Estimation device, estimation method, and program

Abstract

An estimation device (101) according to the present invention generates a multicarrier signal, causes a transmission antenna unit (100) having M transmission antenna elements to transmit the multicarrier signal and, for a first period corresponding to a period derived from activity of a living body, observes a reception signal received by N reception antenna elements of a reception antenna unit (130), the reception signal including a reflection signal that results from the multicarrier signal transmitted from the M transmission antenna elements and reflected or scattered by the living body. A plurality of complex transfer functions respectively representing propagation characteristics between the M transmission antenna elements and the N reception antenna elements are calculated for each of a plurality of subcarriers by using the reception signal observed in the first period, squared values of amplitudes of the plurality of complex transfer functions are calculated, and the distance of a path from the transmission antenna to the reception antenna via the living body is estimated on the basis of the square value.

Description

Estimation device, estimation method, and program

[0001] The present disclosure relates to an estimation device and an estimation method for estimating a distance to a living body or a position of the 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 5). 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, the direction to the living body, and the like with high accuracy.

[0006] In order to achieve the above object, an estimation device according to an embodiment of the present disclosure is an estimation device for estimating 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 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 reception signals received by the N reception antenna elements, wherein the multicarrier signals transmitted from the M transmission antenna elements are reflected by the living body. or a receiving unit that observes a received signal including a scattered reflected signal for a first period corresponding to a cycle resulting from the activity of the living body; a complex transfer function calculation unit that uses the received signal observed in the first period in the receiving unit to calculate a plurality of complex transfer functions, each representing a propagation characteristic 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 square value calculation unit that calculates the square value of the amplitude of each of the plurality of complex transfer functions; and an estimation unit that estimates the distance of a path from the transmitting antenna unit via the living body to the receiving antenna unit based on the square value.

[0007] An estimation method according to an 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 including generating a multicarrier signal in which a plurality of subcarrier signals are modulated, processing the multicarrier signal, and outputting the multicarrier signal to a transmitting antenna unit having M (M is a natural number of 1 or more) transmitting antenna elements, thereby transmitting the multicarrier signal to the transmitting antenna unit, and estimating that the received signals, which are received by N or more (N is a natural number of 1 or more) receiving antenna units and include reflected signals resulting from the multicarrier signal being reflected or scattered by the living body, are attributed to activity of the living body. and using the received signals observed during the first period, for each of M×N combinations of the M transmitting antenna elements and the N receiving antenna elements, calculates a plurality of complex transfer functions, each of which represents 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 the plurality of subcarrier signals respectively correspond, calculates the squared value of the amplitude of each of the plurality of complex transfer functions, and estimates the distance of the path from the transmitting antenna unit via the living body to the receiving antenna unit based on the squared value.

[0008] 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.

[0009] According to the present disclosure, the position of a living body can be estimated with higher accuracy.

[0010] Fig. 1 is a block diagram showing an example of the configuration of an estimation device according to an embodiment. Fig. 2 is a schematic diagram showing a waveform after Fourier transform of the squared amplitude value according to an embodiment. Fig. 3 is a schematic diagram showing the relationship between the phase gradient of the squared amplitude value relative to the subcarrier. Fig. 4 is a schematic diagram showing the relationship between frequency and the gradient of the phase difference. Fig. 5 is a schematic diagram showing the phase of a time-domain biological component transfer function matrix. Fig. 6 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. 7 is a flowchart showing estimation processing by an estimation device according to an embodiment.

[0011] (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.

[0012] 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.

[0013] 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.

[0014] 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.

[0015] 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.

[0016] 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.

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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.

[0021] Therefore, the inventors have come up with an estimation device etc. that can estimate the position etc. of a living body with higher accuracy.

[0022] That is, an estimation device according to a first aspect of the present disclosure is an estimation device for estimating 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 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 reception signals received by the N reception antenna elements, wherein the multicarrier signals transmitted from the M transmission antenna elements are reflected or distorted by the living body. The system comprises a receiving unit that observes a received signal including scattered reflected signals for a first period corresponding to a cycle resulting from the activity of the living body; a complex transfer function calculation unit that uses the received signal observed in the first period by the receiving unit to calculate a plurality of complex transfer functions, each representing a propagation characteristic 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 square value calculation unit that calculates the square value of the amplitude of each of the plurality of complex transfer functions; and an estimation unit that estimates the distance of a path from the transmitting antenna unit via the living body to the receiving antenna unit based on the square value.

[0023] This calculates the squared value of the amplitude of each of multiple complex transfer functions, and based on the squared value, estimates the distance of the path from the transmitting antenna unit through the living body to the receiving antenna unit, thereby making it possible to estimate the position of the living body with high accuracy.

[0024] Furthermore, with this configuration, by using a multi-carrier signal such as OFDM for the transmission signal, it is possible to realize a bio-radar that measures the distance to a living body by utilizing existing communication devices. For example, receivers of multi-carrier signals such as OFDM are already widespread in mobile phones, television broadcast receivers, wireless LAN devices, etc., and it is possible to realize a bio-radar that measures the distance to a living body at lower cost than when using an unmodulated signal.

[0025] An estimation device according to a second aspect of the present disclosure is the estimation device according to the first aspect, wherein the estimation unit transforms the squared value into a frequency domain, extracts a component in a specific frequency domain corresponding to a fluctuation component, and estimates the distance based on the component in the specific frequency domain.

[0026] This makes it possible to remove components that do not change over time, such as direct waves between the transmitting antenna unit and the receiving antenna unit and reflections from walls, etc., and to estimate the position of the living body with higher accuracy.

[0027] An estimation device according to a third aspect of the present disclosure is the estimation device according to the first aspect, wherein the estimation unit transforms the squared value into a frequency domain, extracts components in a specific frequency domain derived from the movement of the living body, and estimates the distance based on the components in the specific frequency domain.

[0028] Therefore, it is possible to more precisely remove unnecessary received signal components other than breathing or body movement specific to a living body, and to estimate the position of the living body with higher accuracy.

[0029] 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 is a component in a positive frequency range.

[0030] Therefore, components that are not caused by the movement of the living body can be removed, and the position of the living body can be measured with higher accuracy.

[0031] 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 is a component in a positive frequency range.

[0032] Therefore, components that are not caused by the movement of the living body can be removed, and the position of the living body can be measured with higher accuracy.

[0033] 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 uses any one of a MUSIC (Multiple Signal Classification) method, a beamformer method, and a Capon method to estimate, as the distances, a first distance from the transmitting antenna unit to the living body, a second distance from the living body to the receiving antenna unit, a first angle indicating the direction from the transmitting antenna unit to the living body, and a second angle indicating the direction from the receiving antenna unit to the living body.

[0034] Therefore, by using the MUSIC method, the position of the living body can be estimated with fine distance resolution.

[0035] An estimation method according to a seventh 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 including generating a multicarrier signal in which a plurality of subcarrier signals are modulated, processing the multicarrier signal, and outputting the multicarrier signal to a transmitting antenna unit having M (M is a natural number of 1 or more) transmitting antenna elements, thereby transmitting the multicarrier signal to the transmitting antenna unit, and estimating that 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 resulting from the multicarrier signal being reflected or scattered by the living body, are estimated as signals originating from activity of the living body. and using the received signals observed during the first period, for each of M×N combinations of the M transmitting antenna elements and the N receiving antenna elements, calculates a plurality of complex transfer functions, each of which represents 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 the plurality of subcarrier signals respectively correspond, calculates the squared value of the amplitude of each of the plurality of complex transfer functions, and estimates the distance of the path from the transmitting antenna unit via the living body to the receiving antenna unit based on the squared value.

[0036] This calculates the squared value of the amplitude of each of multiple complex transfer functions, and based on the squared value, estimates the distance of the path from the transmitting antenna unit through the living body to the receiving antenna unit, thereby making it possible to estimate the position of the living body with high accuracy.

[0037] A program according to an eighth aspect of the present disclosure is a program for causing a computer to execute the estimation method according to the seventh aspect.

[0038] 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.

[0039] 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.

[0040] (Embodiment) In this embodiment, a method for detecting a living body will be described for a SISO (Single Input Single Output) 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 both the transmitting antenna and the receiving antenna are multiple, or a SIMO system or MISO system in which either the transmitting antenna or the receiving antenna is multiple, by extracting elements of a specific transmitting / receiving pair from multiple transmitting / receiving pairs and performing the same processing as in the SISO system.

[0041] [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.

[0042] 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 square value calculating unit 160, and an estimating unit 170. The estimating device 101 estimates the position of a living organism 20. The estimating device 101 may estimate the position of the living organism 20 in a target space, may estimate the posture of the living organism 20, may determine whether or not the living organism 20 is present in the target space, may identify the living organism 20 based on information (complex transfer function matrix) registered in advance for each individual living organism 20, or may estimate the movement of the living organism 20.

[0043] [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.

[0044] [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.

[0045] [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.

[0046] 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.

[0047] [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.

[0048] [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.

[0049] 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).

[0050] 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. Note that the receiving unit 140 may constantly monitor the received signals received by the receiving antenna unit 130 and continuously or periodically transmit the S low-frequency signals (IQ symbols).

[0051] [Complex Transfer Function Calculation Unit 150] The complex transfer function calculation unit 150 uses the multiple received signals observed in the first time period to calculate the complex transfer function H. 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 multiple complex transfer functions, each representing a propagation characteristic between the transmitting antenna element and the receiving antenna element in the combination, for each of multiple subcarriers to which multiple subcarrier signals correspond, or may calculate the complex transfer functions for only one or more combinations out of the M×N combinations.

[0052] 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.

[0053] 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.

[0054] The complex transfer function calculation unit 150 may constantly calculate the complex transfer function matrix by using each of the multiple 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 matrix that is constantly calculated for use in processing by the communication device can also be used by the estimation device 101.

[0055] In this embodiment, the complex transfer function calculation unit 150 calculates, from the S subcarrier signals transmitted from the reception unit 140, the propagation characteristics H(t) between M (one in this embodiment) transmitting antenna elements and N (one in this embodiment) receiving antenna elements for the s-th subcarrier during the observation time t, using a complex transfer function matrix based on Equation 1.

[0056]

[0057] [Square Value Calculation Section 160 ] The square value calculation section 160 calculates the square of the amplitude of each element of the complex transfer function matrix H(t) calculated by the complex transfer function calculation section 150 .

[0058] The calculation of the square will be specifically explained below using mathematical expressions. Let h be the element corresponding to the subcarrier k in the above-mentioned complex transfer function matrix. ｋ and decomposes it into a direct wave component between the transmitting antenna unit 100 and the receiving antenna unit 130 and a component of the path from the transmitting antenna unit 100 reflected by the living body 20 and received by the receiving antenna unit 130 as a function of time t, as shown in Equation 2.

[0059]

[0060] The square value calculation unit 160 calculates this hｋ h, which is the amplitude of (t) ｋ The square of the absolute value of (t) is calculated. From the squared value obtained in this way, random phase errors are removed, as shown in Equation 3.

[0061]

[0062] [Estimation unit 170] The estimation unit 170 estimates the distance of the path from the transmitting antenna unit 100 to the receiving antenna unit 130 via the living body 20, based on the squared value calculated by the squared value calculation unit 160. The estimation unit 170 includes a living body correlation matrix calculation unit 171 and a distance angle calculation unit 172.

[0063] [Biological correlation matrix calculation unit 171] The biological correlation matrix calculation unit 171 calculates, for each of the plurality of subcarriers, the square value |h ｋ | ２ The biological correlation matrix calculation unit 171 then calculates a biological component transfer function matrix expressed by an S-dimensional vector by extracting a biological component from the squared value of the amplitude of the complex transfer function observed during the first period, which is sequentially recorded in time series for each of the multiple subcarriers.

[0064] Here, the biological component transfer function matrix is ​​obtained by extracting reflected waves or scattered waves (biological components) contained in the received signal that have passed through the living body 20. Methods for determining the biological components from complex transfer functions (squared amplitude values) recorded in time series include the Fourier transform disclosed in Patent Document 1 and a method using difference information disclosed in Patent Document 2.

[0065] For example, in a method using a Fourier transform, the squared value of the amplitude is Fourier transformed with respect to the observation time (slow time) to extract only specific frequency components, thereby calculating a biological component transfer function matrix for each of multiple frequency components that may include the influence of the activity of the living organism 20, for example, those included in the frequency range from 0.1 Hz to 3 Hz.

[0066] The component that passes through the living body 20 of interest here is θ ｋｖ(t). Therefore, the biological correlation matrix calculation unit 171 extracts, from the squared amplitude components after Fourier transform, only the positive frequency region and the frequency region that may include the influence of the activity of the living body 20 as the biological component transfer function matrix. As a result, only the first term of Equation 3 is extracted.

[0067] The above-mentioned positive frequency region will be explained using Fig. 2, which is a schematic diagram of the component after frequency conversion of the squared value of amplitude. When the squared value of amplitude is Fourier transformed, a waveform symmetrical in the positive direction and the negative direction with respect to 0 Hz is obtained, as shown in component 200 in Fig. 2. Here, the positive region of this component 200 corresponds to the first term in formula 3, and the negative region of this component 200 corresponds to the second term in formula 3. In other words, the biological correlation matrix calculation unit 171 extracts the waveform of component 210 in Fig. 2 as a positive frequency region and a frequency region that may include the influence of the activity of the living organism 20, thereby obtaining only the component of the first term in formula 3.

[0068] FIG. 3 shows a conceptual diagram of the phase gradient with respect to subcarrier k in Equation 3.

[0069] In Figure 3, the phase for subcarrier k changes as the frequency of the subcarrier increases. k0 and component h via the living body 20 kv Here, the first term of Equation 3 is the component h ｖ is the remainder component obtained by dividing the subcarrier-phase slope 300 of the direct wave h0 from the subcarrier-phase slope 310 of the ＊ ｋ０ h ｋｖ The distance estimation result for is a value obtained by subtracting the distance of the path from the transmitting antenna unit 100 to the receiving antenna unit 130 directly from the path from the transmitting antenna unit 100 to the receiving antenna unit 130 via the living body 20. Therefore, the distance of the path from the transmitting antenna unit 100 to the receiving antenna unit 130 via the living body 20 is h ＊ ｋ０ h ｋｖ The distance is estimated by adding the distance of the direct wave calculated from the installation positions of the transmitting antenna section 100 and the receiving antenna section 130 to the distance estimation result for the above.

[0070] The relationship between frequency and phase of the biological component transfer function matrix is ​​shown in Figure 4. The solid line 800 represents how the phase of each component of the biological component transfer function matrix varies with the subcarrier frequency when the biological component 20 is located at a certain position. As the biological component 20 approaches the transmitting antenna unit 100 or the receiving antenna unit 130 from this position, the path length of the radio waves reflected by the biological component 20 shortens, causing the slope of the graph to become gentler, as shown by the dashed line 810. In principle, the ToF or the distance to the biological component 20 can be estimated from the slope of this graph. Specifically, this biological component transfer function matrix is ​​further inverse Fourier transformed in the subcarrier direction to obtain a time-domain biological component transfer function matrix, which determines the time from when the signal containing the biological component is transmitted from the transmitting antenna unit 100 to when it is received by the receiving antenna unit 130.

[0071] Fig. 5 shows the relationship between time (column direction of the matrix) and phase of the time-domain biological component transfer function matrix. The phase changes of the solid line 800 and dashed line 810 in Fig. 4 appear as peaks indicated by the solid line 910 and dashed line 920, respectively. However, the time resolution Δt calculated here is expressed by Equation 4 using the subcarrier bandwidth B.

[0072]

[0073] For example, when the bandwidth is 20 MHz, the time resolution is equivalent to 0.5 μs, which is converted into a distance resolution of approximately 15 m, which is not practical.

[0074] Therefore, in this embodiment, the resolution is improved by using the MUSIC (Multiple Signal Classification) method. In order to use the MUSIC method, the biometric correlation matrix calculation unit 171 calculates a biometric correlation matrix R of the biometric component transfer function vector obtained by vectorizing the biometric component transfer function matrix. ｆ is calculated according to the following formula 5.

[0075]

[0076] [Distance and angle calculation unit 172] The distance and angle calculation unit 172 calculates the biometric correlation matrix R calculated by the biometric correlation matrix calculation unit 171. ｆIn other words, the distance and angle calculation unit 172 calculates the distance and angle using the biological correlation matrix R ｆ is decomposed into eigenvalues, and a vector U Ｓ and the eigenvector U corresponding to the noise Ｎ Here, the eigenvectors corresponding to the signal are vectors that are ordered from the first eigenvector up to the number of detection targets, and if there is one target, for example, there is only the first eigenvector. Furthermore, if there are k targets (k is a natural number equal to or greater than 2), the eigenvectors corresponding to the signal are k eigenvectors from the first eigenvector to the k-th eigenvector. Furthermore, the eigenvectors corresponding to noise refer to eigenvectors other than the eigenvector corresponding to the signal.

[0077] Using the eigenvectors obtained as described above, the MUSIC spectrum is calculated according to the following equation.

[0078]

[0079] Here, a(l) represents the steering vector and is expressed by Equation 7.

[0080]

[0081] where λ ｉ represents the wavelength of the i-th subcarrier. The MUSIC spectrum P ＭＵＳＩＣ The maximum value of (l) corresponds to the sum (third distance) of the distance a (first distance) between the transmitting antenna unit 100 and the living body 20 and the distance b (second distance) between the receiving antenna unit 130 and the living body 20 in Fig. 6. In this way, the distance angle calculation unit 172 calculates the living body correlation matrix R ｆ A third distance, which is the sum of the first distance between the transmitting antenna unit 100 and the living body 20 and the second distance between the living body 20 and the receiving antenna unit 130, is estimated using the above equation.

[0082] FIG. 6 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 defined by the third distance.

[0083] As shown in FIG. 6, by estimating the third distance, it can be seen that the position of the living body 20 on a plane is limited to the circumference of an ellipse 1010 whose foci are the positions of the transmitting antenna section 100 and the receiving antenna section 130.

[0084] [Operation of Estimation Device 101] The operation of the estimation process of the estimation device 101 configured as above will be described.

[0085] FIG. 7 is a flowchart showing the estimation process of the estimation device 101 according to the embodiment.

[0086] The estimation device 101 calculates a complex transfer function for a first period (S100).

[0087] Next, the estimation apparatus 101 calculates the square value of the amplitude of the complex transfer function (S200).

[0088] Next, the estimation device 101 transforms the squared amplitude into the frequency domain, and extracts from the transformed components components in the positive frequency domain that may include the influence of activity of the living organism 20 (S300).

[0089] Finally, the estimation device 101 estimates the distance of the path from the transmitting antenna unit 100 to the receiving antenna unit 130 via the living body 20 using the MUSIC method, the Capon method, or the like (S400).

[0090] Details of the processing of each step are omitted here because they are included in the description of the configuration of the estimation device 101.

[0091] [Effects, etc.] The estimation device 101 according to this embodiment is an estimation device that estimates the distance to a living body 20, and 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 square value calculation unit 160, and an estimation unit 170. 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 the N receiving antenna elements, including reflected signals resulting from the multicarrier signals transmitted from the M transmitting antenna elements being reflected or scattered by the living body 20. The complex transfer function calculating unit 150 uses the received signals observed by the receiving unit 140 during the first period to calculate, for each of a plurality of subcarriers corresponding to a plurality of subcarriers, a plurality of complex transfer functions each representing a propagation characteristic between the M transmitting antenna elements and the N receiving antenna elements. The square value calculating unit 160 calculates the square value of the amplitude of each of the plurality of complex transfer functions. The estimating unit 170 estimates the distance of the path from the transmitting antenna unit 100 via the living body 20 to the receiving antenna unit 130 based on the square value.

[0092] According to this, the squared value of the amplitude of each of the multiple complex transfer functions is calculated, and based on the squared value, the distance of the path from the transmitting antenna unit 100 through the living body 20 to the receiving antenna unit 130 is estimated, thereby making it possible to estimate the position of the living body 20 with high accuracy.

[0093] In the estimation device 101 according to this embodiment, the estimation unit 170 transforms the squared value into the frequency domain, extracts a component in a specific frequency domain corresponding to the fluctuation component, and estimates the distance based on the component in the specific frequency domain.

[0094] This makes it possible to remove time-invariant components such as direct waves between the transmitting antenna section 100 and the receiving antenna section 130 and reflections from walls, etc., and to estimate the position of the living body 20 with higher accuracy.

[0095] In the estimation device 101 according to this embodiment, the estimation unit 170 converts the squared value into the frequency domain, extracts components in a specific frequency domain derived from the movement of the living body 20, and estimates the distance based on the components in the specific frequency domain.

[0096] Therefore, it is possible to more precisely remove unnecessary received signal components other than breathing or body movement specific to the living body 20, and to estimate the position of the living body 20 with higher accuracy.

[0097] In the estimation device 101 according to this embodiment, the specific frequency region is a component in the positive frequency region.

[0098] Therefore, components that are not caused by the movement of the living body 20 can be removed, and the position of the living body 20 can be measured with higher accuracy.

[0099] In the estimation device 101 according to this embodiment, the estimation unit 170 uses any one of the MUSIC (Multiple Signal Classification) method, the beamformer method, and the Capon method to estimate a first distance from the transmitting antenna unit 100 to the living body 20, a second distance from the living body 20 to the receiving antenna unit 130, a first angle indicating the direction from the transmitting antenna unit 100 to the living body 20, and a second angle indicating the direction from the receiving antenna unit 130 to the living body 20.

[0100] Therefore, by using the MUSIC method, the position of the living body 20 can be estimated with fine distance resolution.

[0101] In this way, according to this embodiment, the position (coordinates) of the living body 20 and the distance between the transmitting antenna unit 100 and the receiving antenna unit 130 and the living body 20 can be estimated using an estimation device using any of the MIMO, MISO, SIMO, and SISO methods.

[0102] As described above, according to the present disclosure, it is possible to realize an estimation device 101 and an estimation method that can estimate the distance and position of a living body using a wireless signal in a short time and with high accuracy.

[0103] While the estimation device and estimation method according to one aspect of the present disclosure have been described above based on the embodiments, 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.

[0104] For example, in the embodiment, distance estimation or position estimation of the living body 20 relative to the estimation device 101 has been described as an example, but the target of estimation is not limited to the living body 20. This estimation is applicable to various moving bodies (machines, etc.) that, when irradiated with a high-frequency signal, exert a Doppler effect on the reflected wave due to their activity.

[0105] Furthermore, the present disclosure can be realized not only as an estimation device having such characteristic components, but also as an estimation method having steps corresponding to the characteristic components included in the estimation device. 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.

[0106] The present disclosure can be used in positioning sensors and distance estimation methods that estimate the distance to a living organism or the position of the living organism using wireless signals, and in particular in distance measurement sensors and direction estimation methods that are installed in measuring instruments that measure the distance to a living organism or the position of the living organism, including between a living organism and a machine, home appliances that perform control according to the distance to a living organism or the position of the living organism, and monitoring devices that detect the intrusion of a living organism.

[0107] 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 160 Square value calculating unit 170 Estimating unit 171 Living body correlation matrix calculating unit 172 Distance angle calculating unit 200, 210 Component 300 Phase gradient of direct wave 310 Phase gradient obtained by positive frequency extraction 800, 810 Phase change with respect to frequency of complex transfer function matrix 900 Time difference after inverse Fourier transform of complex transfer function matrix 910, 920 Phase after inverse Fourier transform of complex transfer function matrix 1010 Ellipse in which a living body may exist, obtained by third distance

Claims

1. An estimation device for estimating the distance from a living body, comprising: a transmission signal generation unit that generates a multi-carrier signal modulated by a plurality of sub-carrier 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 multi-carrier signal and outputs it to the transmission antenna unit to transmit the multi-carrier signal to the transmission antenna unit; a reception antenna unit having N (N is a natural number of 1 or more) reception antenna elements; a reception unit that observes, for a first period corresponding to a period derived from the activity of the living body, a reception signal received by the N reception antenna elements and including a reflection signal in which the multi-carrier signal transmitted from the M transmission antenna elements is reflected or scattered by the living body; a complex transfer function calculation unit that calculates, for each of a plurality of sub-carriers corresponding to the plurality of sub-carrier signals, a plurality of complex transfer functions representing the propagation characteristics between the M transmission antenna elements and the N reception antenna elements using the reception signal observed in the first period in the reception unit; a squared value calculation unit that calculates the squared value of the amplitude of each of the plurality of complex transfer functions; and an estimation unit that estimates the distance of a path from the transmission antenna unit, through the living body, to the reception antenna unit based on the squared value.

2. The estimation device according to claim 1, wherein the estimation unit converts the squared value into a frequency domain, extracts components in a specific frequency domain corresponding to a fluctuation component, and estimates the distance based on the components in the specific frequency domain.

3. The estimation device according to claim 1, wherein the estimation unit converts the squared value into a frequency domain, extracts components in a specific frequency domain derived from the movement of the living body, and estimates the distance based on the components in the specific frequency domain.

4. The estimation device according to claim 2, wherein the specific frequency domain is a component in a positive frequency domain.

5. The estimation device according to claim 3, wherein the specific frequency domain is a component in a positive frequency domain.

6. The estimation unit estimates, using any one of the MUSIC (MUltiple SIgnAl Classification) method, the beamformer method, and the Capon method, a first distance from the transmission antenna unit to the living body and a second distance from the living body to the reception antenna unit as the distances, and a first angle indicating the direction from the transmission antenna unit to the living body and a second angle indicating the direction from the reception antenna unit to the living body. The estimation device according to any one of claims 1 to 5.

7. An estimation method executed by an estimation device for estimating a distance to a living body, the method comprising: generating a multi-carrier signal modulated by a plurality of sub-carrier signals; processing the multi-carrier signal and outputting it to a transmission antenna unit having M (M is a natural number of 1 or more) transmission antenna elements, thereby causing the transmission antenna unit to transmit the multi-carrier signal; observing, for a first period corresponding to a period derived from the activity of the living body, a received signal received by N (N is a natural number of 1 or more) or more constituting a reception antenna unit, the received signal including a reflected signal obtained by reflecting or scattering the multi-carrier signal transmitted from the M transmission antenna elements by the living body; using the received signal observed during the first period, for each of M×N combinations, which are combinations of each of the M transmission antenna elements and the N reception antenna elements, calculating a plurality of complex transfer functions each representing the propagation characteristics between the transmission antenna element and the reception antenna element in the combination, for each of a plurality of sub-carriers corresponding to each of the plurality of sub-carrier signals; calculating a squared value of the amplitude of each of the plurality of complex transfer functions; and estimating the distance of a path from the transmission antenna unit, passing through the living body, to the reception antenna unit based on the squared value. The estimation method.

8. A program for causing a computer to execute the estimation method according to claim 7.

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