Estimation system, estimation method, and program

Abstract

An estimation system (101) comprises Lm transmission devices (102-1 to 102-Lm), Ln reception devices (103-1 to 103-Ln), and a processing unit (191). The Ln reception devices receive a multicarrier signal in a state in which signals are not synchronized with each other. The processing unit calculates biological information on the basis of a plurality of complex transfer functions calculated corresponding to a plurality of combinations of M transmission antenna elements and a total of N reception antenna elements of the Ln reception devices, estimates the position of a living body from a real part component or an imaginary part component of the biological information, and includes a first process for calculating, on the basis of a first matrix relating to the plurality of complex transfer functions corresponding to the plurality of combinations, a correlation matrix representing the correlation between a plurality of elements included in the first matrix, and a second process for extracting a biological component from either the plurality of complex transfer functions or the correlation matrix.

Description

Estimation system, estimation method, and program

[0001] This disclosure relates to an estimation system, estimation method, and program for estimating the orientation or position of a living organism using wireless signals.

[0002] Methods using wireless signals are being considered to determine the location of a person (see, for example, Patent Documents 1 to 5). Patent Documents 1, 2, and 3 disclose a technique for estimating the location and state of a person to be detected by analyzing components including Doppler shift using difference calculations. Patent Documents 4 and 5 disclose a Doppler sensor using OFDM (Orthogonal Frequency Division Multiplexing) signals.

[0003] Japanese Patent Publication No. 2015-117972, Japanese Patent Publication No. 2017-129558, Japanese Patent Publication No. 2018-008021, Japanese Patent Publication No. 2012-088279, Japanese Patent Publication No. 2012-137340

[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] Conventional methods make it difficult to estimate the distance from the estimation system to the living organism, as well as the direction toward the organism, with higher accuracy.

[0006] To achieve the above objective, an estimation device according to one embodiment of the present disclosure is an estimation system for estimating the position of a living organism, the estimation system comprising Lm (where Lm is a natural number of 1 or more) transmitting devices, Ln (where Ln is a natural number of 1 or more) receiving devices, and a processing unit, wherein at least one of Lm and Ln is 2 or more, each of the Lm transmitting devices comprises a transmitting signal generation unit that generates a multicarrier signal in which a plurality of subcarrier signals are modulated, a transmitting antenna unit having one or more transmitting antenna elements, and a transmitting unit that processes the multicarrier signal and outputs it to the transmitting antenna unit, thereby causing the transmitting antenna unit to transmit the multicarrier signal, the Lm transmitting devices have a total of M (where M is a natural number of 1 or more) transmitting antenna elements, each of the Ln receiving devices comprises a receiving antenna unit having one or more receiving antenna elements, and a received signal received by the one or more receiving antenna elements, the received signal including a reflected signal in which the multicarrier signal transmitted from the M transmitting antenna elements is reflected or scattered by the living organism, and the activity of the living organism The system includes a receiving unit that observes for a first period corresponding to a period derived from the above, and a complex transfer function calculation unit that uses the received signal observed in the first period by the receiving unit to calculate a complex transfer function representing the propagation characteristics between the M transmitting antenna elements and the one or more receiving antenna elements, for each of the multiple subcarriers to which the multiple subcarrier signals correspond. The Ln receiving devices receive the multicarrier signal without signal synchronization with each other, and the processing unit calculates biological information based on the multiple complex transfer functions calculated in accordance with a plurality of combinations of the M transmitting antenna elements and the total of N receiving antenna elements of the Ln receiving devices, and estimates the position of the living organism from the real or imaginary component of the biological information. The calculation of the biological information includes a first process of calculating a correlation matrix representing the correlation between a plurality of elements included in the first matrix based on the plurality of complex transfer functions corresponding to the plurality of combinations, and a second process of extracting biological components from either the plurality of complex transfer functions or the correlation matrix.

[0007] These general or specific embodiments may be implemented as devices, methods, integrated circuits, computer programs, or recording media such as computer-readable CD-ROMs, or as any combination of devices, systems, methods, integrated circuits, computer programs, and recording media.

[0008] According to this disclosure, it is possible to estimate the distance from the estimation device to the moving object with higher accuracy.

[0009] Figure 1 is a block diagram showing an example of the configuration of the estimation device in Embodiment 1. Figure 2 is a block diagram showing an example of the configuration of the estimation device in Embodiment 2. Figure 3 is a flowchart showing the estimation process of the estimation systems in Embodiments 1 and 2. Figure 4 is a block diagram showing an example of the configuration of the estimation device in Modification 1. Figure 5 is a block diagram showing an example of the configuration of the estimation device in Modification 2. Figure 6 is a block diagram showing an example of the configuration of the estimation device in Modification 2. Figure 7 is a block diagram showing an example of the configuration of the estimation device in Modification 3. Figure 8 is a block diagram showing an example of the configuration of the estimation device in Modification 3. Figure 9 is a diagram showing the simulation conditions using the estimation method in the embodiment. Figure 10 is a diagram showing the simulation environment using the estimation method in the embodiment. Figure 11 is a diagram showing an example of the positioning results in a simulation using the estimation method in the embodiment. Figure 12 is a diagram showing another simulation result using the estimation method in the embodiment.

[0010] (Knowledge forming the basis of this disclosure) Methods using wireless signals are being considered as a way to determine the location of a person.

[0011] For example, Patent Documents 1 and 2 disclose a method for transmitting a wireless signal to a predetermined area, receiving the reflected wireless signal at the detection target with multiple antennas, and estimating the complex transfer function between the transmitting and receiving antennas. The complex transfer function is a function composed of complex numbers that represent the relationship between input and output, and represents the propagation characteristics between the transmitting and receiving antennas. The number of elements in 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 for estimating the posture of a living organism using RCS (Radar Cross Section) obtained from the received power, using a configuration similar to that of Patent Document 2. RCS is an index that represents the area of ​​an object that reflects the transmitted wave, and the RCS of a living organism changes in various ways depending on the posture of the organism.

[0012] Patent Document 1 further discloses a processing device that can determine the location or state of a person to be detected by analyzing a component containing a Doppler shift using a Fourier transform. More specifically, the processing device records the time evolution of the 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 reflected waves due to biological activities such as breathing and heartbeat. Therefore, the component containing a Doppler shift obtained from the reflected wave includes the influence of the living organism. On the other hand, the component without a Doppler shift obtained from the reflected wave is not influenced by the living organism. In other words, the component without a Doppler shift corresponds to a reflected wave from a fixed object or a direct wave between transmitting and receiving antennas. That is, by using the component included in a predetermined frequency range in the Fourier-transformed waveform, the location or state of the person to be detected can be obtained.

[0013] Patent Document 2 discloses a method for extracting components that include slight Doppler shifts, which are influenced by biological factors, by recording the time evolution of elements of a complex transfer function and analyzing the difference information. In other words, this method allows the location and state of the person to be detected to be determined 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 moving object. Furthermore, Patent Document 4 discloses a high-speed processing method for OFDM Doppler radar that does not require a 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, since the methods described in Patent Documents 1, 2, and 3 transmit unmodulated waves, it is difficult to use commercially available devices, and dedicated hardware is required. In other words, currently available communication devices cannot be used, and users need to install dedicated hardware in addition to their existing communication equipment.

[0017] Furthermore, the methods described in Patent Documents 4 and 5 also require a steep transmission pulse to achieve sufficient accuracy, which necessitates a wide frequency bandwidth. Consequently, the hardware cost is higher compared to consumer-grade communication devices.

[0018] The technology described in Non-Patent Document 1 allows for the estimation of the Time of Flight (ToF) between a transmitting antenna and a receiving antenna, or the distance that can be calculated from ToF, by transmitting and receiving signals of multiple frequencies using a measuring instrument such as a network analyzer. This utilizes the property that, similar to ranging sensors using FMCW (Frequency Modulated Continuous Wave) radar, when two signals of different frequencies are transmitted in 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 in Non-Patent Document 1 further improves the 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. Furthermore, it can only estimate the distance between antennas, making it difficult to estimate the distance between a device and, for example, a living organism without special equipment.

[0020] Therefore, the inventors have come up with estimation devices that can estimate the position of living organisms with higher accuracy.

[0021] In other words, the estimation system according to the first aspect of the present disclosure is an estimation system for estimating the position of a living organism, the estimation system comprising Lm (where Lm is a natural number of 1 or more) transmitting devices, Ln (where Ln is a natural number of 1 or more) receiving devices, and a processing unit, wherein at least one of Lm and Ln is 2 or more, each of the Lm transmitting devices comprises a transmitting signal generation unit that generates a multicarrier signal in which a plurality of subcarrier signals are modulated, a transmitting antenna unit having one or more transmitting antenna elements, and a transmitting unit that processes the multicarrier signal and outputs it to the transmitting antenna unit, thereby causing the transmitting antenna unit to transmit the multicarrier signal, the Lm transmitting devices have a total of M (where M is a natural number of 1 or more) transmitting antenna elements, each of the Ln receiving devices comprises a receiving antenna unit having one or more receiving antenna elements, and a received signal received by the one or more receiving antenna elements, which includes a reflected signal in which the multicarrier signal transmitted from the M transmitting antenna elements is reflected or scattered by the living organism, based on the activity of the living organism The system includes a receiving unit that observes for a first period corresponding to the coming cycle, and a complex transfer function calculation unit that uses the received signal observed in the first period by the receiving unit to calculate a complex transfer function representing the propagation characteristics between the M transmitting antenna elements and one or more receiving antenna elements, for each of the multiple subcarriers to which the multiple subcarrier signals correspond. The Ln receiving devices receive the multicarrier signal without signal synchronization with each other, and the processing unit calculates biological information based on the multiple complex transfer functions calculated in relation to a plurality of combinations of the M transmitting antenna elements and the total of N receiving antenna elements of the Ln receiving devices, and estimates the position of the living organism from the real or imaginary component of the biological information. The calculation of the biological information includes a first process of calculating a correlation matrix representing the correlation between a plurality of elements included in a first matrix based on the plurality of complex transfer functions corresponding to the plurality of combinations, and a second process of extracting biological components from either the plurality of complex transfer functions or the correlation matrix.

[0022] According to this, in a configuration where Lm transmitting devices and Ln receiving devices have a total of M transmitting antenna elements and N receiving antenna elements, a plurality of complex transfer functions calculated for each of a plurality of subcarriers can be collectively handled as a first matrix, and biological information used for estimating the position of a living body can be calculated based on the propagation characteristics of the entire device. Also, for a plurality of complex transfer functions obtained from a plurality of receiving devices for which signal synchronization is not taken, a correlation matrix representing the correlation between a plurality of elements included in the first matrix is calculated, and by extracting a biological component from this correlation matrix or the plurality of complex transfer functions, information resulting from the presence of a living body can be taken out as biological information. Furthermore, in order to estimate the position of a living body using the real part component or the imaginary part component of the biological information, a component useful for estimating the position of a living body among the information regarding the propagation characteristics included in the complex transfer function can be utilized, and the position of a living body can be estimated with high accuracy in an estimation system including Lm transmitting devices and Ln receiving devices.

[0023] Also, with this configuration, it is possible to realize a biological radar that measures the position of a living body by diverting an existing communication device that uses a multi-carrier signal such as OFDM for the transmission signal. For example, receivers for multi-carrier signals such as OFDM have already become widespread as mobile phones, television broadcast receivers, household appliances, and wireless LAN devices, etc., and it is possible to realize a biological radar that measures the position of a living body at a lower cost than in the case of using an unmodulated signal.

[0024] The estimation system according to the second aspect of the present disclosure is the estimation system according to the first aspect, wherein the first matrix is a matrix including the plurality of complex transfer functions as elements, and the second process is a process of extracting a biological component from the correlation matrix.

[0025] According to this, the first matrix is configured as a matrix including a plurality of complex transfer functions as elements, and biometric information in which a biological component is extracted from a correlation matrix calculated based on the first matrix can be obtained. Thereby, the relationship between the complex transfer functions obtained for each of a plurality of combinations of the transmission device and the reception device is generated as a correlation matrix, and by selectively extracting the components related to the living body included in the correlation, information useful for estimating the position of the living body can be efficiently utilized.

[0026] The estimation system according to the third aspect of the present disclosure is the estimation system according to the first aspect, wherein the second process is a process of extracting a biological component from the plurality of complex transfer functions, and the first matrix is a matrix including the result of the second process as an element.

[0027] According to this, a biological component can be extracted from a plurality of complex transfer functions first, and a first matrix including the result as an element can be obtained. Thereby, a correlation matrix can be calculated for the first matrix including the biological component as an element, and biological information focusing on the relationship between living bodies can be obtained and used for position estimation. Therefore, the position of the living body can be estimated in a form that is less affected by components other than the living body. The estimation system according to the fourth aspect of the present disclosure is the estimation system according to any one of the first aspect to the third aspect, wherein the second process is a process of converting either the plurality of complex transfer functions or the correlation matrix into a frequency domain and extracting only components in a specific frequency domain derived from the movement of the living body.

[0028] According to this, in the second process, either the plurality of complex transfer functions or the correlation matrix is converted into a frequency domain, and after extracting components in a specific frequency domain derived from the movement of the living body, a biological component can be obtained. Thereby, biological information focusing on the periodic component corresponding to the movement of the living body can be obtained, and the position of the living body can be estimated by mainly using the components contributing to the estimation of the living body position among the temporal variations.

[0029] The estimation system according to the fifth aspect of the present disclosure is the estimation system according to the fourth aspect, wherein the specific frequency domain is a positive frequency domain.

[0030] According to this approach, by defining a specific frequency range as the positive frequency range, components originating from biological movements expressed in the frequency range can be unified and handled on the positive frequency side. This clarifies the range of frequency components used as biological information, and allows the process of estimating the position of a living organism based on the results of frequency analysis to be performed under simple and consistent conditions.

[0031] An estimation system according to a sixth aspect of this disclosure is an estimation system according to any one aspect of the first to fifth aspects, wherein the processing unit estimates the position of the living organism using either the MUSIC (Multiple Signal Classification) method or the Capon method for the real component or the imaginary component.

[0032] According to this method, position estimation can be performed on either the MUSIC method or the Capon method using either the real or imaginary component of biological information. This allows for the application of computational processing known as a high-resolution direction-of-arrival estimation method to the biological information obtained from the first matrix and correlation matrix, enabling the estimation of the biological position with detailed spatial resolution based on propagation characteristics obtained from Lm transmitters and Ln receivers.

[0033] An estimation system according to a seventh aspect of the present disclosure is an estimation system according to any one aspect of the first to sixth aspects, wherein Lm and Ln are 2 or more and are equal to each other, and the estimation system comprises Lm transceivers, each of the Lm transceivers comprising a transmitting device from among the Lm transmitting devices corresponding to the transceiver and a receiving device from among the Ln receiving devices corresponding to the transceiver.

[0034] According to this, if the number of transmitting devices and receiving devices are made equal, and an estimation system is established in which each transmitting and receiving device is associated with a one-to-one correspondence, then a complex transfer function corresponding to the transmission and reception paths for each transmitting and receiving device can be obtained. Therefore, based on the complex transfer function associated with each transmitting and receiving device, biological information can be calculated and biological location can be estimated, and biological location estimation processing using Lm transmitting and receiving devices can be performed based on an easily understandable correspondence.

[0035] The estimation system according to the eighth aspect of this disclosure is the estimation system according to the seventh aspect, wherein each of the Lm transceivers obtains a complex transfer function from any of the Lm transceivers by MAC address.

[0036] According to this method, the complex transfer function corresponding to any transceiver from among Lm transceivers can be obtained using the MAC address assigned to each transceiver. This allows for flexible selection of a combination of transceivers to be used for biological position estimation from among multiple transceivers connected to the network, and the selection result can be reflected in the calculation of the complex transfer function and biological information.

[0037] An estimation system according to the ninth aspect of this disclosure is an estimation system according to the seventh aspect, wherein each of the Lm transmitting and receiving devices acquires a plurality of data in the time direction and synchronizes signals between the Lm transmitting and receiving devices using at least one of the mean, median, moving mean, and moving median.

[0038] According to this method, by processing multiple data acquired by each transmitting and receiving device in the time direction using at least one of the mean, median, moving mean, and moving median, the signal discrepancy occurring between Lm transmitting and receiving devices can be reduced. As a result, the first matrix and correlation matrix can be obtained with reduced variability in the complex transfer function obtained between transmitting and receiving devices, thereby reducing the variability in estimated biological positions based on biological information and improving the accuracy of biological position estimation to a higher level.

[0039] An estimation method according to a tenth aspect of the present disclosure is an estimation method performed by an estimation system for estimating the position of a living organism, wherein the estimation system comprises Lm (where Lm is a natural number of 1 or more) transmitting devices and Ln (where Ln is a natural number of 1 or more) receiving devices, wherein at least one of Lm and Ln is 2 or more, and each of the Lm transmitting devices comprises a transmitting signal generation unit that generates a multicarrier signal in which a plurality of subcarrier signals are modulated, a transmitting antenna unit having one or more transmitting antenna elements, and a transmitting unit that processes the multicarrier signal and outputs it to the transmitting antenna unit, thereby causing the transmitting antenna unit to transmit the multicarrier signal, wherein the Lm transmitting devices have a total of M (where M is a natural number of 1 or more) transmitting antenna elements, and each of the Ln receiving devices comprises a receiving antenna unit having one or more receiving antenna elements, and a received signal received by the one or more receiving antenna elements, which includes a reflected signal in which the multicarrier signal transmitted from the M transmitting antenna elements is reflected or scattered by the living organism, depending on the activity of the living organism The system includes a receiving unit that observes for a first period corresponding to the coming cycle, and a complex transfer function calculation unit that uses the received signal observed in the first period by the receiving unit to calculate a complex transfer function representing the propagation characteristics between the M transmitting antenna elements and the one or more receiving antenna elements, for each of the multiple subcarriers to which the multiple subcarrier signals correspond. The Ln receiving devices receive the multicarrier signal without signal synchronization with each other. The estimation method calculates biological information based on the multiple complex transfer functions calculated in relation to a plurality of combinations of the M transmitting antenna elements and the total of N receiving antenna elements of the Ln receiving devices, and estimates the position of the living organism from the real or imaginary component of the biological information. The calculation of the biological information includes a first process of calculating a correlation matrix representing the correlation between a plurality of elements included in the first matrix based on the plurality of complex transfer functions corresponding to the plurality of combinations, and a second process of extracting biological components from either the plurality of complex transfer functions or the correlation matrix.

[0040] According to this, in a configuration where Lm transmitters and Ln receivers have a total of M transmitting antenna elements and N receiving antenna elements, multiple complex transfer functions calculated for each of the multiple subcarriers can be treated together as a first matrix, and biological information used for estimating the position of a living organism can be calculated based on the propagation characteristics of the entire device. Furthermore, for multiple complex transfer functions obtained from multiple receivers that are not signal-synchronized, a correlation matrix representing the correlation between multiple elements included in the first matrix can be calculated, and by extracting biological components from this correlation matrix or the multiple complex transfer functions, information attributable to the presence of a living organism can be extracted as biological information. Moreover, since the position of the living organism is estimated using the real or imaginary component of the biological information, components of the propagation characteristic information included in the complex transfer function that are useful for estimating the position of the living organism can be utilized, and the position of the living organism can be estimated with high accuracy in an estimation system equipped with Lm transmitters and Ln receivers.

[0041] The program relating to the eleventh aspect of this disclosure is a program for causing a computer to execute the estimation method relating to the tenth aspect.

[0042] These comprehensive or specific embodiments may be implemented as a system, integrated circuit, computer program, or recording medium such as a computer-readable CD-ROM, or as any combination of apparatus, system, method, integrated circuit, computer program, and recording medium.

[0043] The embodiments of this disclosure will be described in detail below with reference to the drawings. The embodiments described below are all preferred examples of the disclosure. The numerical values, shapes, materials, components, arrangement and connection configurations of components, steps, and the order of steps shown in the following embodiments are examples only and are not intended to limit the disclosure. Furthermore, components in the following embodiments that are not described in the independent claims representing the highest-level concepts of this disclosure will be described as any component constituting a more preferred configuration. In this specification and in the drawings, components having substantially the same functional configuration are denoted by the same reference numerals to avoid redundant explanation.

[0044] (Embodiment 1) Embodiment 1 describes a method for detecting living organisms when multiple transmitting and receiving devices, or both, are arranged in 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 MIMO systems, in which both the transmitting and receiving antenna units have multiple antenna elements, or to SIMO or MISO systems, in which one of the transmitting and receiving antenna units has a single antenna element, by extracting elements from all sets of transmitting and receiving antennas or a specific set of transmitting and receiving antennas and performing the same processing as the SISO system.

[0045] [Configuration of Estimation System 101] Figure 1 is a block diagram showing an example of the configuration of the estimation system in Embodiment 1.

[0046] The estimation system 101 shown in Figure 1 comprises Lm transmitting devices 102-1 to 102-Lm, Ln receiving devices 103-1 to 103-Ln, and an estimation unit 190. Here, Lm is a natural number greater than or equal to 1, and Ln is a natural number greater than or equal to 1.

[0047] Lm transmitting devices 102-1 to 102-Lm each comprise a transmitting antenna section 100-1 to 100-Lm, a transmitting section 110-1 to 110-Lm, and a transmitting signal generation section 120-1 to 120-Lm. For example, transmitting device 102-k comprises a transmitting antenna section 100-k, a transmitting section 110-k, and a transmitting signal generation section 120-k, where k is one of 1 to Lm. Thus, each transmitting device comprises a transmitting antenna section, a transmitting section, and a transmitting signal generation section. The functions realized by the transmitting antenna section, transmitting section, and transmitting signal generation section of each transmitting device are common among the Lm transmitting devices 102-1 to 102-Lm; therefore, the components of one transmitting device will be described as representative below.

[0048] Furthermore, Ln receiving devices 103-1 to 103-Ln each comprise a receiving antenna section 130-1 to 130-Ln, a receiving section 140-1 to 140-Ln, a complex transfer function calculation section 141-1 to 141-Ln, a correlation matrix calculation section 150-1 to 150-Ln, and a bio-information calculation section 180-1 to 180-Ln. For example, receiving device 103-l comprises a receiving antenna section 130-l, a receiving section 140-l, a complex transfer function calculation section 141-l, a correlation matrix calculation section 150-l, and a bio-information calculation section 180-l. Here, l is one of 1 to Ln. Thus, each receiving device comprises a receiving antenna section, a receiving section, a complex transfer function calculation section, a correlation matrix calculation section, and a bio-information calculation section. Furthermore, since the functions realized by the receiving antenna section, receiving section, complex transfer function calculation section, correlation matrix calculation section, and biometric information calculation section of each receiving device are common among Ln transmitting devices 102-1 to 102-Ln, the following description will represent the components of one receiving device. Note that the correlation matrix calculation sections 150-1 to 150-Ln, the biometric information calculation sections 180-1 to 180-Ln, and the estimation section 190 may function as a processing section 191.

[0049] In this embodiment, unless otherwise specified, the same reference numerals are used for other components, and the same correspondence is assumed.

[0050] The estimation system 101 estimates one of the following: the distance to the living organism 20, the direction to the living organism 20, or the position of the living organism 20. The estimation system 101 may also estimate the position of the living organism 20 in the target space, estimate the posture of the living organism 20, determine whether or not the living organism 20 exists in the target space, identify the living organism 20 based on pre-registered information (complex transfer function matrix) for each individual living organism 20, or estimate the movement of the living organism 20. In other words, the estimation system 101 performs processing (estimation processing) on ​​the target of estimation, such as position, posture, existence, identification, and movement, with respect to the living organism 20.

[0051] [Transmitting Antenna Unit 100-k] The transmitting antenna unit 100-k has one or more transmitting antenna elements. The Lm transmitting antenna units 100-1 to 100-Lm have a total of M transmitting antenna elements. In other words, the Lm transmitting devices have a total of M transmitting antenna elements (M is a natural number of 1 or more). Here, M is a natural number of 1 or more. As described above, the transmitting antenna elements transmit the multi-carrier signal (transmitted wave) generated by the transmitting unit 110-k corresponding to the transmitting antenna element.

[0052] [Transmitting Unit 110-k] The transmitting unit 110-k applies appropriate processing to the signal generated by the transmitting signal generation unit 120-k to generate a transmission wave. Processing performed here includes, for example, upconversion, which converts the signal from the IF (Intermediate Frequency) frequency band to the RF (Radio Frequency) frequency band, and amplification, which amplifies the signal to an appropriate transmission level. The transmitting unit 110-k outputs the processed multi-carrier signal to the transmitting antenna unit 100-k, causing the transmitting antenna unit 100-k to transmit the multi-carrier signal. As a result, the multi-carrier signal is transmitted from one or more transmitting antenna elements provided by the transmitting antenna unit 100-k.

[0053] [Transmission Signal Generation Unit 120-k] The transmission signal generation unit 120-k generates a multicarrier signal in which multiple subcarrier signals are modulated. Specifically, it generates multiple subcarrier signals corresponding to multiple subcarriers in different frequency bands, and generates a multicarrier signal by multiplexing the generated multiple subcarrier signals. In this embodiment, the transmission signal generation unit 120-k will be described as generating an OFDM signal consisting of S subcarriers, which has high frequency band utilization efficiency, as the multicarrier signal. Note that the transmission signal generation unit 120-k is not limited to generating an OFDM signal in which each subcarrier is orthogonal, as long as it is a multicarrier signal obtained by multicarrier modulation, it may also generate other multicarrier signals such as a simple FDM (Frequency Division Multiplexing) signal.

[0054] Furthermore, the signal generated by the transmission signal generation unit 120-k may be shared with signals used for communication such as wireless LAN. In other words, the transmission signal used to sense the biological organism 20 may be used exclusively for sensing the biological organism 20, or it may be used for both sensing the biological organism 20 and information communication.

[0055] [Receiving Antenna Unit 130-k] The receiving antenna unit 130-k has one or more receiving antenna elements. The Ln receiving antenna units 130-1 to 130-Ln have a total of N receiving antenna elements. Each of the n receiving antenna units 130 from receiving antenna unit 130-1 to receiving antenna unit 130-Ln has at least one receiving antenna element. Here, N is a natural number of 1 or more. The N receiving antenna elements receive signals (received signals) transmitted from the M transmitting antenna elements and reflected by the living organism 20.

[0056] [Receiver 140-k] The receiver 140-k observes the received signal, which is received by one or more receiving antenna elements of the receiver 140-k and includes reflected signals, which are multi-carrier signals transmitted from M transmitting antenna elements that have been reflected or scattered by the living organism 20, for a first period corresponding to a period derived from the activity of the living organism 20. The period derived from the activity of the living organism is a living organism-derived period (living organism fluctuation period) that is half a period or longer of any of the periods of respiration, heartbeat, or body movement of the living organism 20.

[0057] The receiving unit 140-k converts the high-frequency signal received by one or more receiving antenna elements of the receiving unit 140-k into a low-frequency signal that can be processed. The receiving unit 140-k then demodulates the low-frequency signal into an OFDM signal, which is then demodulated into a signal (IQ symbol) of S subcarriers.

[0058] Furthermore, the receiving unit 140-k outputs all or part of the S subcarrier signals (IQ symbols) corresponding to each combination of M transmitting antenna elements and one or more receiving antenna elements of the receiving unit 140-k to the complex transfer function calculation unit 141-k. Based on this output, the complex transfer function calculation unit 141-k calculates a complex transfer function representing the propagation characteristics between the M transmitting antenna elements and each receiving antenna element of the receiving unit 140-k for each of the multiple subcarriers.

[0059] The receiving unit 140-k may continuously observe the received signal received by the receiving antenna unit 130-k, or it may continuously transmit S low-frequency signals (IQ symbols) at regular intervals.

[0060] Furthermore, the signals from the N receiving antenna elements of the Ln receiving antenna units 130-1 to 130-Ln may each contain different phase rotation noise.

[0061] [Complex Transfer Function Calculation Unit 141-k] The complex transfer function calculation unit 141-k calculates a complex transfer function using a plurality of received signals observed in the first period by the corresponding receiving unit 140-k. Specifically, for each of the plurality of combinations, which are combinations of each of the M transmitting antenna elements and each of the one or more receiving antenna elements of the receiving unit 140-k, the complex transfer function calculation unit 141-k may calculate a complex transfer function representing the propagation characteristics between the transmitting antenna element and the receiving antenna element in that combination, for each of the plurality of subcarriers to which each of the plurality of subcarrier signals corresponds, or it may calculate only one or more of the plurality of combinations. Note that the plurality of combinations are all possible combinations when the M transmitting antenna elements and one or more receiving antenna elements are combined one-to-one. The complex transfer functions calculated by the complex transfer function calculation units 141-k provided in each of the multiple receiving devices are aggregated in the subsequent processing unit 191 within the estimation system 101 and used as a set of complex transfer functions corresponding to the combination of M transmitting antenna elements and a total of N receiving antenna elements. In other words, the multiple complex transfer functions calculated by the complex transfer function calculation units 141-1 to 141-Ln are shared among the Ln receiving devices 103-1 to 103-Ln.

[0062] Thus, the multiple complex transfer functions calculated by the complex transfer function calculation units 141-1 to 141-Ln, each provided in the multiple receiving devices 103-1 to 103-Ln, are aggregated in the subsequent processing unit 191 within the estimation system 101 and treated as a complex transfer function matrix containing multiple complex transfer functions as elements, corresponding to combinations of M transmitting antenna elements and a total of N receiving antenna elements. The calculated complex transfer function matrix includes components corresponding to reflected signals received via the living organism 20, as well as components resulting from paths that do not pass through the living organism 20, such as components corresponding to the direct wave from the transmitting antenna element to the receiving antenna element and components corresponding to reflected waves reflected by fixed objects other than the living organism 20.

[0063] The complex transfer function calculation unit 141-k may sequentially calculate the complex transfer function vector at predetermined time intervals using each of the multiple subcarrier signals (IQ symbols) that are constantly output from the corresponding receiving unit 140-k or output at regular intervals, or it may calculate the complex transfer function vector continuously. By configuring the system to continuously calculate the complex transfer function vector in this way, if the estimation system 101 shares hardware with a communication device such as a wireless LAN device, the complex transfer function vector that is constantly calculated on the communication device side for communication processing can be commonly used in the estimation process used for estimating the position of the living organism 20.

[0064] In this embodiment, the complex transfer function calculation unit 141-k calculates a complex transfer function vector h(t) representing the propagation characteristics between the transmitting antenna element and each receiving antenna element of the receiving unit 140-k during an observation time t, based on S IQ symbols transmitted from the corresponding receiving unit 140-k, according to (Equation 1). If there are multiple receiving devices 103-1 to 103-Ln, a complex transfer function vector h(t) is obtained for each receiving device, and these complex transfer function vectors are aggregated in a subsequent process to be used as multiple complex transfer functions corresponding to a total of N receiving antenna elements.

[0065]

[0066] [Correlation Matrix Calculation Unit 150-k] The correlation matrix calculation unit 150-k receives the complex transfer function vector h(t) calculated by the corresponding complex transfer function calculation unit 141-k as input, and calculates a correlation matrix of complex transfer functions based on a complex transfer function matrix that includes the complex transfer functions corresponding to each combination of M transmitting antenna elements and a total of N receiving antenna elements, and calculates the diagonal terms of the correlation matrix.

[0067] The calculation of the diagonal terms of the correlation matrix will be explained in detail using mathematical formulas below. Among the complex transfer function vector h(t), the element corresponding to the subcarrier s is h ｓThis is expressed as follows. The propagation characteristics between one transmitting antenna unit out of Lm transmitting antenna units 100-1 to 100-Lm and one receiving antenna unit out of Ln receiving antenna units 130-1 to 130-Ln are decomposed as a function of time t, as shown in (Equation 2). Here, we focus on the direct wave component that does not pass through the living organism 20 between one transmitting antenna unit and one receiving antenna unit, the reflected component received by one receiving antenna unit after the signal transmitted from one transmitting antenna unit is reflected by the living organism 20, and the influence of random phase errors caused by clock discrepancies between the transmitting and receiving devices.

[0068]

[0069] Here, h ｓｄ This represents the direct wave component corresponding to the propagation path between one transmitting antenna unit and one receiving antenna unit that does not pass through the living organism 20, and h ｓｖ This represents the component corresponding to the propagation path in which a signal transmitted from one transmitting antenna unit is reflected by the living organism 20 and received by one receiving antenna unit 130. ｅ (t) represents a random phase error that fluctuates over time due to clock misalignment between the transmitting and receiving devices. Here, i is the imaginary unit.

[0070] Next, the vector r, which consists of the diagonal terms of the correlation matrix for the complex transfer function vector h(t), can be expressed as shown in (Equation 3).

[0071]

[0072] Here, * represents the complex conjugate. Here, each vector and matrix from (Equation 1) to (Equation 3) has components in the direction of the antenna elements according to the total number of N receiving antenna elements and M transmitting antenna elements. However, in the following explanation, we will focus on the component corresponding to the propagation characteristics from the m-th transmitting antenna element to the n-th receiving antenna element. In this case, considering the s-th element of (Equation 3), the effect of random phase errors is removed by the autocorrelation calculation as shown in (Equation 4).

[0073]

[0074] Also, h ｓｎｍ These are the components of the complex transfer function vector corresponding to the subcarrier s, the transmitting antenna element m, and the receiving antenna element n. ｓｎｍｄ These are the components of the direct wave between the transmitting antenna section and the receiving antenna section that do not pass through the living organism 20, and which correspond to the subcarrier s, the transmitting antenna element m, and the receiving antenna element n. ｓｎｍｖ These are components of the propagation path that are reflected from the transmitting antenna section by the living organism 20 and received by the receiving antenna section, and correspond to the subcarrier s, transmitting antenna element m, and receiving antenna element n.

[0075] [Biological Information Calculation Unit 180-k] The biological information calculation unit 180-k receives the diagonal term r of the correlation matrix of the complex transfer function calculated by the correlation matrix calculation unit 150-k as input, and for each of the multiple subcarriers, it sequentially records the diagonal term r of the correlation matrix over the first period in the order in which the multiple received signals were observed. Then, for each of the multiple subcarriers, the biological information calculation unit 180-k extracts the components related to the biological organism 20 based on the diagonal term r of the correlation matrix that has been sequentially recorded in the time series, and calculates a biological component transfer function vector represented by an S × N × M dimension matrix for each of the multiple subcarriers.

[0076] Here, the biocomponent transfer function vector is a complex transfer function obtained by extracting and representing the component that has passed through the biological body 20 from the reflected or scattered waves contained in the received signal. To determine the biocomponent, as described above, the diagonal term r of the correlation matrix recorded in time series can be used, for example, by applying a Fourier transform or by using difference information in the time series. Specific examples of these processes are disclosed in Patent Document 1 as a method using a Fourier transform and in Patent Document 2 as a method using difference information.

[0077] For example, in the method using Fourier transform, for the time-series data of the diagonal term r of the correlation matrix, Fourier transform is performed in the observation time direction (slow time direction), and frequency components included in the frequency band that may include the influence of the activity of the living body 20 are selectively extracted. As an example of the frequency band that may include the influence of the activity of the living body 20, for example, a plurality of frequency components included in the range of 0.1 Hz or more and 3 Hz or less can be mentioned. At this time, for each of these plurality of frequency components, as shown in (Equation 5), the biological component transfer function rsnm(ω) can be calculated.

[0078]

[0079] Here, ω is the biological activity frequency to be extracted, and F[·] represents Fourier transform. The component passing through the living body 20 appears corresponding to the component h ｓｎｍｖ (t) that varies depending on the movement of the living body 20 among the plurality of transfer functions shown in (Equation 4). Therefore, by applying Fourier transform to the time series of the diagonal term r of the correlation matrix and selectively extracting the frequency components corresponding to the biological activity frequency band, the component caused by h ｓｎｍｖ (t) can be taken out. As a result, among the components included in the right side of (Equation 4), the biological component transfer function r ｓｎｍ (ω) that reflects the components corresponding to the second and third terms related to the activity of the living body 20 is obtained.

[0080] [Estimation Unit 190] The estimation unit 190 estimates information such as the position of the living organism 20, the distance to the living organism 20, and the angle (direction) to the living organism, based on the biological component transfer functions calculated by Ln biological information calculation units 180-1 to 180-Ln. By using the biological component transfer functions calculated by the biological information calculation unit 180-k for each combination of transmitting antenna elements and receiving antenna elements, the biological component transfer function matrix corresponding to all transmitting and receiving antenna elements in the s-th subcarrier can be represented as a matrix as shown in (Equation 6). This biological component transfer function matrix is ​​a matrix that includes the biological component transfer function rsnm(ω) obtained for each combination of transmitting antenna element m and receiving antenna element n as elements, and expresses the propagation characteristics related to the living organism 20 in a way that reflects the spatial arrangement relationship between the transmitting antenna elements and receiving antenna elements.

[0081]

[0082] The estimation unit 190 rearranges the biocomponent transfer function matrix in the s-th subcarrier shown in (Equation 6) along the combination direction of the transmitting antenna elements and receiving antenna elements to convert it into the biocomponent transfer function vector shown in (Equation 7). This makes it possible to treat the biocomponent transfer function corresponding to the combination of M transmitting antenna elements and a total of N receiving antenna elements in the s-th subcarrier as a single N × M dimension vector, facilitating subsequent calculations of the correlation matrix and spatial spectrum.

[0083]

[0084] Furthermore, the estimation unit 190 obtains a biocomponent transfer function vector corresponding to (Equation 7) for all subcarriers and connects them in the subcarrier direction to form the biocomponent transfer function vector shown in (Equation 8). This biocomponent transfer function vector is an S × N × M dimension vector that includes components corresponding to multiple subcarriers, all transmitting antenna elements, and all receiving antenna elements, and simultaneously represents frequency and spatial information related to the living organism 20.

[0085]

[0086] The estimation unit 190 calculates a correlation matrix of the biocomponent transfer function as shown in (Equation 9) based on the biocomponent transfer function vector shown in (Equation 8), and performs eigenvalue decomposition on this correlation matrix. The correlation matrix is ​​a matrix that represents the autocorrelation of the biocomponent transfer function vector, and it represents the energy distribution of the component corresponding to the reflected component from the biological body 20 and the noise component in matrix form.

[0087]

[0088] Here, E[•] represents the average in the frequency ω direction, U is a matrix containing the eigenvectors of the correlation matrix as elements, and Λ is a diagonal matrix containing the corresponding eigenvalues ​​as diagonal terms. The estimation unit 190 separates the signal space and the noise space based on the magnitude of the eigenvalues ​​of the correlation matrix, and obtains the noise space eigenvector matrix U from the eigenvectors corresponding to the noise space. Ｎ The following are extracted. Then, as an example of an incoming wave direction estimation method, the MUSIC (Multiple Signal Classification) method is applied, and the spatial spectrum corresponding to the candidate position of the living organism 20 is calculated as shown in (Equation 10). Note that instead of the MUSIC method, the Capon method or other spatial spectrum estimation methods may be used as the incoming wave direction estimation method.

[0089]

[0090] Here U Ｎ A is a matrix containing noise space eigenvectors as elements, and a(x, y, z) is a steering vector that represents the positional relationship of the signals arriving at each transmitting antenna element and each receiving antenna element from an arbitrary position (x, y, z) in space, assuming that a living organism 20 exists at that position. The steering vector a(x, y, z) is defined based on the positional information of the transmitting antenna elements and receiving antenna elements and the wavelength of the subcarrier, as shown in (Equation 11).

[0091]

[0092] Here, x is the arbitrary x-coordinate to be estimated, y is the y-coordinate of the position, and z is the z-coordinate of the position. ｍ is the x-coordinate of the m-th transmitting antenna element, and yｍ is the y-coordinate of the m-th transmitting antenna element, and z ｍ x is the z-coordinate of the m-th transmitting antenna element. ｎ is the x-coordinate of the nth receiving antenna element, and y ｎ is the y-coordinate of the nth receiving antenna element, and z ｎ λ is the z-coordinate of the nth receiving antenna element. ｓ is the wavelength of the s-th subcarrier, and d ｎｍ is the distance between the m-th transmitting antenna element and the n-th receiving antenna element. By rearranging the steering vectors defined based on these parameters along the combination direction of the transmitting and receiving antenna elements, the steering vector corresponding to the s-th subcarrier can be expressed as a vector, as shown in (Equation 12).

[0093]

[0094] Furthermore, by determining steering vectors corresponding to (Equation 12) for all subcarriers and connecting them in the subcarrier direction, the steering vector shown in (Equation 13) can be obtained. This steering vector includes elements corresponding to multiple subcarriers, all transmitting antenna elements, and all receiving antenna elements, and represents the theoretical pattern of propagation characteristics that can be observed when it is assumed that a living organism 20 is present at the estimated target position (x, y, z).

[0095]

[0096] As described above, the estimation unit 190 substitutes the steering vector shown in (Equation 13) into (Equation 10) and calculates the spatial spectrum value for each position (x, y, z) in the estimation target space. Then, by searching for the position where there is a peak in the distribution of the obtained spatial spectrum, the location where the living organism 20 is estimated to be present can be determined. Furthermore, based on the estimated position information and the arrangement information of the transmitting antenna element and the receiving antenna element, the distance and direction to the living organism 20 can be calculated.

[0097] [Effects, etc.] The estimation system 101 of this embodiment comprises Lm (where Lm is a natural number of 1 or more) transmitting devices 102-1 to 102 to Lm, Ln (where Ln is a natural number of 1 or more) receiving devices 103-1 to 103-Ln, and a processing unit 191. At least one of Lm and Ln is 2 or more. Transmitting device 102-k, one of the Lm transmitting devices 102-1 to 102 to Lm, comprises a transmitting signal generation unit 120-k, a transmitting antenna unit 100-k, and a transmitting unit 110-k. The transmitting signal generation unit 120-k generates a multicarrier signal in which multiple subcarrier signals are modulated. The transmitting antenna unit 100-k has one or more transmitting antenna elements. The transmitting unit 110-k processes the multicarrier signal and outputs it to the transmitting antenna unit 100-k, thereby causing the transmitting antenna unit 100-k to transmit the multicarrier signal. Lm transmitting devices 102-1 to 102 to Lm have a total of M transmitting antenna elements (where M is a natural number greater than or equal to 1). Receiving device 103-k, one of the Ln receiving devices 103-1 to 103-Ln, comprises a receiving antenna unit 130-k, a receiving unit 140-k, a complex transfer function calculation unit 141-k, a correlation matrix calculation unit 150-k, and a biological information calculation unit 180-k. The receiving antenna unit 130-k has one or more receiving antenna elements. The receiving unit 140-k observes the received signal received by one or more receiving antenna elements, which includes reflected signals obtained by reflecting or scattering multicarrier signals transmitted from M transmitting antenna elements by the living organism 20, for a first period corresponding to a period derived from the activity of the living organism 20. The complex transfer function calculation unit 141-k calculates multiple complex transfer functions representing the propagation characteristics between M transmitting antenna elements and one or more receiving antenna elements, using the received signals observed in the first period by the receiving unit 140-k, for each of the multiple subcarriers that each of the multiple subcarrier signals corresponds to. The Ln receiving devices 103-1 to 103-Ln receive the multicarrier signal without signal synchronization with each other. The processing unit 191 calculates biological information based on the multiple complex transfer functions calculated for multiple combinations of the M transmitting antenna elements and the total of N receiving antenna elements possessed by the Ln receiving devices 103-1 to 103-Ln.The processing unit 191 estimates the position of the living organism 20 from the real or imaginary component of the biological information. The calculation of biological information in the processing unit 191 includes a first process and a second process. The first process is to calculate a correlation matrix representing the correlation between multiple elements included in a first matrix, based on a first matrix relating to multiple complex transfer functions corresponding to multiple combinations. The second process is to extract the biological component from either the multiple complex transfer functions or the correlation matrix.

[0098] According to this, in a configuration in which Lm transmitting devices 102-1 to 102-Lm and Ln receiving devices 103-1 to 103-Ln have a total of M transmitting antenna elements and N receiving antenna elements, multiple complex transfer functions calculated for each of the multiple subcarriers can be treated together as a first matrix, and biological information used for position estimation of the living organism 20 can be calculated based on the propagation characteristics of the entire estimation system 101. Furthermore, for multiple complex transfer functions obtained from multiple receiving devices that are not signal-synchronized, a correlation matrix representing the correlation between multiple elements included in the first matrix can be calculated, and by extracting biological components from this correlation matrix or the multiple complex transfer functions, information attributable to the presence of the living organism 20 can be extracted as biological information. Furthermore, in order to estimate the position of the living organism 20 using the real or imaginary component of the biological information, it is possible to utilize components of the propagation characteristics information included in the complex transfer function that are useful for estimating the position of the living organism 20. This allows for the estimation of the position of the living organism 20 with high accuracy in an estimation system 101 equipped with Lm transmitters 102-1 to 102-Lm and Ln receivers 103-1 to 103-Ln.

[0099] In the estimation system 101 of this embodiment, the first matrix is ​​a matrix containing a plurality of complex transfer functions as elements, and the second process may be a process of extracting biological components from the correlation matrix.

[0100] According to this method, the first matrix is ​​constructed as a matrix containing multiple complex transfer functions as elements, and biological information can be obtained by extracting biological components from the correlation matrix calculated based on this first matrix. In this way, the relationships between the complex transfer functions obtained for each of the multiple combinations of the transmitting device and the receiving device are generated as a correlation matrix, and by selectively extracting the component related to the biological organism 20 included in that correlation, information useful for estimating the position of the biological organism 20 can be efficiently utilized.

[0101] In the estimation system 101 of this embodiment, the second process is a process of extracting biological components from a plurality of complex transfer functions, and the first matrix may be a matrix that includes the results of the second process as elements.

[0102] According to this method, biological components can be extracted from multiple complex transfer functions, and a first matrix containing these components can be obtained. This allows for the calculation of a correlation matrix for the first matrix containing biological components, enabling the acquisition of biological information focusing on the relationships between organisms, which can then be used for position estimation. As a result, the position of organism 20 can be estimated in a way that is less affected by components other than organism 20.

[0103] In the estimation system 101 of this embodiment, the second process may be a process that converts one of the multiple complex transfer functions or correlation matrices into the frequency domain and extracts only the components in a specific frequency domain that originate from the movement of the living organism 20.

[0104] According to this method, in the second process, one of multiple complex transfer functions or correlation matrices is converted to the frequency domain, and components in a specific frequency domain originating from the movement of the living organism 20 are extracted to determine the biological components. This makes it possible to obtain biological information focusing on the periodic components corresponding to the movement of the living organism 20, and to estimate the position of the living organism 20 by focusing on the components of the temporal variation that contribute to the estimation of the position of the living organism 20.

[0105] In the estimation system 101 of this embodiment, the specific frequency range may be a positive frequency range.

[0106] According to this, by defining a specific frequency range as the positive frequency range, components originating from the movement of the biological organism 20, as expressed in the frequency range, can be unified and handled on the positive frequency side. This clarifies the range of frequency components used as biological information, and allows the process of estimating the position of the biological organism 20 based on the results of frequency analysis to be performed under simple and consistent conditions.

[0107] In the estimation system of this embodiment, the processing unit 191 may estimate the position of the living organism 20 using either the MUSIC (Multiple Signal Classification) method or the Capon method for the real component or the imaginary component.

[0108] According to this, position estimation can be performed on the real or imaginary component of the biological information using either the MUSIC method or the Capon method. This allows the application of computational processing known as a high-resolution direction of arrival estimation method to the biological information obtained from the first matrix and the correlation matrix, and enables the estimation of the position of the living organism 20 with detailed spatial resolution based on the propagation characteristics obtained from Lm transmitting devices 102-1 to 102-Lm and Ln receiving devices 103-1 to 103-Ln.

[0109] Furthermore, according to the estimation system 101 of this embodiment, an autocorrelation calculation using complex conjugates is performed on the complex transfer function obtained for each combination of transmitting antenna element and receiving antenna element, and the correlation matrix of the complex transfer function can be obtained by multiplying each element of the complex transfer function and forming a matrix. This reduces the influence of random phase errors that fluctuate over time due to the clock difference between the transmitting and receiving devices, and allows the information on the direction of the transmitting antenna element and the direction of the receiving antenna element to be handled together as a matrix, thereby increasing the amount of spatial information used for position estimation of the living organism 20.

[0110] Furthermore, by configuring the system so that at least one of the transmitting antenna elements or receiving antenna elements is two or more, even when multiple antenna elements are provided on either the transmitting or receiving side in a so-called SISO configuration, the coordinates of the living organism 20 and the distance between the transmitting or receiving antenna elements and the living organism 20 can be estimated. In addition, when the estimation system 101 of this embodiment is applied to a MIMO configuration in which both the transmitting and receiving antenna elements are multiple, a MISO configuration with multiple antenna elements on the transmitting side and one antenna element on the receiving side, or a SIMO configuration with multiple antenna elements on the receiving side and one antenna element on the transmitting side, the amount of usable spatial information increases even further. As a result, the coordinates of the living organism 20 and the distance between the antenna elements and the living organism 20 can be estimated with higher accuracy than before.

[0111] (Embodiment 2) Embodiment 2 describes a method for detecting living organisms in a SISO system where p transceivers 202-1 to 202-p (where p is a natural number of 1 or more) connected to the same access point (AP) share a transmitting antenna element and a receiving antenna element, respectively, when multiple stations are arranged for both or one of the transmitting and receiving devices. Note that the method described in this embodiment can also be applied in the same way as the SISO system to the MIMO system, in which both the transmitting antenna unit and the receiving antenna unit have multiple antenna elements, or to the SIMO system or MISO system, in which one of the transmitting antenna unit and the receiving antenna unit has a single antenna element, by taking elements from all sets of transmitting and receiving antennas or a specific set of transmitting and receiving antennas from multiple sets of transmitting and receiving antennas and performing the same processing as the SISO system.

[0112] [Configuration of Estimation System 201] Figure 2 is a block diagram showing an example of the configuration of the estimation system in Embodiment 2.

[0113] The estimation system 201 shown in Figure 2 comprises p transceivers 202-1 to 202-p and an estimation unit 290. Here, p is a natural number greater than or equal to 1. p may also be equal to Lm and Ln.

[0114] Each of the p transceivers 202-1 to 202-p comprises a transceiver antenna section 230-1 to 230-p, a transceiver section 240-1 to 240-p, a complex transfer function calculation section 241-1 to 241-p, a correlation matrix calculation section 250-1 to 250-p, and a bio-information calculation section 280-1 to 280-p. For example, the transceiver 202-k comprises a transceiver antenna section 230-k, a transceiver section 240-k, a complex transfer function calculation section 241-k, a correlation matrix calculation section 250-k, and a bio-information calculation section 280-k. Here, k is one of 1 to p. Thus, each transceiver comprises a transmitting antenna section, a transceiver section, a complex transfer function calculation section, a correlation matrix calculation section, and a bio-information calculation section. Furthermore, since the functions realized by the transmitting antenna section, transmitting / receiving section, complex transfer function calculation section, correlation matrix calculation section, and biometric information calculation section of each transmitting / receiving device are common to p transmitting / receiving devices 202-1 to 202-p, the following description will represent the components of one transmitting / receiving device.

[0115] The estimation system 201 uses the multi-carrier signal used when wireless communication is performed with such transceivers 202-1 to 202-p joined to the same access point AP 30 to estimate at least one of the following: the distance to the living organism 20, the direction to the living organism 20, and the position of the living organism 20. The correlation matrix calculation units 250-1 to 250-p, the biological information calculation units 280-1 to 280-p, and the estimation unit 290 may function as a processing unit 291.

[0116] [Transmitting / receiving antenna unit 230-k] The transmitting / receiving antenna unit 230-k has one or more transmitting / receiving antenna elements. The p transmitting / receiving antenna units 230-1 to 230-p have a total of M transmitting / receiving antenna elements. Here, M is a natural number of 1 or greater, equal to N. In other words, M transmitting / receiving antenna elements have M transmitting antenna elements and N receiving antenna elements. The transmitting / receiving antenna elements of the transmitting / receiving antenna unit 230-k transmit a multi-carrier signal (transmitted wave) generated by the corresponding transmitting / receiving unit 240-k, and also receive a signal (received signal) transmitted from the transmitting / receiving device 202-k that has been reflected or scattered by the living organism 20. The estimation system 201 uses the component of the signal received by the transmitting / receiving antenna units 230-1 to 230-p that has been reflected or scattered by the living organism 20 to estimate at least one of the distance to the living organism 20, the direction to the living organism 20, and the position of the living organism 20.

[0117] [Transmitting / Receiving Unit 240-k] The transmitting / receiving unit 240-k has the function of generating a multicarrier signal in which multiple subcarrier signals are modulated, and the function of demodulating the signal received via the transmitting / receiving antenna unit 230-k. Specifically, the transmitting / receiving unit 240-k generates multiple subcarrier signals corresponding to multiple subcarriers in different frequency bands, and generates a multicarrier signal by multiplexing the generated multiple subcarrier signals. In this embodiment, an example will be described in which an OFDM signal consisting of S subcarriers, which has high frequency band utilization efficiency, is used as the multicarrier signal generated by the transmitting / receiving unit 240-k. However, as long as it is a multicarrier signal obtained by multicarrier modulation, it is not limited to an OFDM signal in which each subcarrier is orthogonal, but other multicarrier signals by FDM (Frequency Division Multiplexing) may be generated. The transmitting / receiving unit 240-k applies predetermined signal processing to the multi-carrier signal it generates, such as upconversion (converting the signal from the IF (Intermediate Frequency) frequency band to the RF (Radio Frequency) frequency band) and amplification (amplifying the signal to an appropriate transmission level), thereby generating a transmission wave. The transmitting / receiving unit 240-k outputs the processed multi-carrier signal to the transmitting / receiving antenna unit 230-k, causing the transmitting / receiving antenna unit 230-k to transmit the multi-carrier signal. As a result, the multi-carrier signal is transmitted from one or more transmitting antenna elements provided by the transmitting / receiving antenna unit 230-k.

[0118] The transmitting / receiving unit 240-k observes the received signal, which is received by one or more transmitting / receiving antenna elements of the transmitting / receiving antenna unit 230-k and includes a reflected signal in which a multicarrier signal transmitted from another transmitting / receiving antenna unit different from the transmitting / receiving antenna unit 230-k has been reflected or scattered by the living organism 20, for a first period corresponding to a period derived from the activity of the living organism 20. The period derived from the activity of the living organism is a period derived from the living organism (living fluctuation period) that is half a period or longer of any of the periods of respiration, heartbeat, or body movement of the living organism 20.

[0119] The transmitting / receiving unit 240-k converts the high-frequency signal received by one or more transmitting / receiving antenna elements of the transmitting / receiving unit 240-k into a low-frequency signal that can be processed. The transmitting / receiving unit 240-k then demodulates the low-frequency signal into an OFDM signal, which is then demodulated into a signal (IQ symbol) of S subcarriers.

[0120] Furthermore, the transmitting / receiving unit 240-k transmits and outputs all or part of the S subcarrier signals (IQ symbols) of M' × M' pairs (M' = M + 1) corresponding to each combination of the total M transmitting / receiving antenna elements and AP30 to the complex transfer function calculation unit 241.

[0121] The transmitting / receiving unit 240-k may continuously observe the received signal received by the transmitting / receiving antenna unit 230-k, or it may continuously transmit S low-frequency signals (IQ symbols) at regular intervals.

[0122] Furthermore, the signals from the M transmitting and receiving antenna elements of the p transmitting and receiving antenna units 230-1 to 230-p may each contain different phase rotation noise.

[0123] [Complex Transfer Function Calculation Unit 241-k] The complex transfer function calculation unit 241-k calculates a complex transfer function using a plurality of received signals observed in the first period by the corresponding transmitting / receiving unit 240-k. Specifically, for each of the M' × M' combinations corresponding to each combination of M transmitting / receiving antennas and AP 30, the complex transfer function representing the propagation characteristics between the transmitting antenna element and the receiving antenna element in that combination may be calculated for each of the plurality of subcarriers to which the plurality of subcarrier signals correspond, or it may be calculated for only one or more of the M' × M' combinations. Note that the M' × M' combinations are all possible combinations when each element of the M transmitting / receiving antenna elements is paired with AP in a one-to-one relationship. In this embodiment, only one of the M' × M' combinations will be used from here on. Furthermore, the complex transfer functions calculated by the complex transfer function calculation units 241-k provided in each of the multiple receiving devices are aggregated in the subsequent processing unit 291 within the estimation system 201 and used as a set of M' × M' complex transfer functions corresponding to the combination of M' transmitting and receiving antenna elements and AP30. In other words, the multiple complex transfer functions calculated by the complex transfer function calculation units 241-1 to 241-p are shared among the p transmitting and receiving devices 202-1 to 202-p.

[0124] Thus, the multiple complex transfer functions calculated by the complex transfer function calculation units 241-1 to 241-p provided in the p transceiver devices 202-1 to 202-p are aggregated in the subsequent processing unit 291 within the estimation system 201 and treated as a complex transfer function matrix containing M' × M' sets of complex transfer functions corresponding to the combination of M' transceiver antenna elements and AP30. The calculated complex transfer function matrix includes components corresponding to reflected signals received via the living organism 20, as well as components resulting from paths that do not pass through the living organism 20, such as components corresponding to direct waves from one transceiver antenna element to another, and components corresponding to reflected waves reflected by fixed objects other than the living organism 20.

[0125] The complex transfer function calculation unit 241-k may sequentially calculate the complex transfer function vector at predetermined time intervals using each of the multiple subcarrier signals (IQ symbols) that are constantly output from the corresponding transmitting / receiving unit 240-k, or output at regular intervals, or it may calculate the complex transfer function vector continuously. By configuring the system to continuously calculate the complex transfer function vector in this way, if the estimation system 201 shares hardware with a communication device such as a wireless LAN device, the complex transfer function vector that is constantly calculated on the communication device side for communication processing can be commonly used in the estimation process used for estimating the position of the living organism 20.

[0126] In this embodiment, the complex transfer function calculation unit 241-k calculates a complex transfer function vector h(t) representing the propagation characteristics between each transmitting and receiving antenna element during an observation time t, based on S IQ symbols transmitted from the corresponding transmitting and receiving unit 240-k, according to (Equation 14). If there are multiple transmitting and receiving devices 202-1 to 202-p, a complex transfer function vector h(t) is obtained for each transmitting and receiving device, and these complex transfer function vectors are aggregated in a subsequent process to be used as multiple complex transfer functions corresponding to a total of M transmitting and receiving antenna elements.

[0127]

[0128] [Correlation Matrix Calculation Unit 250-k] The correlation matrix calculation unit 250-k receives the complex transfer function vector h(t) calculated by the corresponding complex transfer function calculation unit 241-k as input, calculates a correlation matrix of complex transfer functions based on a complex transfer function matrix that includes M' × M' pairs of complex transfer functions as elements, and calculates the diagonal terms of the correlation matrix.

[0129] The calculation of the diagonal terms of the correlation matrix will be explained in detail using mathematical formulas below. Among the complex transfer function vector h(t), the element corresponding to the subcarrier s is h ｓThis is expressed as follows. The propagation characteristics between one of the p transmitting / receiving antenna units 230-1 to 230-p and AP30 and M' transmitting / receiving antenna units can be decomposed as a function of time t, as shown in (Equation 15). Here, we focus on the direct wave component that does not pass through the living organism 20 between one transmitting antenna unit and one receiving antenna unit, the reflected component received by one receiving antenna unit after the signal transmitted from one transmitting antenna unit is reflected by the living organism 20, and the influence of random phase errors caused by clock discrepancies between the transmitting and receiving devices.

[0130]

[0131] Here, h ｓｄ This represents the direct wave component corresponding to the propagation path between different transmitting and receiving antenna elements that does not pass through the living organism 20, and h ｓｖ This represents the component corresponding to the propagation path in which a signal transmitted from one transmitting / receiving antenna element is reflected by the living organism 20 and received by another transmitting / receiving antenna element. ｅ (t) represents a random phase error that fluctuates over time due to factors such as the clock mismatch between the transmitting and receiving devices. Here, i is the imaginary unit.

[0132] Next, the vector r, which consists of the diagonal terms of the correlation matrix for the complex transfer function vector h(t), can be expressed as shown in (Equation 16).

[0133]

[0134] Here, * represents the complex conjugate. Here, each vector and matrix from (Equation 14) to (Equation 16) has components in the direction of the antenna elements as many times as there are antenna elements, but in the following explanation, we will focus on the components corresponding to the propagation characteristics from the m-th transmitting antenna element to the n-th receiving antenna element. In this case, considering the s-th element of (Equation 16), the effect of random phase errors is removed by the autocorrelation calculation as shown in (Equation 17).

[0135]

[0136] Also, h ｓｎｍThese are the components of the complex transfer function vector corresponding to the subcarrier s, the transmitting antenna element m, and the receiving antenna element n. ｓｎｍｄ These are the components of the direct wave between the transmitting and receiving antennas that do not pass through the living organism 20, corresponding to the subcarrier s, the transmitting antenna element m, and the receiving antenna element n. ｓｎｍｖ These are components of the propagation path that are reflected from the transmitting antenna element by the living organism 20 and received by the receiving antenna element, and correspond to the subcarrier s, the transmitting antenna element m, and the receiving antenna element n.

[0137] [Biological Information Calculation Unit 280-k] The biological information calculation unit 280-k receives the diagonal term r of the correlation matrix of the complex transfer function calculated by the correlation matrix calculation unit 250-k as input, and for each of the multiple subcarriers, it sequentially records the diagonal term r of the correlation matrix over the first period in the order in which the multiple received signals were observed. Then, for each of the multiple subcarriers, the biological information calculation unit 280-k extracts the components related to the biological organism 20 based on the diagonal term r of the correlation matrix that has been sequentially recorded in the time series, and calculates a biological component transfer function vector represented by an S × N × M dimension matrix for each of the multiple subcarriers.

[0138] Here, the biocomponent transfer function vector is a complex transfer function obtained by extracting and representing the component that has passed through the biological body 20 from the reflected or scattered waves contained in the received signal. To determine the biocomponent, as described above, the diagonal term r of the correlation matrix recorded in time series can be used, and methods such as applying the Fourier transform or using difference information in the time series can be employed. Specific examples of these processes are disclosed in Patent Document 1 as a method using the Fourier transform and in Patent Document 2 as a method using difference information.

[0139] For example, in the method using the Fourier transform, a Fourier transform is performed on the time series data of the diagonal term r of the correlation matrix in the observation time direction (slow time direction), and frequency components included in the frequency band that may include the influence of the activity of the living organism 20 are selectively extracted. An example of a frequency band that may include the influence of the activity of the living organism 20 is a group of frequency components that fall within the range of 0.1 Hz to 3 Hz. In this case, for each of these group of frequency components, the biological component transfer function r is calculated as shown in (Equation 18). ｓｎｍ (ω) can be calculated.

[0140]

[0141] Here, ω is the biological activity frequency to be extracted, and F[•] represents the Fourier transform. The component that passes through the biological organism 20 is the component h that fluctuates depending on the movement of the biological organism 20, among the multiple transfer functions shown in (Equation 17). ｓｎｍｖ It appears in correspondence with (t). Therefore, by applying a Fourier transform to the time series of the diagonal term r of the correlation matrix and selectively extracting frequency components corresponding to the biological activity frequency band, h ｓｎｍｖ The component attributable to (t) can be extracted. This allows us to obtain the biocomponent transfer function r that reflects the components corresponding to the second and third terms related to the activity of the organism 20 among the components included in the right-hand side of (Equation 17). ｓｎｍ (ω) is obtained.

[0142] [Estimation Unit 290] The estimation unit 290 estimates information such as the position of the living organism 20, the distance to the living organism 20, and the angle (direction) to the living organism, based on the biological component transfer functions calculated by the p biological information calculation units 280-1 to 280-p. Using the biological component transfer functions calculated by the biological information calculation unit 280-k for each combination of transmitting and receiving antenna elements, the biological component transfer function matrix corresponding to all (M') combinations of transmitting and receiving antenna elements in the s-th subcarrier can be expressed as a matrix as shown in (Equation 19). This biological component transfer function matrix is ​​a matrix that includes the biological component transfer function rsnm(ω) obtained for each combination of transmitting and receiving antenna elements as an element, and expresses the propagation characteristics related to the living organism 20 in a form that reflects the spatial arrangement relationship of all transmitting and receiving antenna elements.

[0143]

[0144] The estimation unit 290 rearranges the biocomponent transfer function matrix in the s-th subcarrier shown in (Equation 19) along the combination direction of the transmitting and receiving antenna elements to convert it into the biocomponent transfer function vector shown in (Equation 20). This allows the biocomponent transfer function corresponding to the combination of M' transmitting and receiving antenna elements in the s-th subcarrier to be treated as a single M' × M' dimension vector, making it easier to perform subsequent correlation matrix calculations and spatial spectrum calculations.

[0145]

[0146] Furthermore, the estimation unit 290 obtains a biocomponent transfer function vector corresponding to (Equation 20) for all subcarriers and connects them in the subcarrier direction to form the biocomponent transfer function vector shown in (Equation 21). This biocomponent transfer function vector is an S × M' × M' dimension vector that includes components corresponding to multiple subcarriers, all transmitting antenna elements, and all receiving antenna elements, and simultaneously represents frequency and spatial information related to the biological organism 20.

[0147]

[0148] The estimation unit 290 calculates a correlation matrix of the biocomponent transfer function as shown in (Equation 22) based on the biocomponent transfer function vector shown in (Equation 21), and performs eigenvalue decomposition on this correlation matrix. The correlation matrix is ​​a matrix that represents the autocorrelation of the biocomponent transfer function vector, and it represents the energy distribution of the component corresponding to the reflected component from the biological body 20 and the noise component in matrix form.

[0149]

[0150] Here, E[•] represents the average in the frequency ω direction, U is a matrix containing the eigenvectors of the correlation matrix as elements, and Λ is a diagonal matrix containing the corresponding eigenvalues ​​as diagonal terms. The estimation unit 290 separates the signal space and the noise space based on the magnitude of the eigenvalues ​​of the correlation matrix, and obtains the noise space eigenvector matrix U from the eigenvectors corresponding to the noise space. Ｎ The following are extracted. Then, as an example of an incoming wave direction estimation method, the MUSIC (Multiple Signal Classification) method is applied, and the spatial spectrum corresponding to the candidate position of the living organism 20 is calculated as shown in (Equation 23). Note that instead of the MUSIC method, the Capon method or other spatial spectrum estimation methods may be used as the incoming wave direction estimation method.

[0151]

[0152] Here U Ｎ A is a matrix containing noise space eigenvectors as elements, and a(x, y, z) is a steering vector that represents the positional relationship of the signals arriving at each transmitting antenna element and each receiving antenna element from an arbitrary position (x, y, z) in space, assuming that a living organism 20 exists at that position. The steering vector a(x, y, z) is defined based on the positional information of the transmitting antenna elements and receiving antenna elements and the wavelength of the subcarrier, as shown in (Equation 24).

[0153]

[0154] Here, x is the arbitrary x-coordinate to be estimated, y is the y-coordinate of the position, and z is the z-coordinate of the position. ｍ is the x-coordinate of the m-th transmitting antenna element, and yｍ is the y-coordinate of the m-th transmitting antenna element, and z ｍ x is the z-coordinate of the m-th transmitting antenna element. ｎ is the x-coordinate of the nth receiving antenna element, and y ｎ is the y-coordinate of the nth receiving antenna element, and z ｎ λ is the z-coordinate of the nth receiving antenna element. ｓ is the wavelength of the s-th subcarrier, and d ｎｍ is the distance between the m-th transmitting antenna element and the n-th receiving antenna element. By rearranging the steering vectors defined based on these parameters along the combination direction of the transmitting and receiving antenna elements, the steering vector corresponding to the s-th subcarrier can be expressed as a vector, as shown in (Equation 25).

[0155]

[0156] Furthermore, by determining steering vectors corresponding to (Equation 25) for all subcarriers and connecting them in the subcarrier direction, the steering vector shown in (Equation 26) can be obtained. This steering vector includes elements corresponding to multiple subcarriers, all transmitting antenna elements, and all receiving antenna elements, and represents the theoretical pattern of propagation characteristics that can be observed when it is assumed that a living organism 20 is present at the estimated target position (x, y, z).

[0157]

[0158] As described above, the estimation unit 290 substitutes the steering vector shown in (Equation 26) into (Equation 23) and calculates the spatial spectrum value for each position (x, y, z) in the estimation target space. Then, by searching for the position where there is a peak in the distribution of the obtained spatial spectrum, the location where the living organism 20 is estimated to be present can be determined. Furthermore, based on the estimated position information and the arrangement information of the transmitting antenna element and the receiving antenna element, the distance and direction to the living organism 20 can be calculated.

[0159] [Effects, etc.] According to the estimation system 201 of this embodiment, when the number of transmitting devices and the number of receiving devices are made equal to each other, and the estimation system 201 is configured to have a one-to-one correspondence between the transmitting and receiving devices, it is possible to obtain the complex transfer function corresponding to the transmission path and reception path for each transmitting and receiving device. Therefore, it is possible to calculate biological information and estimate the biological position based on the complex transfer function associated with each transmitting and receiving device, and the biological position estimation process using p transmitting and receiving devices can be executed based on an easy-to-understand correspondence.

[0160] According to the estimation system 201 of this embodiment, the diagonal term of the correlation matrix is ​​calculated based on the autocorrelation of the complex transfer function obtained for each combination of the multiple transmitting and receiving antenna elements of the p transmitting and receiving devices 202-1 to 202-p and the access point AP30. This configuration reduces the influence of random phase errors caused by clock shifts between the transmitting and receiving devices, while allowing the information on the directions of multiple transmitting and receiving antenna elements to be calculated together as a matrix. As a result, the amount of spatial information can be increased by integrally processing the complex transfer functions obtained from multiple transmitting and receiving devices, enabling high-precision estimation of the position of the living organism 20, the distance to the living organism 20, and the direction to the living organism 20. In particular, even if each transmitting and receiving device has only a single transmitting and receiving antenna element in a SISO configuration, by combining two or more transmitting and receiving devices to configure the estimation system 201, the coordinate information of the living organism 20 and the distance from the transmitting and receiving antenna elements to the living organism 20 can be estimated with the same spatial resolution as when multiple transmitting and receiving antenna elements are provided. Furthermore, even in MIMO, MISO, or SIMO configurations where the transceiver or access point AP30 has multiple antenna elements, the amount of spatial information can be similarly increased based on the correlation matrix of the complex transfer function. Therefore, compared to the SISO configuration, the position of the living organism 20, the distance to the living organism 20, and the direction to the living organism 20 can be estimated with higher accuracy.

[0161] [Operation of Estimation Systems 101 and 201] The operation of the estimation process of the estimation systems 101 and 201 configured as described above will now be explained. Figure 3 is a flowchart showing the estimation process of estimation systems 101 and 201 in Embodiment 1 and Embodiment 2.

[0162] Estimation systems 101 and 201 calculate the complex transfer function for the first period (S100).

[0163] Next, the estimation systems 101 and 201 calculate the correlation matrix of an arbitrary complex transfer function (S200).

[0164] Next, estimation systems 101 and 201 vectorize the correlation matrices of the complex transfer functions (S300).

[0165] Next, the estimation systems 101 and 201 transform the correlation matrix into the frequency domain and extract the imaginary part of the positive frequency components that are affected by the biological organism 20 (S400).

[0166] Finally, the estimation systems 101 and 201 estimate the distance of the path from the transmitting antenna to the receiving antenna via the living organism 20 using the incoming wave direction estimation method based on the extracted imaginary component (S500).

[0167] Details of each step have been described above and will therefore be omitted here.

[0168] (Modification 1) Figure 4 is a block diagram showing an example of the configuration of the estimation system in Modification 1.

[0169] In Modification 1, instead of arranging the transmitting device and receiving device described in Embodiment 1 as separate devices, a transmitting / receiving device 302-1 to 302-p is used, as shown in Figure 4, which shares the transmitting and receiving functions within the same device. Each transmitting / receiving device 302-k (where k is one of 1 to p) has a transmitting / receiving antenna unit 330-k, a transmitting / receiving unit 340-k, a complex transfer function calculation unit 341-k, a correlation matrix calculation unit 350-k, and a biometric information calculation unit 380-k, and cooperates with the estimation unit 390 via a processing unit 391. With this configuration, each transmitting / receiving device 302-k can perform the transmitting and receiving processes within the same housing, similar to the transmitting / receiving device described in Embodiment 2.

[0170] In the modified example 1, the estimation system 301 may be configured to include a mix of devices primarily having a transmitting function, a device primarily having a receiving function, and a device having both transmitting and receiving functions. For example, one device may primarily consist of a transmitting antenna and a transmitting unit, another device may primarily consist of a receiving antenna and a receiving unit, and yet another device may consist of a transmitting / receiving antenna and a transmitting / receiving unit. The complex transfer function calculation units 341-1 to 341-p, correlation matrix calculation units 350-1 to 350-p, biological information calculation units 380-1 to 380-p, and estimation unit 390 of these devices work together to perform processing, thereby enabling high-precision estimation of the position of the biological organism 20, the distance to the biological organism 20, and the direction to the biological organism 20 based on the reflected signal from the biological organism 20, similar to the estimation system 101 described in Embodiment 1.

[0171] (Modification 2) Figure 5 is a block diagram showing a first example of the configuration of the estimation system in Modification 2. Figure 6 is a block diagram showing a second example of the configuration of the estimation system in Modification 2.

[0172] In Embodiments 1 and 2, examples were described in which the transmitting antenna unit 100-k, the receiving antenna unit 130-l, and the transmitting / receiving antenna unit 230-k each have one or more antenna elements. In contrast, the estimation system 101A shown in Figure 5 shows an example in which each transmitting antenna unit 100A-1 to 100A-Lm and each receiving antenna unit 130A-1 to 130A-Ln each have one antenna element. Furthermore, the estimation system 201A shown in Figure 6 shows an example in which each transmitting / receiving antenna unit 230-1 to 230-p each have one transmitting / receiving antenna element.

[0173] Thus, if at least one of the transmitting antenna unit, receiving antenna unit, and transceiver antenna unit has a single antenna element and the other has multiple antenna elements, then, similar to Embodiment 1 and Embodiment 2, the estimation system 101A or estimation system 201A can be used to estimate not only the distance to the living organism 20, but also the direction to the living organism 20 and the position of the living organism 20. On the other hand, if both the transmitting antenna unit and the receiving antenna unit, or the transceiver antenna unit, have a single antenna element, then the spatial arrangement information of the transmitting antenna element and the receiving antenna element becomes one-dimensional, so the estimation system 101A or estimation system 201A can estimate the distance to the living organism 20.

[0174] Even when adopting the configuration of this modified example 2, the same effects as in Embodiment 1 and Embodiment 2 can be obtained, such as reducing random phase errors based on the correlation matrix of the complex transfer function and extracting the propagation component that passes through the living organism 20.

[0175] (Modification 3) Figure 7 is a block diagram showing a first example of the configuration of the estimation system in Modification 3. Figure 8 is a block diagram showing a second example of the configuration of the estimation system in Modification 3.

[0176] This third modification describes an example in which the calculation of the complex transfer function and the subsequent calculation of the correlation matrix, the calculation of biological information, and the location estimation process are modified compared to the estimation system according to Embodiments 1 and 2. In Embodiments 1 and 2, the estimation units 190 and 290 within the estimation system 101 and 201 were described as compiling the biological component transfer functions calculated for each combination of the m-th transmitting antenna element (transmitting and receiving antenna element) and the n-th receiving antenna element (transmitting and receiving antenna element) into a matrix, and then calculating the correlation matrix and the spatial spectrum.

[0177] In contrast, in the modified example 3 shown in Figures 7 and 8, the estimation systems 101B and 201B perform the calculation of the complex transfer function, and transmit the results to the network N1 via communication interfaces such as communication interfaces 160-1 to 160-Lm, 161-1 to 161-Ln, and 261-1 to 261-p, and the results are aggregated and processed by a server 400 connected to the same network N1. The server 400 includes a communication interface 460, a correlation matrix calculation unit 450, a biological information calculation unit 480, and an estimation unit 490, and can estimate the position of the biological organism 20, the distance to the biological organism 20, and the direction (angle) to the biological organism 20 based on the complex transfer function transmitted from the estimation systems 101B and 201B, similar to embodiments 1 and 2.

[0178] Furthermore, the device used as server 400 is not limited to a dedicated server device. For example, home appliances such as televisions, refrigerators, washing machines, microwave ovens, vacuum cleaners, and air conditioners, or information devices that can connect to network N1, such as PCs and routers, may be equipped with server 400 functionality.

[0179] In this way, the complex transfer function calculated by the estimation systems 101B and 201B is transmitted to the server 400 via the network N1, and the server 400 centrally executes the correlation matrix calculation process, the biometric information calculation process, and the position estimation process. This configuration allows for the same effects as in Embodiments 1 and 2, while consolidating a portion of the estimation process on the server side to improve the distribution of processing load and the flexibility of the device configuration.

[0180] (Modification 4) In Embodiment 1 and Embodiment 2, as shown in (Equation 8) and (Equation 21), vectorization was performed using a biocomponent transfer function matrix that includes components corresponding to all combinations of transmitting antenna elements and receiving antenna elements.

[0181] In contrast, the estimation system according to Modification 4 does not use all combinations of transmitting and receiving antenna elements, but rather selects only the matrix elements corresponding to these combinations and performs vectorization based on the selected elements. In that case, the steering vector shown in (Equation 13) is also calculated using only the components corresponding to the selected combination of transmitting and receiving antenna elements.

[0182] In this way, by defining the biocomponent transfer function vector and steering vector using only the components corresponding to the necessary combination of transmitting and receiving antenna elements, the amount of computation can be reduced, and the position of the living organism 20, the distance to the living organism 20, and the direction toward the living organism 20 can be estimated with high accuracy, similar to Embodiment 1 and Embodiment 2.

[0183] (Modification 5) In Embodiment 1 and Embodiment 2, as shown in (Equation 3) and (Equation 16), the autocorrelation of the complex transfer function was determined for each transmitting and receiving antenna element, and a correlation matrix was constructed based on the results.

[0184] In contrast, in the estimation system according to Modification 5, a complex transfer function matrix may be constructed first along the combination direction of the transmitting and receiving antenna elements using the acquired complex transfer function, and then a correlation matrix may be calculated by finding the autocorrelation for each element of this complex transfer function matrix. In this case, the acquired complex transfer function matrix can be calculated as shown in (Equation 27), for example.

[0185] This configuration allows for the handling of the complex transfer function as a single matrix while separating components originating from the biological system 20 from random phase errors, thereby achieving the same effects as in Embodiment 1 and Embodiment 2.

[0186]

[0187] When the autocorrelation of the complex transfer function matrix obtained as described above is calculated element by element, the correlation matrix is ​​expressed as shown in (Equation 28).

[0188]

[0189] Furthermore, by performing a Fourier transform on the correlation matrix shown in (Equation 28) in the same manner as in (Equation 5), and extracting the imaginary component of the obtained frequency domain data, the biocomponent transfer function matrix corresponding to the s-th subcarrier shown in (Equation 6) can be obtained. The obtained biocomponent transfer function matrix can be used in subsequent estimation processes to determine the position of the organism 20, the distance to the organism 20, and the direction to the organism 20, similar to Embodiments 1 and 2 described above.

[0190] (Modification 6) In Embodiment 1 and Embodiment 2, the biocomponent transfer function was calculated using the imaginary part of the spectrum after the Fourier transform, as shown in (Equation 5) and (Equation 18). However, instead, the biocomponent transfer function may be calculated using the real part of the spectrum after the Fourier transform, as shown in (Equation 29). Even with this configuration, the same effects as in Embodiment 1 and Embodiment 2 can be obtained in terms of estimating the position, distance, and direction of the living organism 20.

[0191]

[0192] (Modification 7) In Embodiment 1 and Embodiment 2, the biocomponent transfer function was calculated using only the imaginary component after the Fourier transform, as shown in (Equation 5) and (Equation 18). However, instead, as shown in (Equation 30) and (Equation 31), the absolute values ​​of the imaginary component and the real component after the Fourier transform are taken, and the sum of these values ​​along the subcarrier direction is compared, with the larger value being used as the representative value of the biocomponent. By configuring it in this way, it is possible to emphasize the fluctuations originating from the biocomponent 20 that mainly appear in either the imaginary component or the real component, and thus obtain the same effects as in Embodiment 1 and Embodiment 2.

[0193]

[0194]

[0195] (Modification 8) In Embodiment 1 and Embodiment 2, the observation time t was set based on a predetermined time width, but instead, the first observation time t1 may be determined from the complex transfer function vector h(t). Specifically, the time range in which the effects of the activity of the living organism 20 are sufficiently apparent may be extracted based on the peaks and troughs of the amplitude in the complex transfer function vector h(t), or an arbitrary value corresponding to a desired threshold, and that time range may be set as the first observation time t1. By configuring it in this way, estimation processing can be performed by focusing on the period in which the activity of the living organism 20 is clearly apparent, and the same effects as in Embodiment 1 and Embodiment 2 can be obtained.

[0196] (Modification 9) In Embodiment 1 and Embodiment 2, the position of the living organism 20 was estimated using the MUSIC method as the incoming wave direction estimation method. However, other spatial spectrum estimation methods such as the Capon method or the beamformer method may be applied instead of the MUSIC method. Even in this case, the same effect as Embodiment 1 and Embodiment 2 can be obtained, as the spatial spectrum is calculated based on the correlation matrix, and the location of the living organism 20, the distance from the living organism 20, and the direction are estimated from the peak position.

[0197] (Modification 10) In this embodiment 2, the complex transfer function is calculated for all combinations of transmitting antenna elements and receiving antenna elements of all transmitting and receiving devices that have joined the same access point, and the complex transfer function matrix shown in (Equation 19) is constructed using all of these elements. In contrast, the communication devices that join the same access point may include devices with only transmitting functions, devices with only receiving functions, and devices with both transmitting and receiving functions. In this case, matrix elements corresponding to combinations of transmitting and receiving antenna elements for which a complex transfer function cannot be obtained due to the configuration of the transmitting and receiving functions may be treated as elements with no value, and the complex transfer function matrix equivalent to (Equation 19) may be constructed using only the matrix elements corresponding to the obtained complex transfer function. With this configuration, the same effects as in this embodiment 2 can be obtained.

[0198] (Modification 11) In this embodiment 2, the complex transfer function matrix is ​​calculated using the complex transfer functions corresponding to the transmitting antenna elements and receiving antenna elements of all transmitting and receiving devices that have joined the same access point. Alternatively, the transmitting and receiving device to be processed may be selected based on the MAC address of the transmitting or receiving device, and only the matrix elements corresponding to the combination of transmitting and receiving antenna elements belonging to the selected transmitting and receiving device may be extracted to construct the complex transfer function matrix. With this configuration, even if the number of communication devices that join the same access point increases and the amount of acquired data increases, the amount of data used for estimation processing can be controlled by filtering by MAC address, thereby preventing delays in normal communication processing.

[0199] (Modification 12) In Embodiment 1 and Embodiment 2, since multiple transmitting and receiving devices operate independently, the timing of the transmission and reception processes does not necessarily coincide, and the acquired complex transfer function may contain asynchronous components. To reduce the influence of these asynchronous components, the complex transfer function or biocomponent transfer function may be acquired multiple times in the time direction, and the mean, median, moving mean, or moving median may be calculated on these to smooth out temporal fluctuations and approximate a synchronous state. With this configuration, even if the multiple transmitting and receiving devices are not perfectly synchronized, the position and distance of the biological organism 20 can be estimated with stable accuracy.

[0200] [Effects, etc.] According to this embodiment, the complex transfer function obtained from any combination of transmitting and receiving antenna elements and access points is treated as a matrix, and a correlation matrix is ​​calculated by multiplying each element of the matrix by its complex conjugate. This makes it possible to obtain a correlation matrix that simultaneously incorporates information on the direction of the transmitting antenna element and the direction of the receiving antenna element, while reducing the influence of random phase errors caused by clock deviations between the transmitting and receiving devices through autocorrelation calculation. As a result, especially when there are two or more wireless devices in a SISO configuration, the coordinates of the living organism 20 and the distance to the living organism 20 can be estimated with high reliability using the estimation system. Furthermore, since the amount of information can be similarly increased even in MIMO, MISO, or SIMO configurations, the coordinates of the living organism 20 and the distance to the living organism 20 can be estimated with higher accuracy than before using the estimation system.

[0201] As described above, this disclosure makes it possible to realize an estimation system and estimation method that can estimate the distance to the living organism 20, the position of the living organism 20, and the angle (direction) to the living organism 20 in a short time and with high accuracy using wireless signals.

[0202] The above describes a distance measuring or positioning sensor and distance estimation method according to one aspect of the present disclosure, based on an embodiment. However, the present disclosure is not limited to these embodiments. Without departing from the spirit of the present disclosure, various modifications to this embodiment that a person skilled in the art could conceive, or forms constructed by combining components from different embodiments, are also included within the scope of the present disclosure.

[0203] For example, in Embodiment 1 and its modifications, distance estimation and position estimation of a living organism 20 were described as examples, but the object of estimation is not limited to a living organism 20. The above estimation method can be applied to various moving objects (machines, etc.) that, when irradiated with a high-frequency signal, cause a Doppler effect on the reflected wave due to their activity.

[0204] To confirm the effectiveness of the estimation method according to this embodiment, an evaluation was conducted using simulation. The simulation conditions, simulation environment, and obtained results are described below.

[0205] [Simulation] Figure 9 shows the simulation conditions using the estimation method according to this embodiment.

[0206] As shown in Figure 9, both the transmitting and receiving antennas were configured as 1x1 SISO using single-element omnidirectional antennas, with three transmitting and three receiving stations. The transmitter transmitted a signal with a center frequency of 2.4 GHz, and the operating frequency band was 20 MHz. The number of subcarriers used was 64, the vital frequency was 0.2 Hz, and the sampling frequency was 100 Hz. The antenna element spacing was half a wavelength, and the channel measurement time was 10.24 seconds. In addition, a random phase component was added to the channel, and the SNR of the received signal was set to 40 dB. The distance between the transmitter and receiver was 4 m.

[0207] Figure 10 shows an example of the estimated space and the arrangement of the transmitter, receiver, and living organism 20 in the simulation.

[0208] The transmitter Tx was positioned at coordinates (x, y) = (0, 4), and the receiver Rx was positioned at coordinates (x, y) = (4, 0). The true position (target position) of the living organism 20 was positioned at coordinates (x, y) = (2, 3).

[0209] Figure 11 shows an example of positioning results in a simulation using the estimation method in this embodiment. Specifically, Figure 11 shows an example of a spatial spectral distribution obtained using the estimation method according to this embodiment.

[0210] As shown in Figure 11, the spatial spectrum shows a peak near the target position (2,3), indicating that the location of the living organism 20 can be identified in two-dimensional space using the estimation method according to this embodiment.

[0211] Figure 12 shows another simulation result using the estimation method in the embodiment. Specifically, Figure 12 shows the cumulative probability distribution (CDF: Cumulative Distribution Function) for the absolute value of the difference between the estimated distance to the biological organism 20 and the true value.

[0212] In Figure 12, the horizontal axis represents the distance measurement error (in meters), and the vertical axis represents the probability (CDF value) that the measurement error is less than or equal to the measurement error. When using the estimation method according to this embodiment, the median distance error, i.e., the distance error at which the CDF value is 0.5, is obtained to be approximately 0.2 m, confirming that the biological position of a person can be estimated with high accuracy.

[0213] Furthermore, this disclosure can be implemented not only as a distance measuring sensor or positioning sensor equipped with such characteristic components, but also as an estimation method in which the characteristic components included in the distance measuring sensor or positioning sensor are used as steps. It can also be implemented as a computer program that causes a computer to execute each of the characteristic steps included in such a method. And it goes without saying that such a computer program can be distributed via a computer-readable non-temporary recording medium such as a CD-ROM or via a communication network such as the Internet.

[0214] This disclosure can be used in sensors and estimation methods for estimating the direction, distance, and position of a living organism using wireless signals. In particular, it can be used in distance measuring sensors and positioning sensors mounted on measuring instruments that measure the distance and position to a living organism using one or more wireless devices, home appliances that perform control according to the distance and position between wireless devices and a living organism, and monitoring devices that detect the intrusion of a living organism.

[0215] 20 Biological system 30 Access point 101, 201, 301 Estimation system 100-1 to 100-Lm Transmitting antenna section 102-1 to 102-Lm Transmitting device 103-1 to 103-Ln Receiving device 110-1 to 110-Lm Transmitting section 120-1 to 120-Lm Transmitting signal generation section 130-1 to 130-Ln Receiving antenna section 140-1 to 140-Ln Receiving section 141-1 to 141-Ln, 241-1 to 241-p, 341-1 to 341-p Complex transfer function calculation section 150-1 to 150-Ln, 250-1 to 250-p, 350-1 to 350-p, 450 Correlation matrix calculation section 160, 260, 460 Communication I / F 180-1 to 180-Ln, 280-1 to 280-p, 380-1 to 380-p, 480 Biological Information Calculation Unit 190, 290, 390, 490 Estimation Unit 191, 291, 391 Processing Unit 230-1 to 230-p Transmitting / Receiving Antenna Unit 240-1 to 240-p, 340-1 to 340-p Transmitting / Receiving Unit 400 Server N1 Network

Claims

1. An estimation system for estimating the position of a living organism, wherein the estimation system comprises Lm (where Lm is a natural number of 1 or more) transmitting devices, Ln (where Ln is a natural number of 1 or more) receiving devices, and a processing unit, wherein at least one of Lm and Ln is 2 or more, and each of the Lm transmitting devices comprises: a transmitting signal generation unit that generates a multicarrier signal in which a plurality of subcarrier signals are modulated; a transmitting antenna unit having one or more transmitting antenna elements; and a transmitting unit that processes the multicarrier signal and outputs it to the transmitting antenna unit, thereby causing the transmitting antenna unit to transmit the multicarrier signal, wherein the Lm transmitting devices have a total of M (where M is a natural number of 1 or more) transmitting antenna elements, and each of the Ln receiving devices comprises: a receiving antenna unit having one or more receiving antenna elements; and a receiving unit that observes the received signal received by the one or more receiving antenna elements, which includes a reflected signal in which the multicarrier signal transmitted from the M transmitting antenna elements is reflected or scattered by the living organism, for a first period corresponding to a period derived from the activity of the living organism. The system comprises: a receiving unit that uses the received signal observed in the first period to calculate a complex transfer function for each of the multiple subcarriers corresponding to the multiple subcarriers, each of which is a receiving unit; Ln receiving devices receiving the multicarrier signal without signal synchronization with each other; the processing unit calculating biological information based on the multiple complex transfer functions calculated for each of the multiple combinations of the M transmitting antenna elements and the total of N receiving antenna elements of the Ln receiving devices; estimating the position of the living organism from the real or imaginary component of the biological information; and the calculation of the biological information includes: a first process of calculating a correlation matrix representing the correlation between multiple elements in a first matrix based on a first matrix relating to the multiple complex transfer functions corresponding to the multiple combinations; and a second process of extracting biological components from either the multiple complex transfer functions or the correlation matrix.

2. The estimation system according to claim 1, wherein the first matrix is ​​a matrix containing the plurality of complex transfer functions as elements, and the second process is a process of extracting biological components from the correlation matrix.

3. The estimation system according to claim 1, wherein the second process is a process of extracting biological components from the plurality of complex transfer functions, and the first matrix is ​​a matrix that includes the results of the second process as elements.

4. The estimation system according to any one of claims 1 to 3, wherein the second process is a process of converting one of the plurality of complex transfer functions or the correlation matrix into the frequency domain and extracting only components in a specific frequency domain that originate from the movement of the living organism.

5. The estimation system according to claim 4, wherein the specific frequency range is a positive frequency range.

6. The estimation system according to any one of claims 1 to 3, wherein the processing unit estimates the position of the living organism using either the MUSIC (Multiple Signal Classification) method or the Capon method for the real component or the imaginary component.

7. The estimation system according to any one of claims 1 to 3, wherein Lm and Ln are 2 or more and are equal to each other, the estimation system comprises Lm transmitting and receiving devices, and each of the Lm transmitting and receiving devices comprises a transmitting device from among the Lm transmitting devices corresponding to the transmitting and receiving device and a receiving device from among the Ln receiving devices corresponding to the transmitting and receiving device.

8. The estimation system according to claim 7, wherein each of the Lm transceivers obtains a complex transfer function from any of the Lm transceivers using the MAC address.

9. The estimation system according to claim 7, wherein each of the Lm transmitting and receiving devices acquires a plurality of data in the time direction and synchronizes the signals between the Lm transmitting and receiving devices using at least one of the mean, median, moving mean, and moving median.

10. An estimation method performed by an estimation system for estimating the position of a living organism, wherein the estimation system comprises Lm (where Lm is a natural number of 1 or more) transmitting devices and Ln (where Ln is a natural number of 1 or more) receiving devices, where at least one of Lm and Ln is 2 or more, each of the Lm transmitting devices comprises: a transmitting signal generation unit that generates a multicarrier signal in which a plurality of subcarrier signals are modulated; a transmitting antenna unit having one or more transmitting antenna elements; and a transmitting unit that processes the multicarrier signal and outputs it to the transmitting antenna unit, thereby causing the transmitting antenna unit to transmit the multicarrier signal, the Lm transmitting devices have a total of M (where M is a natural number of 1 or more) transmitting antenna elements, each of the Ln receiving devices comprises: a receiving antenna unit having one or more receiving antenna elements; and a receiving unit that observes the received signal received by the one or more receiving antenna elements, which includes a reflected signal in which the multicarrier signal transmitted from the M transmitting antenna elements is reflected or scattered by the living organism, for a first period corresponding to a period derived from the activity of the living organism. The receiving unit includes a complex transfer function calculation unit that uses the received signal observed in the first period to calculate a complex transfer function representing the propagation characteristics between the M transmitting antenna elements and the one or more receiving antenna elements, for each of the multiple subcarriers to which the multiple subcarrier signals correspond, the Ln receiving devices receive the multicarrier signal without signal synchronization with each other, the estimation method calculates biological information based on the multiple complex transfer functions calculated in relation to a plurality of combinations of the M transmitting antenna elements and the total of N receiving antenna elements of the Ln receiving devices, the estimation method estimates the position of the living organism from the real or imaginary component of the biological information, the calculation of the biological information includes a first process of calculating a correlation matrix representing the correlation between a plurality of elements included in the first matrix based on the plurality of complex transfer functions corresponding to the plurality of combinations, and a second process of extracting biological components from either the plurality of complex transfer functions or the correlation matrix.

11. A program for causing a computer to execute the estimation method described in claim 10.

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