ｑ Based on the difference between ｆｉｔ The waveform structure for the vital component is modeled by determining the coefficients A, B, and C that minimize the above.

[0082] Here, the subcarrier frequency direction component is a set of frequency responses obtained corresponding to a plurality of subcarrier numbers s, and indicates the tendency (fluctuation) of the frequency response expressed as a function with the subcarrier number s as a variable.

[0083] Evaluation function r ｆｉｔ is defined by the following (Equation 9).

[0084]

[0085] Here, φ is a coefficient that depends on the initial phase of the vital sign, and is multiplied equally for all subcarriers. Therefore, the estimation unit 190 calculates, for example, the imaginary component Im(r ｑ (s, f')e ｉφ ) is maximized, the consistency with the sine wave can be improved, and the estimation accuracy can be improved. That is, based on (Equation 9), the estimation unit 190 identifies the coefficients A (amplitude), B (subcarrier phase gradient), and C (phase shift) that minimize the error (sum of squared differences) between the observed data (imaginary component of frequency response) and the sine wave model. As a result, the estimation unit 190 estimates the vital component r ｑ The sinusoidal structure contained in the signal can be quantified, and the quantification results can be used to perform subsequent estimation processing on the estimation target.

[0086] 3 is a conceptual diagram of the phase gradient with respect to the subcarrier number s in (Equation 3). As shown in FIG. 3, the phase changes as the subcarrier frequency increases, and the gradient is ｓｄ and the reflected wave component h ｓｖ The complex conjugate product h ＊ ｓｄ h ｓｖ The imaginary part of the reflected wave component h ｓｖ From the subcarrier phase gradient 310 of the direct wave component h ｓｄ is the remainder component obtained by dividing the subcarrier phase gradient 300 of ＊ ｓｄ h ｓｖ The distance estimation result based on this is a value obtained by subtracting the distance of the direct propagation path between the transmitting antenna unit 100 and the receiving antenna unit 130 from the distance of the propagation path from the transmitting antenna unit 100 to the receiving antenna unit 130 via the living body 20. Therefore, the estimation unit 190 can estimate the distance of the entire propagation path of the signal emitted from the transmitting antenna unit 100 to the receiving antenna unit 130 via the living body 20 by adding a known distance based on the direct wave obtained from the installation positions of the transmitting antenna unit 100 and the receiving antenna unit 130.

[0087] At this time, the total propagation path distance d ｖ is the complex conjugate product h ＊ ｓｄ h ｓｖ Estimated distance d based on ＴＯＦ and the direct wave component h ｓｄ The distance between the transmitter and receiver d based on ｄ In this embodiment, the distance between the transmitter and receiver d ｄ may be a known value or may be a value estimated by a known method.

[0088] Here, the subcarrier phase gradient refers to the rate of change in the phase of a signal observed across frequency components corresponding to multiple subcarriers, i.e., phase tilt. This reflects the phase change caused by differences in propagation distance and arrival time to the target, and is an index used for estimating the distance to an object.

[0089]

[0090] where κ ｍａｘ is the wave number of the maximum frequency in the used subcarrier, κ ｍｉｎ represents the wave number of the minimum frequency in the subcarrier used.

[0091] 4 is a schematic diagram showing the positional relationship between the living body, the transmitting antenna element (the transmitting antenna unit 100), and the receiving antenna element (the receiving antenna unit 130), and the position of the living body 20 defined based on the third distance. ｖ corresponds to the sum of the first distance a between the transmitting antenna unit 100 and the living body 20 and the second distance b between the living body 20 and the receiving antenna unit 130 in FIG. 4, that is, the third distance.

[0092] Also, the distance d ｄ corresponds to the transmission / reception distance d between the transmitting antenna unit 100 and the receiving antenna unit 130. The estimation unit 190 estimates a third distance, which is the sum of the first distance a between the transmitting antenna unit 100 and the living body 20 and the second distance b between the living body 20 and the receiving antenna unit 130, using a correlation matrix calculated for each of the multiple subcarriers. This allows the estimation unit 190 to estimate that the living body 20 is located on the periphery of an ellipse 1010 whose foci are the positions of the transmitting antenna unit 100 and the receiving antenna unit 130. Note that the estimation unit 190 may estimate multiple third distances using three or more pairs of transmitting antenna units 100 and receiving antenna units 130, and estimate the position of the living body 20 based on the intersections of multiple ellipses obtained from each of the multiple third distances.

[0093] [Operation of Estimation Device 101] The operation of the estimation process of the estimation device 101 configured as above will be described with reference to Fig. 5. Fig. 5 is a flowchart of the estimation process executed by the estimation device 101 in the embodiment.

[0094] The estimation device 101 calculates a plurality of complex transfer functions for each of a plurality of subcarriers based on observation of a received signal in a first period (S100).

[0095] Next, the estimation device 101 calculates a correlation matrix based on the complex transfer functions calculated for each of the subcarriers (S200).

[0096] Next, the estimation apparatus 101 calculates biometric information including the biometric components extracted from the correlation matrix (S300).

[0097] Finally, the estimation device 101 calculates the subcarrier phase gradient, which is the gradient of the signal phase across frequency components corresponding to multiple subcarriers, from the imaginary component of the biometric information, and estimates the distance of the propagation path from the transmitting antenna unit 100 through the living body 20 to the receiving antenna unit 130 (S400).

[0098] The details of the processing of each step have been described above and will not be repeated here.

[0099] [Effects, etc.] The estimation device 101 according to this embodiment estimates the distance to a living body 20. The estimation device 101 includes a transmission signal generation unit 120, a transmission antenna unit 100, a transmission unit 110, a reception antenna unit 130, a reception unit 140, a complex transfer function calculation unit 150, a correlation matrix calculation unit 160, a biological information calculation unit 180, and an estimation unit 190. The transmission signal generation unit 120 generates a multicarrier signal in which a plurality of subcarrier signals are modulated. The transmission antenna unit 100 has M (M is a natural number equal to or greater than 1) transmission antenna elements. The transmission unit 110 processes the multicarrier signal and outputs it to the transmission antenna unit 100, thereby causing the transmission antenna unit 100 to transmit the multicarrier signal. The reception antenna unit 130 has N (N is a natural number equal to or greater than 1) reception antenna elements. The receiving unit 140 observes, for a first period corresponding to a cycle resulting from the activity of the living body 20, received signals received by N receiving antenna elements, including reflected signals resulting from the multicarrier signals transmitted from M transmitting antenna elements being reflected or scattered by the living body. The complex transfer function calculation unit 150 uses the received signals observed by the receiving unit 140 during the first period to calculate multiple complex transfer functions representing propagation characteristics between the M transmitting antenna elements and the N receiving antenna elements, for each of multiple subcarriers corresponding to multiple subcarrier signals. The correlation matrix calculation unit 160 calculates a correlation matrix based on the multiple complex transfer functions calculated for each of the multiple subcarriers. The biological information calculation unit 180 calculates biological information including biological components extracted from the correlation matrix. The estimation unit 190 calculates a subcarrier phase gradient, which is the gradient of the signal phase across frequency components corresponding to the multiple subcarriers, from the imaginary component of the biological information, and estimates the distance of the propagation path from the transmitting antenna unit 100 to the receiving antenna unit 130 via the living body.

[0100] This allows the distance of the propagation path between the living body 20 to be accurately estimated based on the frequency characteristics by analyzing the phase gradient of the signal across multiple subcarriers.

[0101] In the estimation device 101 according to this embodiment, the biometric information calculation unit 180 extracts only components in a specific frequency domain derived from the movement of the living body 20 as biometric components from a transformation matrix obtained by transforming the correlation matrix into the frequency domain.

[0102] This makes it possible to extract only the signal components corresponding to the fluctuation components, thereby reducing the influence of unnecessary components and improving the accuracy of estimating the distance to the living body 20 .

[0103] In the estimation device 101 according to this embodiment, the biometric information calculation unit 180 extracts only components in a specific frequency domain derived from the movement of the living body 20 as biometric components from a transformation matrix obtained by transforming the correlation matrix into the frequency domain.

[0104] This makes it possible to extract signal components corresponding only to components resulting from the movement of the living body 20, thereby reducing the influence of unnecessary components and improving the accuracy of estimating the distance to the living body 20.

[0105] In the estimation device 101 according to this embodiment, the specific frequency region includes only positive frequency components.

[0106] According to this, by limiting the frequency components to positive ones, signal processing can be performed based on information in a specific frequency band derived from the living body 20, and the accuracy of the estimation processing can be improved.

[0107] In the estimation device 101 according to this embodiment, the estimation unit 190 calculates the subcarrier phase gradient using one of the following methods: fitting the imaginary component of the biological component of the correlation matrix with a sine wave, second-order differentiation, the MUSIC (MUltiple SIgnal Classification) method, the Capon method, the FFT (Fast Fourier Transform), and the DFT (Discrete Fourier Transform), thereby estimating a third distance, which is the sum of the first distance from the transmitting antenna unit 100 to the biological component 20 and the second distance from the biological component 20 to the receiving antenna unit 130.

[0108] According to this, by performing calculations using any one of the processing methods suitable for analyzing the phase gradient, it is possible to estimate the third distance based on the imaginary component of the complex transfer function with high accuracy.

[0109] In the estimation device 101 according to this embodiment, at least one of the M transmitting antenna elements and the N receiving antenna elements may include two antenna elements. The estimation unit 190 may further calculate two or more ellipses whose focal points are the positions of the M transmitting antenna elements and the N receiving antenna elements and whose major axes have a length of the third distance, and estimate the intersection of the two or more calculated ellipses as the position of the living body 20.

[0110] This makes it possible to geometrically identify the position of a living body within a plane or space depending on the arrangement of the transmitting antenna section 100 and the receiving antenna section 130, thereby improving the accuracy of position estimation.

[0111] (Modification 1) In this embodiment, in an arbitrary range, the sine wave model A sin(Bs+C) shown in (Equation 9) and the vital component r ｑ The coefficient B was calculated by calculating the combination of coefficients A, B, and C that minimizes the difference between the coefficients A, B, and C. Alternatively, the distance to the living body 20 may be calculated by directly calculating only the coefficient B, as shown in (Equation 10). Here, when y=A sin(Bs+C) is defined, the coefficient B may be calculated by second-order differentiation of y in the direction of the number of subcarriers s, as shown in (Equation 12).

[0112]

[0113] Here, B corresponds to the phase gradient of the signal across the subcarriers, and B>0. Therefore, the coefficient B can be calculated by taking the square root based on (Equation 12). Furthermore, the distance between the estimation device 101 and the living body 20 may be calculated using (Equation 10) and (Equation 11) based on the coefficient B calculated using (Equation 12).

[0114] (Modification 2) In this embodiment, the coefficient B is calculated by calculating a combination of the coefficients A, B, and C that minimizes the error shown in (Equation 8) in an arbitrary range.ｑ Alternatively, a Fourier transform (FFT or DFT) or a spectrum estimation method (MUSIC method or Capon method) may be applied to the signal, and the coefficient B may be calculated from the peak in the resulting frequency spectrum.

[0115] (Modification 3) In this embodiment, the fitting process is performed using the imaginary part in (Equation 9), but instead, the real part may be used as shown in (Equation 13).

[0116]

[0117] (Modification 4) In this embodiment, the fitting process is performed using the imaginary part in (Equation 9). However, instead of this, as shown in (Equation 14), the sums of the squares of the absolute values ​​of the imaginary part and real part are compared, and the difference r ｄｉｆｆ Based on this, the larger component of the square of the absolute value of the real part and the imaginary part may be selectively used as in (Equation 15).

[0118]

[0119]

[0120] (Variation 5) In this embodiment, the first observation time t1 may be determined based on the complex transfer function vector h(t) corresponding to the observation time t. The first observation time t1 may be calculated based on the amplitude of the complex transfer function vector h(t) according to any criterion, such as the time when the amplitude is maximum or minimum (peak or valley) or the time when a predetermined threshold is reached.

[0121] While the estimation device and estimation method according to one aspect of the present disclosure have been described above based on embodiments and modifications, the present disclosure is not limited to these embodiments. As long as they do not deviate from the spirit of the present disclosure, various modifications conceivable by those skilled in the art to the present embodiment or configurations constructed by combining components of different embodiments are also included within the scope of the present disclosure.

[0122] For example, in the embodiment and the modified example, distance estimation and position estimation of the living body 20 have been described as an example, but the present invention is not limited to the living body 20. When a high-frequency signal is irradiated, the present invention can be applied to various moving objects (machines, etc.) that, due to their activity, give a Doppler effect to the reflected wave.

[0123] Here, evaluation was carried out by simulation to confirm the effects of this embodiment, and the simulation will be described below.

[0124] [Simulation] FIG. 6 is a diagram showing conditions for a simulation using the estimation method according to this embodiment.

[0125] As shown in Figure 6, both the transmitting and receiving antennas were configured as a single-element omnidirectional antenna in a SISO configuration. The distance between the transmitter and receiver was 4.0 m, and a 2.4 GHz band signal was transmitted from the transmitter. The channel measurement time was 10.24 seconds, the number of subcarriers used was 64, the frequency band was 20 MHz, the vital frequency was 0.2 Hz, and the sampling frequency was 100 Hz. A random phase component was added, and the SNR (Signal to Noise Ratio) was 20 dB.

[0126] Figure 7 shows the layout of the antenna and target in the simulation. The transmitter position was set to (x, y) = (0, 0), the receiver position was set to (x, y) = (4, 0), and the target (subject) position was set to (x, y) = (2, 3).

[0127] 8 is a conceptual diagram of the imaginary component of the frequency response versus the subcarrier number. The non-vital component 200 of the imaginary component of the frequency response exhibits a linear trend versus the subcarrier number, fluctuating around 0. Meanwhile, the vital component 210 of the imaginary component of the frequency response exhibits a sinusoidal waveform, and the fitting waveform 220 applied to the vital component 210 of the imaginary component of the frequency response is drawn to trace the vital component 210 of the imaginary component of the frequency response. This confirms that the estimation method according to this embodiment functions effectively and that fitting is possible.

[0128] Fig. 9 is a diagram showing another simulation result using the estimation method according to the embodiment. Fig. 9 shows the cumulative distribution function (CDF) of ranging errors. In Fig. 9, the horizontal axis represents ranging errors (unit: m), and the vertical axis represents CDF values ​​corresponding to ranging errors. With the proposed estimation method, the CDF value for a ranging error of 0.3 m is 0.75, indicating that highly accurate living body position estimation is possible.

[0129] Furthermore, the present disclosure can be realized not only as a ranging sensor or positioning sensor having such characteristic components, but also as an estimation method in which the characteristic components included in the ranging sensor or positioning sensor are used as steps. Furthermore, the present disclosure can also be realized as a computer program that causes a computer to execute each of the characteristic steps included in such a method. It goes without saying that such a computer program can be distributed on a non-transitory computer-readable recording medium such as a CD-ROM or via a communication network such as the Internet.

[0130] The present disclosure can be used in sensors and estimation methods that estimate the distance and position of a living body using wireless signals, and in particular in ranging sensors and positioning sensors installed in measuring instruments that measure the distance and position of a living body, including between a living body and a machine, home appliances that perform control according to the distance and position of a living body, and monitoring devices that detect the intrusion of a living body.

[0131] 20 Living body 101 Estimation device 100 Transmitting antenna unit 110 Transmitting unit 120 Transmitting signal generating unit 130 Receiving antenna unit 140 Receiving unit 150 Complex transfer function calculating unit 180 Living body information calculating unit 190 Estimating unit 200 Non-vital component of imaginary component of frequency response 210 Vital component of imaginary component of frequency response 220 Fitted waveform of vital component of imaginary component of frequency response 300 Phase gradient of direct wave 310 Phase gradient obtained by positive frequency extraction

Claims

1. An estimation device for estimating a distance to a living body, comprising: a transmission signal generation unit that generates a multicarrier signal modulated with a plurality of subcarrier signals; a transmission antenna unit having M (M is a natural number equal to or greater than 1) transmission antenna elements; a transmission unit that processes the multicarrier signal and outputs it to the transmission antenna unit, thereby causing the multicarrier signal to be transmitted by the transmission antenna unit; a reception antenna unit having N (N is a natural number equal to or greater than 1) reception antenna elements; a reception unit that observes, for a first period corresponding to a cycle derived from activity of the living body, reception signals received by the N reception antenna elements, the reception signals including reflected signals formed when the multicarrier signals transmitted from the M transmission antenna elements are reflected or scattered by the living body; and a complex transfer function calculation unit that uses the reception signals observed in the first period by the reception unit to calculate a plurality of complex transfer functions representing propagation characteristics between the M transmission antenna elements and the N reception antenna elements, for each of a plurality of subcarriers to which the plurality of subcarrier signals respectively correspond. an estimation device comprising: a correlation matrix calculation unit that calculates a correlation matrix based on a plurality of complex transfer functions calculated for each of the plurality of subcarriers; a biometric information calculation unit that calculates biometric information including a biometric component extracted from the correlation matrix; and an estimation unit that calculates a subcarrier phase gradient, which is a gradient of a phase of a signal across frequency components corresponding to the plurality of subcarriers, from an imaginary component of the biometric information, and estimates a distance of a propagation path from the transmitting antenna unit to the receiving antenna unit via the living body.

2. The estimation device according to claim 1, wherein the biological information calculation unit extracts, as the biological component, only components in a specific frequency domain corresponding to fluctuation components from a transformation matrix obtained by transforming the correlation matrix into the frequency domain.

3. The estimation device according to claim 1, wherein the biometric information calculation unit extracts only components in a specific frequency domain derived from the movement of the biological body as the biological components from a transformation matrix obtained by transforming the correlation matrix into the frequency domain.

4. The estimation device according to claim 2, wherein the specific frequency range includes only positive frequency components.

5. The estimation device according to claim 3, wherein the specific frequency range includes only positive frequency components.

6. The estimation device according to any one of claims 1 to 5, wherein the estimation unit calculates the subcarrier phase gradient using one of the following methods for fitting the imaginary component of the biological component of the correlation matrix with a sine wave, second-order differentiation, the MUSIC (MUltiple SIgnal Classification) method, the Capon method, an FFT (Fast Fourier Transform), and a DFT (Discrete Fourier Transform), thereby estimating a third distance which is the sum of a first distance from the transmitting antenna unit to the biological component and a second distance from the biological component to the receiving antenna unit.

7. The estimation device according to claim 6, wherein at least one of the M transmitting antenna elements and the N receiving antenna elements includes two antenna elements, and the estimation unit further calculates two or more ellipses whose focal points are the positions of the M transmitting antenna elements and the N receiving antenna elements and whose major axis has a length of the third distance, and estimates the intersection of the two or more calculated ellipses as the position of the living body.

8. An estimation method executed by an estimation device for estimating a distance to a living body, comprising: generating a multicarrier signal in which a plurality of subcarrier signals are modulated; processing the multicarrier signal and outputting it to a transmitting antenna unit having M (M is a natural number equal to or greater than 1) transmitting antenna elements, thereby transmitting the multicarrier signal from the transmitting antenna unit; observing, for a first period corresponding to a cycle derived from activity of the living body, received signals received by N or more (N is a natural number equal to or greater than 1) receiving antenna units, the received signals including reflected signals formed when the multicarrier signals transmitted from the M transmitting antenna elements are reflected or scattered by the living body; using the received signals observed in the first period, for each of M×N combinations of the M transmitting antenna elements and each of the N receiving antenna elements, calculating a plurality of complex transfer functions representing propagation characteristics between the transmitting antenna element and the receiving antenna element in the combination for each of a plurality of subcarriers to which the plurality of subcarrier signals respectively correspond; calculating a correlation matrix based on the plurality of complex transfer functions calculated for each of the plurality of subcarriers; an estimation method for estimating a distance of a propagation path from the transmitting antenna unit to the receiving antenna unit via the living body, the method comprising: calculating biometric information including a biometric component extracted from the correlation matrix; calculating a subcarrier phase gradient, which is a gradient of a phase of a signal across frequency components corresponding to the plurality of subcarriers, from an imaginary component of the biometric information; and estimating a distance of a propagation path from the transmitting antenna unit to the receiving antenna unit via the living body.

9. A program for causing a computer to execute the estimation method according to claim 8.