SENSOR AND POSITION ESTIMATION METHOD - Patent application

Abstract

A sensor (1) having: a biological component extraction unit (24-1, etc.) for receiving, by means of a reception antenna, a signal that was transmitted by a transmission station (10-1, etc.) and has been affected by a living body, and extracting, from the received signal, a signal component that has been affected by the living body; a position spectrum function computation unit (25-1) for calculating, from the signal component, a position spectrum function that corresponds to the likelihood of a position of the living body, said function being calculated up to the number of combinations of transmission stations (10-1, etc.) and reception stations (20-1, etc.); a weighting function computation unit (30) for calculating a weighting function that represents the reliability of the position spectrum function of the reception stations (20-1, etc.) at each set of coordinates within a measurement range, said function being calculated up to the number of combinations of the transmission stations (10-1, etc.) and the reception stations (20-1, etc.); an integrated position spectrum function computation unit (40) for outputting an integrated position spectrum function using the position spectrum function and the weighting function; and a position estimation unit (50) for detecting a local maximum value from the integrated position spectrum function to estimate the position of the living body.

Description

[Technical field]

[0001] The present disclosure relates to a sensor and a position estimation method, and more particularly to a sensor and a position estimation method for estimating the position of a living body by using a wireless signal. [Background technology]

[0002] Technologies have been developed for detecting targets by utilizing signals transmitted wirelessly (see, for example, Patent Document 1 and Non-Patent Document 1).

[0003] Patent Document 1 discloses that the position and state of a person to be detected can be known by analyzing components including Doppler shift using Fourier transform. In addition, Non-Patent Document 1 discloses a technology for estimating the position of a detection target by using fluctuation components extracted from propagation channel information and the MUSIC (MUltiple SIgnal Classification) method. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2015-117972 A [Patent Document 2] JP 2010-249712 A [Patent Document 3] JP 2007-155490 A [Patent Document 4] JP 2010-32442 A [Patent Document 5] Special Publication No. 2007-518968 [Patent Document 6] Special Publication No. 2012-524898 [Patent Document 7] JP 2018-112539 A [Patent Document 8] JP 2008-170386 A [Non-patent literature]

[0005] [Non-Patent Document 1] T.MIWA, S.OGIWARA,and Y.YAMAKOSHI, “Localization of Living-bodies using Single-frequency multistatic Doppler radar System,” IEICE Transactions on Communications, Vol.E92-B, No.7, pp.20468-2476, July 2009. Summary of the Invention [Problem to be solved by the invention]

[0006] However, the techniques disclosed in Patent Document 1 and Non-Patent Document 1 have a problem in that when the living body to be detected is stationary, the range in which the living body can be detected, that is, the detection range, becomes narrow.

[0007] The present disclosure has been made in consideration of the above-mentioned circumstances, and aims to provide a sensor and a position estimation method that can estimate the position of a living body over a wider range and with higher accuracy by using wireless signals. [Means for solving the problem]

[0008] A sensor according to one embodiment of the present disclosure is a sensor including one or more transmitting stations having a transmitting array antenna for transmitting signals and one or more receiving stations having a receiving array antenna for receiving signals, the sensor including: a biological component extraction unit that receives signals transmitted by the transmitting stations and influenced by a living body by the receiving array antenna, and extracts signal components influenced by the living body from the received signals; a position spectral function calculation unit that calculates position spectral functions corresponding to the likelihood of the position of the living body from the signal components, the number of which is equal to the number of combinations of the transmitting stations and the receiving stations; a weighting function calculation unit that calculates weighting functions indicating the reliability of the position spectral function of the receiving station at each coordinate within a measurement range, the number of which is equal to the number of combinations of the transmitting stations and the receiving stations; an integrated position spectral function calculation unit that outputs a position spectral function integrated using the position spectral function calculated by the position spectral function calculation unit and the weighting function calculated by the weighting function calculation unit; and a position estimation unit that detects a maximum value from the integrated position spectral function to estimate the position of the living body.

[0009] These comprehensive or specific aspects may be realized as a system, a method, an integrated circuit, a computer program, or a recording medium such as a computer-readable CD-ROM, or may be realized as any combination of a system, a method, an integrated circuit, a computer program, and a recording medium. Effect of the Invention

[0010] According to the sensor and the like of the present disclosure, the location of a living body can be estimated over a wider range and with higher accuracy by utilizing wireless signals. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a block diagram showing a configuration of a sensor according to an embodiment. [Diagram 2] FIG. 2 is a diagram showing an example of an arrangement of a transmitting station and a receiving station according to the embodiment. [Diagram 3] FIG. 3 is a diagram illustrating an example of a weighting function using a Rayleigh distribution according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of a weighting function using a normal distribution according to the embodiment. [Diagram 5] FIG. 5 is a flowchart showing a process of estimating a position of a sensor in the embodiment. [Figure 6] FIG. 6 is a flowchart showing details of the position estimation process shown in FIG. [Figure 7] FIG. 7 is a diagram showing an example of an arrangement of a transmitting station and a receiving station in the first modification of the embodiment. [Figure 8] FIG. 8 is a diagram showing an example of an arrangement of transmitting and receiving stations in the second modification of the embodiment. [Figure 9] FIG. 9 is a block diagram showing an example of a configuration of a sensor according to the second modification of the embodiment. In FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] (Findings on which this disclosure is based) Techniques have been developed for detecting a detection target by utilizing a signal transmitted wirelessly (see, for example, Patent Documents 1 to 6 and Non-Patent Document 1).

[0013] For example, Patent Documents 2 and 3 disclose a technique for calculating the presence or absence of an object and its moving direction by using a UWB (Ultra Wide Band) wireless signal. More specifically, a UWB wireless signal is transmitted to a predetermined area, and the wireless signal reflected by the object to be detected is received by an array antenna. Then, using the Doppler effect, only the signal from the moving object is separated, and the presence or absence of the moving object or its moving direction is calculated based on the separated signal.

[0014] Furthermore, for example, Patent Documents 4 and 5 disclose a technique for calculating the direction or position of a transmitter by performing direction of arrival estimation processing, which is one of the array antenna signal processing techniques, on the difference in reception timing when an antenna receives a UWB signal transmitted from a transmitter.

[0015] Also, for example, Patent Document 6 discloses a technology for estimating the position of an object using a direction estimation algorithm such as the MUSIC method. Specifically, a direction estimation algorithm such as the MUSIC method is applied to each of a plurality of receiving stations that receive a signal emitted by a transmitting station, and the results are integrated by multiplication or addition. This enables highly accurate direction estimation.

[0016] However, after detailed investigation, the inventors found that the techniques disclosed in Patent Documents 2 to 6 are not capable of performing highly accurate position estimation of a living body. That is, the methods of Patent Documents 2 to 3 can detect the presence or absence of a person, but cannot estimate the direction or position of the person. In addition, the techniques disclosed in Patent Documents 4 to 6 are position estimation techniques for a transmitter that emits radio waves, and cannot perform position estimation for a living body.

[0017] Patent Document 1 discloses a technique that can learn the position and state of a person to be detected by analyzing components including Doppler shift using Fourier transform. In addition, Non-Patent Document 1 discloses a technique that estimates the position of a detection target by using fluctuation components extracted from propagation channel information and the MUSIC method.

[0018] More specifically, in the technology disclosed in Patent Document 1 and Non-Patent Document 1, the propagation channel between the transmitting and receiving antennas is observed and the time series changes are recorded. Then, a Fourier transform process is performed on the propagation channel observed in time series, and the time response is converted into a frequency response. Here, since there are multiple transmitting and receiving antennas, the frequency response is a matrix whose elements are complex numbers. By applying a direction or position estimation algorithm such as the MUSIC method to this frequency response matrix, the direction or position of the target can be identified. Furthermore, Patent Document 1 shows that even if there are multiple targets, they can be detected simultaneously.

[0019] However, the technology disclosed in Patent Document 1 and Non-Patent Document 1 has a problem that in a situation where the Doppler effect is very weak, such as when the target living body is stationary, the detectable distance becomes short, and the detection range in which the living body can be detected becomes narrow. This is because, in a situation where the Doppler effect is very weak, it becomes difficult to detect a weak signal that has undergone a Doppler shift due to the influence of internal noise of the receiver, interference waves coming from sources other than the target, and the presence of objects that generate a Doppler shift other than the target. In addition, if the target living body is equipped with a special device such as a transmitter, it is possible to detect even a stationary living body.

[0020] Patent Document 7 discloses a technology for estimating the position of a living body using a direction estimation algorithm such as the MUSIC method. Specifically, a signal emitted by a transmitting station is reflected by a living body, and multiple receiving stations receive the reflected waves. Each receiving station extracts a fluctuation component including the Doppler shift caused by the living body from the received signal, applies a direction estimation algorithm such as the MUSIC method, and integrates the results by multiplication or addition. This enables highly accurate direction estimation.

[0021] However, the technology disclosed in Patent Document 7 has a problem that a false image is likely to be generated in a place where the location of the living body is not the true location of the living body. In areas close to the transmitting station and the receiving station, the reflected waves from the living body can be observed strongly, so the reliability of the estimation result is high, but the reliability decreases the further away the station is. However, when the results are integrated, the results of all the receiving stations are treated with the same weight, so that results with low reliability are mixed in.

[0022] In Patent Document 8, a value calculated from the relative position of each sensor and the target is used as a weight for integration, which was not taken into account in Patent Document 7. Specifically, the closer the sensor is to the target, the higher the weight is set since the reliability of the result is higher, and the weight is set smaller for the results of sensors farther away from the target, making them less likely to be reflected in the integration result.

[0023] However, the technology disclosed in Patent Document 8 cannot correctly integrate targets when multiple targets are present within the detection range. This is because it is not possible to distinguish whether the targets detected by each sensor are the same or different targets, and the number of targets can only be integrated as one.

[0024] In consideration of these circumstances, the inventors came up with a sensor or the like that can estimate the location of a living organism over a wider range and with higher accuracy by using wireless signals, without requiring the target organism to carry special equipment such as a transmitter.

[0025] A sensor according to one embodiment of the present disclosure is a sensor including one or more transmitting stations having a transmitting array antenna for transmitting signals and one or more receiving stations having a receiving array antenna for receiving signals, the sensor including: a biological component extraction unit that receives signals transmitted by the transmitting stations and influenced by a living body by the receiving array antenna, and extracts signal components influenced by the living body from the received signals; a position spectral function calculation unit that calculates position spectral functions corresponding to the likelihood of the position of the living body from the signal components, the number of which is equal to the number of combinations of the transmitting stations and the receiving stations; a weighting function calculation unit that calculates weighting functions indicating the reliability of the position spectral function of the receiving station at each coordinate within a measurement range, the number of which is equal to the number of combinations of the transmitting stations and the receiving stations; an integrated position spectral function calculation unit that outputs a position spectral function integrated using the position spectral function calculated by the position spectral function calculation unit and the weighting function calculated by the weighting function calculation unit; and a position estimation unit that detects a maximum value from the integrated position spectral function to estimate the position of the living body.

[0026] With this configuration, the position spectrum function obtained from the complex transfer functions calculated at multiple receiving stations is integrated using weights that take into account the positions of the transmitting station and receiving station, and the location of the living body can be estimated over a wider range and with higher accuracy using wireless signals. In areas close to the transmitting station and receiving station, the reflected waves from the living body are strongly observed, so the reliability of the estimation results is high, but the reliability decreases the further away the station is. Taking this into consideration, the weights of the position spectrum function obtained from the complex transfer functions at receiving stations that are close to the living body can be increased to accurately estimate the location of the living body.

[0027] For example, there may be multiple transmitting stations or multiple receiving stations, or there may be multiple both. If there are multiple transmitting stations, a step of controlling the transmission timing or transmission frequency of each station so that they do not overlap may be included. The weighting function and the position spectrum function may be integrated by multiplying or adding them together. The MUSIC (MUltiple SIgnal Classification) algorithm may be used to calculate the position spectrum function.

[0028] For example, the one or more transmitting stations may be two or more of the transmitting stations, or the one or more receiving stations may be two or more of the receiving stations.

[0029] For example, the one or more transmitting stations may be two or more of the transmitting stations, and the one or more receiving stations may be two or more of the receiving stations.

[0030] For example, the weighting function calculation unit may calculate the weighting function based on the coordinates and the positional relationship between a transmitting array antenna and a receiving array antenna.

[0031] For example, the weighting function calculation unit may calculate a Rayleigh distribution or a normal distribution as the weighting function.

[0032] For example, the one or more transmitting stations may be two or more transmitting stations that control the transmission timing or the transmission frequency so as not to transmit simultaneously from the transmitting array antenna.

[0033] For example, the integrated position spectral function calculation unit may integrate the calculated multiple position spectral functions and a weighting function into one function by multiplying or adding them together.

[0034] For example, the position spectral function calculation unit may calculate the position spectral function based on a MUSIC (MUltiple SIgnal Classification) algorithm, a Capon algorithm, or a beamformer algorithm.

[0035] Furthermore, a position estimation method according to one aspect of the present disclosure is a position estimation method executed by a sensor including one or more transmitting stations including a transmitting array antenna that transmits a signal and one or more receiving stations including a receiving array antenna that receives a signal, the position estimation method including the steps of: receiving a signal transmitted by the transmitting station and influenced by a living body by the receiving array antenna, and extracting a signal component influenced by the living body from the received signal; calculating a position spectral function corresponding to the likelihood of the position of the living body from the signal components, the number of times corresponding to the number of combinations of the transmitting station and the receiving station; calculating a weighting function indicating the reliability of the position spectral function of the receiving station at each coordinate within a measurement range, the number of times corresponding to the number of combinations of the transmitting station and the receiving station; outputting a position spectral function obtained by integrating the calculated position spectral function and the calculated weighting function; and detecting a local maximum from the integrated position spectral function to estimate the position of the living body.

[0036] The present disclosure may be realized not only as an apparatus, but also as an integrated circuit including a processing means included in such an apparatus, as a method having steps corresponding to the processing means constituting the apparatus, as a program for causing a computer to execute the steps, or as information, data, or signals indicating the program. These programs, information, data, and signals may be distributed via a recording medium such as a CD-ROM or a communication medium such as the Internet.

[0037] Hereinafter, the embodiments of the present disclosure will be described in detail with reference to the drawings. Note that each of the embodiments described below shows a preferred specific example of the present disclosure. The numerical values, shapes, materials, components, arrangement and connection forms of the components, steps, and order of steps shown in the following embodiments are merely examples and are not intended to limit the present disclosure.

[0038] In addition, among the components in the following embodiments, those components that are not described in the independent claims showing the highest concept of the present disclosure will be described as optional components constituting a more preferred embodiment. In addition, in this specification and drawings, components having substantially the same functional configurations are given the same reference numerals to avoid redundant description.

[0039] (Embodiment) Hereinafter, a method for estimating the position of the sensor 1 in the embodiment will be described with reference to the drawings.

[0040] [Sensor 1 Configuration] Fig. 1 is a block diagram showing a configuration of a sensor 1 according to an embodiment of the present invention, and Fig. 2 is a diagram showing an example of an arrangement of a transmitting station and a receiving station according to an embodiment of the present invention.

[0041] The sensor 1 shown in Fig. 1 includes M transmitting stations 10-1 to 10-M, a transmission timing control unit 15, N receiving stations 20-1 to 20-N, a weighting function calculation unit 30, an integrated position spectral function calculation unit 40, and a position estimation unit 50. Fig. 2 conceptually illustrates the arrangement of the transmitting stations 10-1 and 10-2, and the receiving stations 20-1 and 20-2, and how signals are transmitted when M is 2 and N is 2.

[0042] [Transmission station 10-1~10-M] Each of transmitting stations 10-1 to 10-M has a transmitting array antenna, where M is an integer equal to or greater than 1. A j-th transmitting station 10-j (j is an integer equal to or greater than 1 and equal to or less than M) will be described as a representative of the M transmitting stations. All transmitting stations 10-1 to 10-M have the same configuration and perform the same processing.

[0043] The transmitting station 10-j is composed of a transmitting unit 11-j and a transmitting antenna 12-j, as shown in Fig. 1. The transmitting unit 11-j is controlled by a transmission timing control unit 15 so as not to transmit a transmission wave simultaneously with other transmitting stations.

[0044] [Transmission timing control unit 15] The transmission timing control section 15 controls the transmission timing so that two or more transmitting stations 10-1 to 10-M do not transmit from the transmitting array antennas at the same time. Since it is only necessary to distinguish the transmission signals of each transmitter, different frequencies may be assigned instead of controlling the transmission timing, or when antennas with limited directivity are used in a sufficiently wide space, antennas that are sufficiently far apart may transmit simultaneously. Also, time division multiplexing or frequency multiplexing, CSMA / CA (Carrier Sense Multiple Access / Collision Avoidance), CSMA / CD (Carrier Sense Multiple Access / Collision Detection), etc. may be used, as in wireless communication such as wireless LAN (Local Area Network).

[0045] The transmitting antenna 12-j is M T A transmitting antenna with elements, namely, M T It is composed of transmitting antenna elements.

[0046] The transmitter 11-j generates a high-frequency (e.g., microwave) signal (e.g., a CW (Continuous Wave) or OFDM (Orthogonal Frequency Division Multiplexing) signal) used to estimate the position of the living body 100. For example, as shown in Fig. 2, the transmitter 11-j transmits the generated signal as a transmission wave from a transmission antenna 12-j.

[0047] [Receiving stations 20-1 to 20-N] Each of the receiving stations 20-1 to 20-N has a receiving array antenna, where N is an integer equal to or greater than 2. The following description will be given taking as an example the i-th receiving station 20-i (i is an integer equal to or greater than 1 and equal to or less than N) as a representative of the N receiving stations. All of the receiving stations 20-1 to 20-N have the same configuration and perform the same processing.

[0048] The receiving station 20-i includes a receiving antenna 21-i, a receiving section 22-i, a complex transfer function calculating section 23-i, a biological component extracting section 24-i, and a position spectral function calculating section 25-i.

[0049] <Receiving antenna 21-i> The receiving antenna 21-i is M R A receiving antenna with elements, namely, M R The receiving antenna 21-i is a receiving array antenna composed of receiving antenna elements. The receiving antenna 21-i receives a high-frequency (e.g., microwave) signal (e.g., CW or OFDM signal) by the receiving array antenna. In this embodiment, depending on the arrangement of the receiving antenna 21-i, the high-frequency signal received may include a reflected wave, which is a signal that is a part of the transmission wave transmitted from the transmitting antenna 12-j and reflected by the living body 100, as shown in FIG. 2, for example.

[0050] <Receiving unit 22-i> The receiver 22-i converts the high-frequency signal received by the receiver antenna 21-i into a low-frequency signal that can be processed. The receiver 22-i transmits the converted low-frequency signal to the complex transfer function calculator 23-i.

[0051] <Complex transfer function calculation unit 23-i> The complex transfer function calculation unit 23-i calculates a complex transfer function representing the propagation characteristics between the receiving array antenna of the receiving station 20-i and the transmitting antenna 12-j of the transmitting station 10-j from a signal observed at the receiving array antenna of the receiving station 20-i. More specifically, the complex transfer function calculation unit 23-i calculates a complex transfer function representing the propagation characteristics between one transmitting antenna element of the transmitting antenna 12-j and M of the receiving array antenna from a low-frequency signal transmitted by the receiving unit 22-i. R The complex transfer function calculating unit 23-i calculates a complex transfer function representing a propagation characteristic between the transmitting antenna 12-j and each of the receiving antenna elements. The complex transfer function calculated by the complex transfer function calculating unit 23-i includes a direct wave from the transmitting antenna 12-j and a reflected wave from a fixed object, which does not pass through the living body 100.

[0052] Furthermore, the complex transfer function calculated by the complex transfer function calculation unit 23-i may include a reflected wave, which is a signal obtained by reflecting a part of the transmission wave transmitted from the transmitting antenna 12-j by the living body 100. The amplitude and phase of the reflected wave reflected by the living body 100, i.e., the reflected wave via the living body 100, constantly fluctuates due to biological activities such as breathing and heartbeat of the living body 100.

[0053] In the following description, it is assumed that the complex transfer function calculated by the complex transfer function calculation unit 23-i includes a reflected wave, which is a signal reflected by the living body 100.

[0054] <Biomechanical component extraction unit 24-i> The biocomponent extracting unit 24-i extracts biocomponents, which are signal components transmitted from the transmitting antenna 12-j and reflected by one or more living bodies 100, from the signals observed by the receiving array antenna of the receiving station 22-i. More specifically, the biocomponent extracting unit 24-i records the complex transfer functions calculated by the complex transfer function calculating unit 23-i in a time series in the order in which the signals were observed. Then, the biocomponent extracting unit 24-i extracts, as the biocomponent, fluctuation components due to the influence of the living body 100 from the changes in the complex transfer functions recorded in time series.

[0055] Here, the method of extracting the fluctuation component due to the influence of the living body includes a method of extracting only the component corresponding to the vibration of the living body after conversion to the frequency domain by Fourier transform or the like, or a method of extracting by calculating the difference between the complex transfer functions at two different times. By these methods, the complex transfer functions of the direct wave and the reflected wave via the fixed object are removed, and only the complex transfer function component of the reflected wave via the living body 100 remains.

[0056] In this embodiment, the receiving antenna array is made up of M R Therefore, the number of fluctuation components of the complex transfer function corresponding to the receiving array antenna passing through the living body 100, that is, the living body components, is also multiple. Hereinafter, these are collectively referred to as a living body component channel matrix.

[0057] <Position Spectral Function Calculation Unit 25-i> The position spectral function calculation unit 25-i calculates a position spectral function, which is an evaluation function for the position of one or more living bodies 100 as seen from the receiving station 20-i, from the biocomponent extracted by the biocomponent extraction unit 24-i. Here, for example, the position spectral function calculation unit 25-i may calculate the position spectral function based on the MUSIC algorithm.

[0058] In this embodiment, the position spectral function calculation unit 25-i calculates a correlation matrix R i,j Calculate the correlation matrix Ri,j Using a predetermined direction of arrival estimation method, a position spectrum function P i,j Calculate (X).

[0059] The position spectral function calculation unit 25-i calculates the position spectral function P i,j (X) is transmitted to the integrated position spectral function calculation unit 40.

[0060] Hereinafter, the position spectral function calculation unit 25-i calculates the position spectral function P i,j The procedure for calculating (X) will be explained using formulas. It is assumed that the biological components are extracted using Fourier transform.

[0061] M R ×M T The biological component channel matrix H(f) can be expressed as (Equation 1). This biological component channel vector is expressed as M R M T Convert the vector into a 1× biocomponent channel vector.

[0062]

number

[0063]

number

[0064] Here, [·]T denotes the transpose of a matrix.

[0065] The correlation matrix R of the biological component channel vectors obtained in this way i is calculated as shown in (Equation 3).

[0066]

number

[0067] Here, E[·] represents the average calculation in the frequency direction, and f1 and f2 are the lower and upper limits of the frequencies at which the effects of biological activity appear, respectively.

[0068] The correlation matrix R of the biological component channel vectors obtained in this way i By performing eigenvalue decomposition, it can be written as the following (Equation 4) to (Equation 6).

[0069]

number

[0070]

number

[0071]

number

[0072] Here, [·]H represents the complex conjugate transpose, and Ui has M elements. R ×M T eigenvector, Λ i,j are the eigenvalues ​​corresponding to the eigenvectors,

number

[0073] The steering vector, i.e., the direction vector, of the receiving array antenna can be defined by (Equation 7).

[0074]

number

[0075] Here, k is the wave number and d is the element spacing of the receiving array antenna. Similarly, the steering vector of the transmitting array antenna can be defined by (Equation 8).

[0076]

number

[0077] Furthermore, the steering vectors for transmission and reception are multiplied together to define a steering vector that takes into account the angle information for both transmission and reception, as shown in (Equation 9).

[0078]

number

[0079] Here, X is the coordinate of a point within the measurement range of the sensor. Functions Θt and Θr are functions for calculating the angle between the coordinate X and the transmitting antenna 12-j, and the angle between the coordinate X and the receiving antenna 21-i, respectively. vec[·] is a transformation for rearranging a matrix of M rows and N columns into a vector of M×N elements. In this embodiment, an example of an equally spaced array antenna is shown, but the steering vector can be calculated in the same way from the arrangement information of elements for other array antennas. Also, a value obtained by actual measurement may be used instead of a value obtained by calculation.

[0080] In the MUSIC method, this steering vector is used to calculate the position spectrum function P i,j Calculate (X).

[0081]

number

[0082] Position spectrum function P i,j The denominator of (X) is minimum and takes a maximum value at the position where a living body is present as viewed from the j-th transmitting station 10-j and the i-th receiving station 20-i.

[0083] The position spectrum function may be calculated using the beamformer method or the Capon method instead of the MUSIC method.

[0084] [Weighting function calculation part 30] The weighting function calculation unit 30 calculates a weighting function f(d i,j ) where d i,j is the sum of the distance between the position X and the transmitting antenna and the distance between the position X and the receiving antenna minus the distance between the transmitting antenna and the receiving antenna. The function f is the position spectrum function P i,j It is a weighting function that expresses the reliability of position X of (X), and basically, the closer position X is to the transmitting antenna and the receiving antenna, the closer it is to "1", and the farther it is, the closer it is to "0". For example, the weighting function uses the Rayleigh distribution expressed by (Equation 11) or the normal distribution expressed by (Equation 12).

[0085]

number

[0086]

number

[0087] FIG. 3 shows a conceptual diagram of a weighting function using a Rayleigh distribution. The shaded area 200 is an area where the value of the weighting function is larger than a certain value, and is an area where the measurement result is highly reliable. Basically, the weighting function value is large in areas close to the transmitting antenna 10 and the receiving antenna 20, but the weighting function value is small in an area 201 on the line connecting the transmitting antenna 10 and the receiving antenna 20. This is because, on this line, the angle between the line connecting the transmitting antenna and the receiving antenna, and the line connecting the transmitting antenna and the living body in the area 201 is small, resulting in a decrease in measurement accuracy. FIG. 4 shows a conceptual diagram of a weighting function when a normal distribution is used.

[0088] [Integrated Position Spectral Function Calculation Part 40] The integrated position spectral function calculation unit 40 is transmitted N×M position spectral functions calculated by each of the N position spectral function calculation units 25-1 to 25-N, where N is multiplied by M, and the weighting function calculated by the weighting function calculation unit 30. The integrated position spectral function calculation unit 40 integrates the multiple position spectral functions calculated by each of the position spectral function calculation units 25-1 to 25-N into one function. Here, the integrated position spectral function calculation unit 40 integrates the multiple calculated position spectral functions into one function by multiplying or adding them together after taking into account a weighting function determined from the positions of the transmitting antenna and the receiving antenna.

[0089] In this embodiment, the integrated position spectral function calculation unit 40 calculates (N×M) position spectral functions P i,j More specifically, the integrated position spectral function calculation unit 40 integrates the position spectral functions P i,j Then, the integrated position spectral function calculation unit 40 obtains the obtained N×M position spectral functions P i,j (X) integrated position spectrum function P all Calculate (X).

[0090]

number

[0091] These weighting functions are called the position spectrum function P i,j By multiplying by (X) and then taking the sum, it is possible to extract and integrate only the most reliable position spectrum functions.

[0092] In addition, each position spectrum function P i,j(X) has a maximum value at the angle where the living body 100 is located as seen from the corresponding receiving station 20-i, but its value does not become 0 at any other angle including directions outside the measurement range. Therefore, by multiplying N×M position spectrum functions, an evaluation function that reflects the results of all N×M combinations of transmitting stations and receiving stations, i.e., an integrated position spectrum function P all (X) can be obtained. Note that although the sum is used to integrate the position spectrum functions here, they may also be multiplied together.

[0093] [Position estimation unit 50] The position estimation unit 50 estimates the integrated position spectral function P all By searching for the maximum value of (X), the position of the living body 100, which is the direction of the arriving wave, is estimated.

[0094] [Sensor 1 operation] The process of estimating the position of a living body by the sensor 1 configured as above will be described.

[0095] Fig. 5 is a flowchart showing a position estimation process of the sensor 1 in an embodiment that is an example of the present disclosure, and Fig. 6 is a flowchart showing details of the position estimation process shown in Fig. 5.

[0096] First, as shown in Fig. 5, the sensor 1 extracts a biological component, which is a signal component transmitted from a transmitting antenna element of a transmitting station 10-j among M transmitting stations and reflected by one or more living bodies, from a signal observed by the receiving array antenna of each of the multiple receiving stations 20-1 to 20-N (step S1). More specifically, as shown in Fig. 6, the sensor 1 first observes the received signals at the N receiving stations for a predetermined period (step S11).

[0097] Next, the sensor 1 calculates a complex transfer function from each of the received signals observed by the receiving array antennas of the N receiving stations (step S12).The sensor 1 then records each of the calculated complex transfer functions in time series, and extracts a biological component from each of the recorded time series complex transfer functions (step S13).

[0098] Next, as shown in Fig. 5, the sensor 1 calculates position spectral functions, which are evaluation functions for the positions of one or more living bodies 100 as seen from each of the multiple receiving stations 20-1 to 20-N, from each of the living body components extracted in step S1, for (N x M) positions, which is the number of combinations of the transmitting station and the receiving station (step S2). More specifically, as shown in Fig. 6, the sensor 1 first calculates a correlation matrix for each of the living body components extracted in step S13 (step S21). Next, the sensor 1 calculates a position spectral function of the living body 100 as seen from each of the N receiving stations using the correlation matrix calculated in step S21 (step S22).

[0099] Next, the sensor 1 calculates a weighting function for each combination of M transmitting stations and N transmitting stations (step S3), as shown in Fig. 5. This weighting function is a function that indicates the reliability of the position spectrum function, and the weight decreases as the position becomes farther from the antenna. Functions that can be used as the weighting function include a Rayleigh distribution and a normal distribution.

[0100] Next, as shown in Fig. 5, the sensor 1 integrates the multiple position spectral functions calculated in step S2 into one integrated position spectral function using the weighting function calculated in step S3 (step S4). More specifically, the sensor 1 multiplies the position spectral function calculated in step S3 by the weighting function of the corresponding combination of the transmitting station and the receiving station calculated in step S4, and calculates the sum for all combinations of the transmitting station and the receiving station to calculate the integrated position spectral function.

[0101] Finally, the sensor 1 estimates the positions of one or more living organisms 100 by calculating one or more maximum values ​​of the integrated position spectral function calculated in step S4 as shown in FIG. 5 (step S5).

[0102] [Effects, etc.] According to the sensor 1 and the position estimation method of the present embodiment, the position of the living body can be estimated in a wider range and with higher accuracy by using a wireless signal. Also, according to the sensor 1 and the position estimation method of the present embodiment, by providing a plurality of receiving stations, the detection range in which the living body can be detected can be widened.

[0103] More specifically, according to the sensor 1 and the position estimation method of the present embodiment, a biological component is extracted from information of a complex transfer function obtained by a plurality of receiving stations, and a position spectrum function calculated from the extracted biological components is integrated to estimate the position of the biological component. This makes it possible to estimate the position of the biological component over a wider range without being affected by obstacles.

[0104] For example, even if the signal from the target living organism is weak and some of the multiple receiving stations are unable to observe the reflected wave from the living organism, the living organism's position can be estimated using the position spectrum function obtained from the complex transfer function at the receiving station that was able to observe the reflected wave from the living organism.

[0105] (Variation 1) Fig. 7 is a conceptual diagram showing a first modified example of the arrangement of the sensor 1 in the embodiment. In the embodiment, the case where the transmitting antenna 12-j and the receiving antenna 21-i are equally-spaced array antennas has been described as an example, but the antennas used are not limited to equally-spaced array antennas. For example, by arranging antenna elements in a circle as shown in Fig. 7, the directivity of the antenna can be directed in all directions, and the measurement range of the sensor can be expanded. For example, even if a living body is outside the area surrounded by the antennas, such as the living body 100-2 in Fig. 7, the position can be correctly estimated.

[0106] (Variation 2) Fig. 8 is a conceptual diagram showing a second modification of the arrangement of the sensor 1 in the embodiment, and Fig. 9 is a block diagram showing an example of the configuration of a sensor 1A in this modification 2.

[0107] In the embodiment, the transmitting antenna 12-j and the receiving antenna 21-i are arranged at different positions, but they may share the same physical antenna and be arranged as in the transmitting / receiving stations 310-1 to 310-4 in FIG. 8. Many actual wireless devices share a transmitting antenna and a receiving antenna, and such a configuration allows sensing to be performed by reusing the hardware of the wireless device. In addition, the signals transmitted by the transmitting / receiving stations 310-1 to 310-4 may be signals used for wireless communication such as wireless LAN. In the embodiment, one transmission timing control unit controls M transmitting units, but as shown in FIG. 9, M transmission timing control units 15A-1 to 15A-M may control the transmitting units 11-1 to 11-M, respectively.

[0108] Moreover, the receiving station does not need to include all of the complex transfer function calculation unit 23-i, the biometric information extraction unit 24-i, and the position spectral function calculation unit 25-i, and may transmit data to, for example, an external server 401 and perform calculations in the external server 401. Moreover, the position spectral function may be transmitted to one receiving station, and the integrated position spectral function may be calculated in the receiving station.

[0109] In the above-mentioned embodiment and modified examples, each component may be configured with dedicated hardware, or may be realized by executing a software program suitable for each component. Each component may be realized by a program execution unit such as a CPU or a processor reading and executing a software program recorded on a recording medium such as a hard disk or a semiconductor memory. Here, the software for realizing the devices of the above-mentioned embodiment and modified examples is a program such as the following.

[0110] That is, this program causes a computer to execute a position estimation method performed by a sensor having one or more transmitting stations equipped with a transmitting array antenna for transmitting signals and having one or more receiving stations equipped with a receiving array antenna for receiving signals, the position estimation method including the steps of: receiving signals transmitted by the transmitting stations and influenced by a living body by the receiving array antenna, and extracting signal components influenced by the living body from the received signals; calculating position spectral functions corresponding to the likelihood of the position of the living body from the signal components, the number of which is equal to the number of combinations of the transmitting stations and the receiving stations; calculating weighting functions representing the reliability of the position spectral function of the receiving station at each coordinate within a measurement range, the number of which is equal to the number of combinations of the transmitting stations and the receiving stations; outputting a position spectral function obtained by integrating the calculated position spectral function and the calculated weighting function; and detecting a maximum value from the integrated position spectral function to estimate the position of the living body.

[0111] Although the sensor and the position estimation method according to one aspect of the present disclosure have been described based on the embodiments, the present disclosure is not limited to these embodiments. As long as it does not deviate from the gist of the present disclosure, various modifications conceived by a person skilled in the art to the present embodiment or a form constructed by combining components in different embodiments are also included in the scope of the present disclosure.

[0112] The present disclosure can be realized not only as a sensor having such characteristic components, but also as a position estimation method in which the characteristic components included in the sensor are included as steps. It can also be realized as a computer program that causes a computer to execute each of the characteristic steps included in such a method. It goes without saying that such a computer program can be distributed on a non-transitory computer-readable recording medium such as a CD-ROM or via a communication network such as the Internet. [Industrial Applicability]

[0113] The present disclosure can be used in sensors and position estimation methods that estimate the position of a living body using wireless signals, and in particular in sensors and position estimation methods installed in measuring instruments that measure the direction or position of a living body, home appliances that perform control according to the direction or position of a living body, and monitoring devices that detect the intrusion of a living body. [Explanation of symbols]

[0114] 1, 1A sensor 10, 12-1~12-M Transmitting Antenna 10-1~10-M, 10A-1~10A-M transmitting station 11-1~11-M Transmitter 15, 15A-1 to 15A-M Transmission timing control section 20, 21-1~21-N Receiving antenna 20-1~20-N, 20A-1~20A-N receiving station 22-1~22-N Receiver 23-1~23-N Complex transfer function calculation section 24-1~24-N Biological component extraction section 25-1~25-N Position spectrum function calculation section 30 Weighting function calculation unit 40 Integrated position spectrum function calculation unit 50 Position estimation part 100, 100-1, 100-2 Living organism 200, 201 area 310-1, 310-2, 310-3, 310-4 Transmitting and receiving stations 401 External Server

Claims

1. A sensor including one or more transmitting stations having a transmitting array antenna for transmitting a signal, and two or more receiving stations having a receiving array antenna for receiving the signal, a biological component extraction unit that receives a signal transmitted by the transmitting station and influenced by a living body by the receiving array antenna, and extracts a signal component influenced by the living body from the received signal; a position spectral function calculation unit that calculates a position spectral function corresponding to the likelihood of the position of the living body from the signal components, the number of which corresponds to the number of combinations of the transmitting station and the receiving station; a weighting function calculation unit that calculates weighting functions representing reliability of a position spectrum function of the receiving station at each coordinate within a measurement range based on a distance between the living body and the transmitting array antenna and a distance between the living body and the receiving array antenna, the weighting functions being equal to the number of combinations of the transmitting station and the receiving station; an integrated position spectral function calculation unit that outputs a position spectral function that is integrated using the position spectral function calculated by the position spectral function calculation unit and the weighting function calculated by the weighting function calculation unit; a position estimation unit that detects a maximum value from the integrated position spectral function to estimate a position of the living body; A sensor having

2. The one or more transmitting stations are two or more transmitting stations. The sensor of claim 1 .

3. the weighting function calculation unit calculates the weighting function based on the coordinates and a positional relationship between a transmitting array antenna and a receiving array antenna. The sensor according to claim 1 or 2.

4. The weighting function calculation unit calculates a Rayleigh distribution or a normal distribution as the weighting function. The sensor according to any one of claims 1 to 3.

5. The one or more transmitting stations are two or more transmitting stations that control a transmission timing or a transmission frequency so as not to transmit from the transmitting array antennas simultaneously. The sensor according to any one of claims 1 to 4.

6. The integrated position spectral function calculation unit integrates the calculated position spectral functions and a weighting function into one function by multiplying or adding them together. The sensor according to any one of claims 1 to 5.

7. The position spectrum function calculation unit calculates the position spectrum function based on a MUSIC (Multiple Signal Classification) algorithm, a Capon algorithm, or a beamformer algorithm. The sensor according to any one of claims 1 to 6.

8. A position estimation method executed by a sensor including one or more transmitting stations having a transmitting array antenna for transmitting a signal and two or more receiving stations having a receiving array antenna for receiving the signal, the method comprising: receiving a signal transmitted by the transmitting station and influenced by a living body by the receiving array antenna, and extracting a signal component influenced by a living body from the received signal; calculating a position spectral function corresponding to a likelihood of a position of the living body from the signal components, the number of which corresponds to the number of combinations of the transmitting station and the receiving station; calculating weighting functions representing reliability of a position spectrum function of the receiving station at each coordinate within a measurement range based on a distance between the living body and the transmitting array antenna and a distance between the living body and the receiving array antenna, the weighting functions being equal to the number of combinations of the transmitting station and the receiving station; a step of outputting a position spectral function integrated using the calculated position spectral function and the calculated weighting function; detecting a maximum value from the integrated position spectral function to estimate the position of the living body; A location estimation method comprising:

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