Sensor and Position Estimation Method

Abstract

The sensor (1) includes: a biological component extraction unit (such as 24-1), which receives, through a receiving array antenna, a signal transmitted by a transmitting station (such as 10-1) and affected by a living body, and extracts a signal component affected by the living body from the received signal; a position spectrum function calculation unit (25-1), which calculates, based on the above signal component, a corresponding number of position spectrum functions corresponding to the likelihood of the position of the living body, the number of the position spectrum functions being the same as the number of combinations between the transmitting station (such as 10-1) and the receiving station (such as 20-1); a weight function calculation unit (30), which calculates a corresponding number of weight functions, the number of the weight functions being the same as the number of combinations between the transmitting station (such as 10-1) and the receiving station (such as 20-1), the weight functions representing the reliability of the position spectrum function of the receiving station (such as 20-1) at each coordinate within the measurement range; a comprehensive position spectrum function calculation unit (40), which outputs a comprehensively combined position spectrum function using the position spectrum function and the weight function; and a position estimation unit (50), which detects a maximum value from the comprehensively combined position spectrum function and estimates the position of the living body.

Description

Technical Field

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

[0002] Techniques for detecting a detection target using signals transmitted wirelessly are being developed (for example, refer to Patent Document 1 and Non-Patent Document 1).

[0003] In Patent Document 1, it is disclosed that the position or state of a person who is the detection target can be known by analyzing components including Doppler shift using Fourier transform. In addition, in Non-Patent Document 1, a technique for estimating the position of a detection target by using a variation component extracted from propagation channel information and the MUSIC (MUltiple SIgnal Classification) method is disclosed.

[0004] Prior Art Documents

[0005] Patent Documents

[0006] Patent Document 1: Japanese Unexamined Patent Application Publication No. 2015-117972

[0007] Patent Document 2: Japanese Unexamined Patent Application Publication No. 2010-249712

[0008] Patent Document 3: Japanese Unexamined Patent Application Publication No. 2007-155490

[0009] Patent Document 4: Japanese Unexamined Patent Application Publication No. 2010-32442

[0010] Patent Document 5: Japanese Patent Application Laid-Open No. 2007-518968

[0011] Patent Document 6: Japanese Patent Application Laid-Open No. 2012-524898

[0012] Patent Document 7: Japanese Unexamined Patent Application Publication No. 2018-112539

[0013] Patent Document 8: Japanese Unexamined Patent Application Publication No. 2008-170386

[0014] Non-Patent Documents

[0015] 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

[0016] Problems to be Solved by the Invention

[0017] However, in the technologies disclosed in Patent Document 1 and Non-Patent Document 1, in the case where the living body to be detected is stationary or the like, there are the following problems: the range in which the living body can be detected, that is, the detection range, becomes narrow.

[0018] The present disclosure has been made in view of the above circumstances, and an object thereof is to provide a sensor and a position estimation method capable of estimating the position where a living body exists with a wider range and higher accuracy using a wireless signal.

[0019] Means for Solving the Problems

[0020] The sensor according to one aspect of the present disclosure includes one or more transmitting stations and one or more receiving stations. The transmitting station includes a transmitting array antenna that transmits a signal, and the receiving station includes a receiving array antenna that receives a signal. In the sensor, it includes: a living body component extraction unit that receives, through the receiving array antenna, the signal transmitted by the transmitting station and affected by the living body, and extracts the signal component affected by the living body from the received signal; a position spectrum function calculation unit that calculates, based on the signal component, a number of position spectrum functions corresponding to the number of combinations between the transmitting station and the receiving station, the position spectrum function corresponding to the likelihood of the position of the living body; a weight function calculation unit that calculates a number of weight functions corresponding to the number of combinations between the transmitting station and the receiving station, the weight function indicating the reliability of the position spectrum function of the receiving station at each coordinate within the measurement range; a comprehensive position spectrum function calculation unit that outputs a comprehensively synthesized position spectrum function using the position spectrum function calculated by the position spectrum function calculation unit and the weight function calculated by the weight function calculation unit; and a position estimation unit that estimates the position of the living body by detecting a maximum value from the comprehensively synthesized position spectrum function.

[0021] In addition, these included or specific manners can also be implemented by a system, a method, an integrated circuit, a computer program, or a recording medium such as a computer-readable CD-ROM, or can also be implemented by any combination of a system, a method, an integrated circuit, a computer program, and a recording medium.

[0022] Advantages of the Invention

[0023] According to the sensor etc. of the present disclosure, it is possible to estimate the position where a living body exists with a wider range and higher accuracy by using a wireless signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a block diagram showing the structure of the sensor in the embodiment.

[0025] Figure 2 It is a diagram showing an example of the configuration of the transmitting station and the receiving station in the embodiment.

[0026] Figure 3 It is a diagram showing an example of the weight function using the Rayleigh distribution in the embodiment.

[0027] Figure 4 It is a diagram showing an example of the weight function using the normal distribution in the embodiment.

[0028] Figure 5 It is a diagram showing a flowchart of the position estimation process of the sensor in the embodiment.

[0029] Figure 6 It shows Figure 5 a flowchart showing details of the position estimation process shown.

[0030] Figure 7 It is a diagram showing an example of the configuration of the transmitting station and the receiving station in Modification 1 of the embodiment.

[0031] Figure 8 It is a diagram showing an example of the configuration of the transmitting and receiving station in Modification 2 of the embodiment.

[0032] Figure 9 It is a block diagram showing an example of the structure of the sensor in Modification 2 of the embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] (Knowledge and Insights Underlying the Present Disclosure)

[0034] Techniques for detecting a detection object using signals transmitted wirelessly are being developed (for example, refer to Patent Documents 1 to 6 and Non-Patent Document 1).

[0035] For example, in Patent Documents 2 to 3, a technique is disclosed for calculating the presence or absence of an object and its moving direction using a wireless signal of UWB (Ultra Wide Band). More specifically, a UWB wireless signal is transmitted to a specified area, and the wireless signal reflected by an object to be detected is received by an array antenna. Then, using the Doppler effect, only the signal from a moving object is separated, and based on the separated signal, the presence or absence of a moving object or its moving direction is calculated.

[0036] In addition, for example, in Patent Documents 4 to 5, the following technique is disclosed: By performing direction-of-arrival estimation processing, which is one of the array antenna signal processing techniques, on the difference in reception timing of the UWB signal received by an antenna from a transmitter, the direction or position of the transmitter is calculated.

[0037] In addition, for example, in Patent Document 6, a technique for estimating the position of an object using a direction estimation algorithm such as the MUSIC method is disclosed. Specifically, in each of a plurality of receiving stations that receive the signal emitted from a transmitting station, a direction estimation algorithm such as the MUSIC method is applied, and the results are combined by multiplication or addition. Thereby, highly accurate direction estimation can be performed.

[0038] However, as a result of detailed research by the inventors, it is known that in the techniques disclosed in Patent Documents 2 to 6, highly accurate estimation of the position of a living body cannot be performed. That is, it is known that in the methods of Patent Documents 2 to 3, the presence or absence of a person can be detected, but the direction or position where the person exists cannot be estimated. In addition, it is known that 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 on a living body.

[0039] In Patent Document 1, the following technique is disclosed: The position and state of a person to be detected can be known by analyzing components including Doppler shift using Fourier transform. In addition, in Non-Patent Document 1, a technique for estimating the position of a detection object is disclosed by using a variation component extracted from propagation channel information and the MUSIC method.

[0040] More specifically, in the techniques disclosed in Patent Document 1 and Non-Patent Document 1, the propagation channel between the transmitting and receiving antennas is observed, and its time-series change is recorded. Then, Fourier transform processing is performed on the propagation channel observed in time series, and the time response is transformed into a frequency response. Here, since both the transmitting and receiving antennas are multiple, the elements of the frequency response become a complex matrix. By applying a direction or position estimation algorithm such as the MUSIC method to this frequency response matrix, the direction or position of the object can be determined. Furthermore, in Patent Document 1, it is shown that even if there are multiple objects, they can be detected simultaneously.

[0041] However, in the technologies disclosed in Patent Document 1 and Non-Patent Document 1, in a situation where the Doppler effect is very weak, such as when the living body being detected is stationary, the detectable distance becomes short, so there is a problem that the detection range capable of detecting the living body becomes narrow. This is because, in a situation where the Doppler effect is very weak, affected by the internal noise of the receiver, interference waves coming from outside the detection object, and the presence of an object that causes a Doppler shift outside the detection object, it is difficult to detect a weak signal undergoing a Doppler shift. In addition, if the living body to be targeted holds a special device such as a transmitter, even a stationary living body can be detected.

[0042] In Patent Document 7, a technique for estimating the position of a living body using a direction estimation algorithm such as the MUSIC method is disclosed. Specifically, multiple receiving stations respectively receive the reflected waves obtained by the living body reflecting the signals transmitted by the transmitting station. At each receiving station, a variation component including a Doppler shift based on the living body is extracted from the received signal, and a direction estimation algorithm such as the MUSIC method is applied, and the results are combined by multiplication or addition. Thereby, high-precision direction estimation can be performed.

[0043] However, in the technology disclosed in Patent Document 7, there are the following problems: At a location that is not the true position of the living body, virtual images that are estimated to be the position of the living body are likely to appear. In the area near the transmitting station and the receiving station, the reflected waves based on the living body can be observed strongly, so the reliability of the estimation result is high, but the reliability decreases as the distance increases. However, when combining the results, the results of all receiving stations are processed with the same weight, so the results with low reliability are mixed in.

[0044] In Patent Document 8, as a weight for combination that was not considered in Patent Document 7, a value obtained based on the relative position between each sensor and the object is used. Specifically, the closer the distance between the sensor and the object, the higher the reliability of the result, so the weight is increased, and for the result of the sensor with a long distance from the object, its reflection on the combined result is made difficult by reducing the weight.

[0045] However, in the technology disclosed in Patent Document 8, accurate combination cannot be performed when multiple objects exist in the detection range. This is because it is impossible to distinguish whether the objects detected by each sensor are the same or different objects, and the number of objects can only be combined as one.

[0046] Therefore, in view of these, the inventors came up with a sensor or the like that can estimate the position where a living body exists with a wider range and higher accuracy using wireless signals without making the living body to be targeted hold a special device such as a transmitter.

[0047] A sensor according to an aspect of the present disclosure includes one or more transmitting stations and one or more receiving stations. The transmitting station includes a transmitting array antenna that transmits a signal, and the receiving station includes a receiving array antenna that receives a signal. In the sensor, it includes: a biological component extraction unit that receives, through the receiving array antenna, a signal transmitted by the transmitting station and affected by a living body, and extracts a signal component affected by the living body from the received signal; a position spectrum function calculation unit that calculates a corresponding number of position spectrum functions according to the signal component, where the number of position spectrum functions corresponds to the number of combinations between the transmitting station and the receiving station, and the position spectrum function corresponds to the likelihood of the position of the living body; a weight function calculation unit that calculates a corresponding number of weight functions according to the number of combinations between the transmitting station and the receiving station, where the weight function represents the reliability of the position spectrum function of the receiving station at each coordinate within the measurement range; a comprehensive position spectrum function calculation unit that outputs a comprehensively synthesized position spectrum function using the position spectrum function calculated by the position spectrum function calculation unit and the weight function calculated by the weight function calculation unit; and a position estimation unit that estimates the position of the living body by detecting a maximum value from the comprehensively synthesized position spectrum function.

[0048] With this structure, the position spectrum function obtained from the complex transfer function obtained by multiple receiving stations is comprehensively synthesized and estimated using weights considering the positions of the transmitting station and the receiving station. Therefore, the position where a living body exists can be estimated with a wider range and higher accuracy using wireless signals. In the area close to the transmitting station and the receiving station, the reflected wave based on the living body can be strongly observed, so the reliability of the estimation result is high, but the reliability decreases as the distance increases. Considering this situation, by increasing the weight of the position spectrum function obtained from the complex transfer function in the receiving station closer to the living body, the position of the living body can be accurately estimated.

[0049] For example, either the transmitting station or the receiving station can be multiple, or both can be set to multiple. In addition, when the transmitting station is multiple, it may include a step of controlling so that the respective transmission timings or transmission frequencies do not overlap. In addition, the synthesis of the weight function and the position spectrum function can also be performed by multiplying or adding them to each other. In addition, the MUSIC (MUltiple SIgnal Classification) algorithm can also be used in the calculation of the position spectrum function.

[0050] For example, one or more of the transmitting stations can be two or more transmitting stations, or one or more of the receiving stations can be two or more receiving stations.

[0051] For example, one or more of the transmitting stations can be two or more transmitting stations, and one or more of the receiving stations can be two or more receiving stations.

[0052] For example, the weight function calculation unit may also calculate the weight function based on the positional relationship among the coordinates, the transmitting array antenna, and the receiving array antenna.

[0053] For example, the weight function calculation unit may also calculate a Rayleigh distribution or a normal distribution as the weight function.

[0054] For example, two or more of the transmitting stations may be one or more of the transmitting stations that control the transmission timing or the transmission frequency so as not to transmit simultaneously from the transmitting array antenna.

[0055] For example, the integrated position spectrum function calculation unit may also synthesize a plurality of calculated position spectrum functions and weight functions into one function by multiplying or adding them to each other.

[0056] For example, the position spectrum function calculation unit may also calculate the position spectrum function based on a MUSIC (MUltiple SIgnal Classification) algorithm, a Capon algorithm, or a beamforming algorithm.

[0057] Furthermore, a position estimation method according to an aspect of the present disclosure is executed by a sensor including one or more transmitting stations and one or more receiving stations, the transmitting station including a transmitting array antenna that transmits a signal, the receiving station including a receiving array antenna that receives a signal, the position estimation method including: a step of receiving, by the receiving array antenna, a signal transmitted from the transmitting station and affected by a living body, and extracting a signal component affected by the living body from the received signal; a step of calculating, based on the signal component, a number of position spectrum functions corresponding to the number of combinations between the transmitting station and the receiving station, the position spectrum function corresponding to the likelihood of the position of the living body; a step of calculating a number of weight functions corresponding to the number of combinations between the transmitting station and the receiving station, the weight function indicating the reliability of the position spectrum function of the receiving station at each coordinate within a measurement range; a step of outputting an integrated position spectrum function using the calculated position spectrum function and the calculated weight function; and a step of estimating the position of the living body by detecting a maximum value from the integrated position spectrum function.

[0058] In addition, the present disclosure can be implemented not only as a device, but also as an integrated circuit having processing components included in such a device, or as a method in which the processing components constituting the device are set as steps, or as a program that causes a computer to execute these steps, or as information, data, or signals representing the program. Further, these programs, information, data, and signals can also be distributed via a recording medium such as a CD-ROM or a communication medium such as the Internet.

[0059] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In addition, the embodiments described below all represent a preferred specific example of the present disclosure. The numerical values, shapes, materials, structural elements, arrangement positions of the structural elements, connection methods, steps, order of steps, etc. shown in the following embodiments are examples and do not limit the gist of the present disclosure.

[0060] In addition, among the structural elements in the following embodiments, the structural elements not described in the independent claims of the broadest concept of the present disclosure are described as optional structural elements constituting a more preferred mode. In addition, in this specification and the drawings, structural elements having substantially the same functional structure are given the same reference numerals, and repeated descriptions are omitted.

[0061] (Embodiment)

[0062] Hereinafter, a method for estimating the position of the sensor 1 in the embodiment will be described with reference to the drawings.

[0063] [Structure of Sensor 1]

[0064] Figure 1 is a block diagram showing the structure of the sensor 1 in the embodiment. Figure 2 is a diagram showing an example of the configuration of the transmitting station and the receiving station in the embodiment.

[0065] Figure 1 The illustrated sensor 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 weight function calculation unit 30, a comprehensive position spectrum function calculation unit 40, and a position estimation unit 50. In addition, in Figure 2 conceptually shows the configuration of the transmitting stations 10-1 and 10-2 and the receiving stations 20-1 and 20-2 and the situation where signals are transmitted in the case where M is 2 and N is 2.

[0066] [Transmitting Stations 10-1 to 10-M]

[0067] The transmitting stations 10-1 to 10-M each have a transmitting array antenna. Here, M is an integer of 1 or more. Among the M transmitting stations, the j-th (j is an integer from 1 to M) transmitting station 10-j is taken as an example for illustration. In addition, all the transmitting stations 10-1 to 10-M have the same structure and the same processing is performed thereon.

[0068] The transmitting station 10-j is composed of a transmitting unit 11-j and a transmitting antenna 12-j as shown in Figure 1 . Here, 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.

[0069] [Transmission timing control unit 15]

[0070] The transmission timing control unit 15 controls the transmission timing so that two or more transmitting stations 10-1 to 10-M do not transmit simultaneously from the transmitting array antenna. In addition, since the transmission signals of the respective transmitters only need to be distinguishable, frequencies can be allocated instead of controlling the transmission timing, or antennas with limited directivity can be used in a sufficiently wide space to transmit antennas that are sufficiently separated simultaneously. In addition, time division multiplexing, frequency multiplexing, CSMA / CA (Carrier Sense Multiple Access / Collision Avoidance), CSMA / CD (Carrier Sense Multiple Access / Collision Detection), etc. can be used in the same way as wireless communication such as wireless LAN (Local Area Network).

[0071] The transmitting antenna 12-j is composed of a transmitting antenna of M T elements, that is, M T transmitting antenna elements.

[0072] The transmitting unit 11-j generates a high-frequency (for example, microwave) signal (for example, CW (Continuous Wave) or OFDM (Orthogonal Frequency Division Multiplexing) signal) used for estimating the position of the living body 100. For example, as shown in Figure 2 , the generated signal is used as a transmission wave and transmitted from the transmitting antenna 12-j.

[0073] [Receiving stations 20-1 to 20-N]

[0074] The receiving stations 20-1 to 20-N each have a receiving array antenna. Here, N is an integer of 2 or more. As an example, the i-th receiving station 20-i (where i is an integer from 1 to N) among the N receiving stations will be described. In addition, each of all the receiving stations 20-1 to 20-N has the same structure and the same processing is performed thereon.

[0075] The receiving station 20-i includes a receiving antenna 21-i, a receiving unit 22-i, a complex transfer function calculation unit 23-i, a biological component extraction unit 24-i, and a position spectrum function calculation unit 25-i.

[0076] <Receiving Antenna 21-i>

[0077] The receiving antenna 21-i is a receiving array antenna composed of M R elements, that is, M R receiving antenna elements. The receiving antenna 21-i receives a high-frequency (e.g., microwave) signal (e.g., CW or OFDM signal) through the receiving array antenna. In the present embodiment, as shown in the receiving antenna 21-i Figure 2 , with this configuration, sometimes the received high-frequency signal includes a reflected wave, which is a part of the transmitted wave sent from the transmitting antenna 12-j and reflected by the living body 100.

[0078] <Receiving Unit 22-i>

[0079] The receiving unit 22-i converts the high-frequency signal received by the receiving antenna 21-i into a low-frequency signal that can be processed. The receiving unit 22-i transmits the converted low-frequency signal to the complex transfer function calculation unit 23-i.

[0080] <Complex Transfer Function Calculation Unit 23-i>

[0081] The complex transfer function calculation unit 23-i calculates a complex transfer function representing the propagation characteristics between the receiving array antenna and the transmitting antenna 12-j of the transmitting station 10-j based on the signal observed by 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 the M R receiving antenna elements of the receiving array antenna based on the low-frequency signal transmitted through the receiving unit 22-i. In addition, the complex transfer function calculated by the complex transfer function calculation unit 23-i includes a direct wave from the transmitting antenna 12-j and a reflected wave that does not pass through the living body 100, such as a reflected wave from a fixed object.

[0082] In addition, in the complex transfer function calculated by the complex transfer function calculation unit 23-i, there may be included a reflected wave, which is a signal obtained by reflecting a part of the transmitted wave transmitted from the transmission antenna 12-j through the living body 100. The amplitude and phase of the reflected wave reflected by the living body 100, that is, the reflected wave via the living body 100, constantly change according to the living body activities such as the respiration and heart rate of the living body 100.

[0083] Hereinafter, an explanation will be given of the case where 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.

[0084] <Biological component extraction unit 24-i>

[0085] The biological component extraction unit 24-i extracts a biological component, which is a signal component transmitted from the transmission antenna 12-j and reflected by one or more living bodies 100, based on the signal observed by the receiving array antenna of the receiving station 22-i. More specifically, the biological component extraction unit 24-i records the complex transfer function calculated by the complex transfer function calculation unit 23-i in the order in which the signal is observed, that is, in a time series. Then, the biological component extraction unit 24-i extracts a variation component based on the influence of the living body 100 as a biological component from the changes in the complex transfer function recorded in the time series.

[0086] Here, as a method for extracting the variation component based on the influence of the living body, there is a method of extracting only the component corresponding to the vibration of the living body after transformation into the frequency domain based on 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 a fixed object are removed, and only the complex transfer function component of the reflected wave via the living body 100 remains.

[0087] In addition, in the present embodiment, there are M R receiving antenna elements constituting the receiving array antenna, that is, a plurality of receiving antenna elements. Therefore, the number of variation components of the complex transfer function corresponding to the receiving array antenna via the living body 100, that is, the biological components, also becomes a plurality. Hereinafter, they are collectively referred to as the biological component channel matrix.

[0088] <Position spectrum function calculation unit 25-i>

[0089] The position spectrum function calculation unit 25-i calculates an evaluation function, that is, a position spectrum function, for the positions of one or more living bodies 100 observed from the receiving station 20-i based on the biological components extracted by the biological component extraction unit 24-i. Here, for example, the position spectrum function calculation unit 25-i may calculate the position spectrum function based on the MUSIC algorithm.

[0090] In the present embodiment, the position spectrum function calculation unit 25-i calculates the correlation matrix R of the biological component channel vector obtained by vectorizing the biological component channel matrix extracted by the biological component extraction unit 24-i. i，j , and uses the obtained correlation matrix R i，j , and calculates the position spectrum function P i，j (X) of the position X of the organism 100 observed from the receiving station 20-i by a prescribed direction-of-arrival estimation method.

[0091] The position spectrum function calculation unit 25-i transmits the calculated position spectrum function P i，j (X) to the comprehensive position spectrum function calculation unit 40.

[0092] Hereinafter, the process until the position spectrum function calculation unit 25-i calculates the position spectrum function P i，j (X) using the MUSIC method will be described using equations. In addition, it is assumed that the biological components are extracted using Fourier transform.

[0093] Let the M R ×M T matrix, that is, the biological component channel matrix H(f), be expressed as in (Equation 1). The biological component channel vector is transformed into an M R M T ×1 biological component channel vector according to (Equation 2).

[0094] [Equation 1]

[0095]

[0096] [Equation 2]

[0097]

[0098] Here, [·]T represents the transpose of a matrix.

[0099] Calculate the correlation matrix R of the biological component channel vector thus obtained as in (Equation 3) i .

[0100] [Equation 3]

[0101] R i = E[h(f)h(f) H (f1 ≤ f ≤ f2)…(Equation 3)

[0102] Here, E[·] represents the average operation in the frequency direction, and f1 and f2 are respectively set as the lower and upper limit frequencies at which the influence of organism activity appears.

[0103] If the correlation matrix Ri of the biological component channel vectors thus obtained is subjected to eigenvalue decomposition, it can be written as shown in the following (Equation 4) to (Equation 6).

[0104] [Equation 4]

[0105]

[0106] [Equation 5]

[0107]

[0108] [Equation 6]

[0109]

[0110] Here, [·]H represents the complex conjugate transpose, and U i is an eigenvector with the number of elements being M R ×M T and Λ i，j is the eigenvalue corresponding to the eigenvector, and is set to be in the order of

[0111] [Equation 7]

[0112]

[0113] L is the number of arrival waves, that is, the number of biological objects to be detected.

[0114] The steering vector of the receiving array antenna, that is, the direction vector, can be defined by (Equation 7).

[0115] [Equation 8]

[0116]

[0117] 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).

[0118] [Equation 9]

[0119]

[0120] Furthermore, by multiplying the steering vectors of transmission and reception, a steering vector considering the angle information of both transmission and reception is defined as shown in (Equation 9).

[0121] [Equation 10]

[0122]

[0123] Here, X is the coordinate of a certain location within the measurement range of the sensor. In addition, the functions Θ t and Θ rThey are functions for obtaining the angles formed by the coordinate X and the transmitting antenna 12-j, and the coordinate X and the receiving antenna 21-i, respectively. In addition, vec[·] is a transformation that rearranges an M-row N-column matrix into a vector of M×N elements. An example of an equally spaced array antenna is shown in this embodiment, but even for array antennas other than this, the steering vector can be calculated in the same manner based on the configuration information of the elements. In addition, the actually measured values can be used instead of the values obtained by calculation.

[0124] In the MUSIC method, the position spectrum function P is calculated as shown in (Equation 10) using this steering vector. i，j (X).

[0125] [Equation 11]

[0126]

[0127] The position spectrum function P i，j (X) has a minimum denominator and takes a maximum value at the position where the organism exists as observed from the j-th transmitting station 10-j and the i-th receiving station 20-i.

[0128] In addition, in the calculation of the position spectrum function, the beamforming method or the Capon method can be used instead of the MUSIC method.

[0129] [Weight function calculation unit 30]

[0130] The weight function calculation unit 30 calculates the weight function f(d i，j ) for the pair of the transmitting station 10-j and the receiving station 20-i. Here, d i，j is the value obtained by subtracting the distance between the transmitting antenna and the receiving antenna from the sum of the distance from the position X to the transmitting antenna and the distance from the position X to the receiving antenna. The function f is a weight function representing the reliability of the position spectrum function P i，j (X) at the position X. Basically, the closer the 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". This position spectrum function P i，j (X) is the position spectrum function at the position X measured by the pair of the transmitting station 10-j and the receiving station 20-i. The weight function uses, for example, the Rayleigh distribution represented by (Equation 11) or the normal distribution represented by (Equation 12).

[0131] [Equation 12]

[0132]

[0133] [Equation 13]

[0134]

[0135] InFigure 3 Figure 3 shows a conceptual diagram of a weight function using the Rayleigh distribution. The area 200 that forms a grid is an area where the value of the weight function is greater than a certain value, and it is an area with high reliability of measurement results. Basically, the value of the weight function is large in the area close to the transmitting antenna 10 and the receiving antenna 20, but the value of the weight function in the area 201 on the straight line connecting the transmitting antenna 10 and the receiving antenna 20 becomes smaller. This is because, on this straight line, the angle formed by the straight line connecting the transmitting antenna and the receiving antenna and the straight line connecting the transmitting antenna and the living body in area 201 is small, and the measurement accuracy decreases. In Figure 4 Figure 4 shows a conceptual diagram of the weight function when using the normal distribution.

[0136] [Comprehensive Position Spectrum Function Calculation Unit 40]

[0137] The position spectrum functions of N×M (N multiplied by M) calculated by each of the N position spectrum function calculation units 25-1 to 25-N and the weight function calculated by the weight function calculation unit 30 are passed to the comprehensive position spectrum function calculation unit 40. The comprehensive position spectrum function calculation unit 40 synthesizes the multiple position spectrum functions calculated by each of the position spectrum function calculation units 25-1 to 25-N into one function. Here, the comprehensive position spectrum function calculation unit 40 multiplies or adds the multiple calculated position spectrum functions to each other after considering the weight function obtained according to the positions of the transmitting antenna and the receiving antenna, so as to synthesize them into one function.

[0138] In the present embodiment, the comprehensive position spectrum function calculation unit 40 performs the synthesis of (N×M) position spectrum functions P i，j (X). More specifically, the comprehensive position spectrum function calculation unit 40 obtains the respective position spectrum functions P i，j (X) calculated using, for example, (Equation 10) from the N receiving stations 20-1 to 20-N. And, the comprehensive position spectrum function calculation unit 40 uses (Equation 13) to calculate the position spectrum function P i，j (X) after synthesizing the obtained N×M position spectrum functions P all (X).

[0139] [Equation 14]

[0140]

[0141] After multiplying these weight functions by the position spectrum function P i，j (X) and taking the sum, only the highly reliable ones among the position spectrum functions can be extracted and synthesized.

[0142] In addition, each position spectrum function P i，j(X) takes a maximum value at the angle where the living organism 100 exists, but this value does not become 0 at angles other than those including directions outside the measurement range. Therefore, an evaluation function that reflects the results of all combinations between N×M types of transmitting stations and receiving stations, that is, the synthesized position spectrum function P, can be obtained by multiplying N×M position spectrum functions. all (X). Additionally, in the synthesis of the position spectrum function here, a sum is used, but they can also be multiplied with each other.

[0143] [Position estimation unit 50]

[0144] The position estimation unit 50 estimates the direction of the arriving wave, that is, the position of the living organism 100, by searching for the maximum value of the synthesized position spectrum function P calculated by the synthesized position spectrum function calculation unit 40. all (X).

[0145] [Operation of sensor 1]

[0146] A process for estimating the position of the living organism by the sensor 1 configured as described above will be described.

[0147] Figure 5 is a flowchart showing the position estimation process of the sensor 1 in an embodiment as an example of the present disclosure. In addition Figure 6 is showing Figure 5 the details of the position estimation process shown.

[0148] First, as shown in Figure 5 , the sensor 1 extracts, from the signals observed by the receiving array antennas of the plurality of receiving stations 20-1 to 20-N, the signal components of the living organisms, that is, the living organism components (step S1), which are the signals transmitted from the transmitting antenna elements of the transmitting station 10-j among the M transmitting stations and reflected by one or more living organisms. More specifically, as shown in Figure 6 , first, for the sensor 1, its N receiving stations observe the received signals during a specified period (step S11).

[0149] Next, the sensor 1 calculates the complex transfer function based on each of the received signals observed by the receiving array antennas of the N receiving stations (step S12). And the sensor 1 records the calculated complex transfer functions as time series, and extracts the living organism components from the recorded complex transfer functions of each time series (step S13).

[0150] Next, the sensor 1 as shown in Figure 5As shown, based on each biological component extracted in step S1, an evaluation function for the positions of one or more organisms 100 for each observation from multiple receiving stations 20-1 to 20-N, that is, a position spectrum function, is calculated for the number of combinations of the transmitting station and the receiving stations, which is (N×M) (step S2). More specifically, as Figure 6 shown, first, the sensor 1 calculates the correlation matrix for each biological component extracted in step S13 (step S21). Next, the sensor 1 uses the correlation matrix calculated in step S21 to calculate the position spectrum function of the organism 100 for each observation from N receiving stations (step S22).

[0151] Next, as Figure 5 shown, the sensor 1 calculates the weight function for each combination between M transmitting stations and N receiving stations (step S3). This weight function is a function representing the reliability of the position spectrum function, and is a function in which the weight becomes smaller as the position is farther from the antenna. Among the functions that can be used as the weight function, there are Rayleigh distribution or normal distribution.

[0152] Next, as Figure 5 shown, the sensor 1 synthesizes the multiple position spectrum functions calculated in step S2 into one comprehensive position spectrum function using the weight function calculated in step S3 (step S4). More specifically, the position spectrum function calculated in step S3 is multiplied by the weight function of the corresponding combination of the transmitting station and the receiving station calculated in step S4, and the sum is taken for all combinations of the transmitting station and the receiving station, thereby calculating the comprehensive position spectrum function.

[0153] Finally, as Figure 5 shown, the sensor 1 estimates the positions of one or more organisms 100 by calculating one or more maxima of the comprehensive position spectrum function calculated in step S4 (step S5).

[0154] [Effects, etc.]

[0155] According to the sensor 1 and the position estimation method of the present embodiment, it is possible to estimate the position where the organism exists with a wider range and high precision using wireless signals. In addition, according to the sensor 1 and the position estimation method of the present embodiment, multiple receiving stations are provided, so that the detection range in which the organism can be detected can be widened.

[0156] More specifically, according to the sensor 1 and the position estimation method of the present embodiment, biological components are extracted from the information of the complex transfer function obtained from multiple receiving stations, the position spectrum functions calculated based on the extracted biological components are synthesized, and the position of the organism is estimated. Thereby, the estimation of the position where the organism exists can be performed in a wider range without being affected by obstacles.

[0157] For example, even when the signal from the target organism is weak and some of the multiple receiving stations cannot observe the reflected wave from the organism, the position spectrum function obtained from the complex transfer function in the receiving stations that can observe the reflected wave from the organism can be used to estimate the position of the organism.

[0158] (Modification Example 1)

[0159] Figure 7 It is a conceptual diagram showing the first modification example of the configuration of the sensor 1 in the embodiment. In the embodiment, the case where the transmission antenna 12-j and the reception antenna 21-i are equidistant array antennas is taken as an example for explanation, but the antennas used are not limited to equidistant array antennas. For example, by arranging the antenna elements in a circle as Figure 7 shown, the directivity of the antenna can be directed in all directions, and the measurement range of the sensor can be widened. For example, even when there is an organism such as Figure 7 the organism 100-2 outside the area surrounded by the antennas, the position can be accurately estimated.

[0160] (Modification Example 2)

[0161] Figure 8 It is a conceptual diagram showing the second modification example of the configuration of the sensor 1 in the embodiment. In addition Figure 9 It is a block diagram showing an example of the structure of the sensor 1A in this modification example 2.

[0162] In the embodiment, the transmission antenna 12-j and the reception antenna 21-i are respectively arranged at different positions, but they can also be arranged by physically sharing the same antenna as the transmission and reception stations 310-1 to 310-4 such as Figure 8 . Since many actual wireless devices share the transmission antenna and the reception antenna, by adopting such a structure, the hardware of the wireless device can be used for sensing. In addition, the signals transmitted by the transmission and reception stations 310-1 to 310-4 can also be the signals used for wireless communication such as wireless LAN. In addition, in the embodiment, one transmission timing control unit controls the M transmission units, but it can also be as Figure 9 shown, and the M transmission timing control units 15A-1 to 15A-M respectively control the transmission units 11-1 to 11-M.

[0163] In addition, the receiving station does not necessarily need to include all of the complex transfer function calculation unit 23-i, the organism information extraction unit 24-i, and the position spectrum function calculation unit 25-i. For example, data can be sent to an external server 401 for calculation by the external server 401. In addition, the position spectrum function can also be sent to one receiving station for calculation of the comprehensive position spectrum function within the receiving station.

[0164] In addition, in the above-described embodiments and variations, each structural element is constituted by dedicated hardware, or may be implemented by executing a software program suitable for each structural element. Each structural element may also be implemented by a program execution unit such as a CPU or a processor reading and executing a software program recorded in a recording medium such as a hard disk or a semiconductor memory. Here, the software for implementing the devices and the like of the above-described embodiments and variations is a program as follows.

[0165] That is, this program is a program that causes a computer to execute a position estimation method performed by a sensor. The sensor includes one or more transmitting stations and one or more receiving stations. The transmitting station includes a transmitting array antenna for transmitting a signal, and the receiving station includes a receiving array antenna for receiving a signal. The position estimation method includes: a step of receiving, by the receiving array antenna, a signal transmitted by the transmitting station and affected by a living body, and extracting a signal component affected by the living body from the received signal; a step of calculating, based on the signal component, a corresponding number of position spectrum functions corresponding to the likelihood of the position of the living body, the number of the position spectrum functions corresponding to the number of combinations between the transmitting station and the receiving station; a step of calculating a corresponding number of weight functions corresponding to the number of combinations between the transmitting station and the receiving station, the weight function indicating the reliability of the position spectrum function of the receiving station at each coordinate within a measurement range; a step of outputting a synthesized position spectrum function using the calculated position spectrum function and the calculated weight function; and a step of estimating the position of the living body by detecting a maximum value from the synthesized position spectrum function.

[0166] As described above, the sensor and the position estimation method according to one aspect of the present disclosure have been described based on the embodiments. However, the present disclosure is not limited to these embodiments. As long as it does not deviate from the gist of the present disclosure, embodiments obtained by applying various variations conceivable by those skilled in the art to the present embodiment, or embodiments constructed by combining structural elements in different embodiments may also be included within the scope of the present disclosure.

[0167] In addition, the present disclosure can be implemented not only as a sensor having structural elements with such characteristics, but also as a position estimation method or the like in which the structural elements including the characteristics in the sensor are set as steps. Further, it can also be implemented as a computer program that causes a computer to execute each step including the characteristics in such a method. And needless to say, such a computer program can be distributed via a computer-readable non-volatile recording medium such as a CD-ROM or a communication network such as the Internet.

[0168] Industrial Applicability

[0169] The present disclosure can be applied to a sensor and a position estimation method for estimating the position of a living body using wireless signals. In particular, it can be applied to a measuring device for measuring the direction or position of a living body, a home appliance for performing control corresponding to the direction or position of a living body, a sensor and a position estimation method mounted on a monitoring device for detecting the intrusion of a living body, etc.

[0170] Reference Numeral Explanation

[0171] 1, 1A Sensor

[0172] 10, 12-1 to 12-M Transmission Antenna

[0173] 10-1 to 10-M, 10A-1 to 10A-M Transmission Station

[0174] 11-1 to 11-M Transmission Unit

[0175] 15, 15A-1 to 15A-M Transmission Timing Control Unit

[0176] 20, 21-1 to 21-N Reception Antenna

[0177] 20-1 to 20-N, 20A-1 to 20A-N Reception Station

[0178] 22-1 to 22-N Reception Unit

[0179] 23-1 to 23-N Complex Transfer Function Calculation Unit

[0180] 24-1 to 24-N Living Body Component Extraction Unit

[0181] 25-1 to 25-N Position Spectrum Function Calculation Unit

[0182] 30 Weight Function Calculation Unit

[0183] 40 Comprehensive Position Spectrum Function Calculation Unit

[0184] 50 Position Estimation Unit

[0185] 100, 100-1, 100-2 Living Body

[0186] 200, 201 Region

[0187] 310-1, 310-2, 310-3, 310-4 Transmission and Reception Station

[0188] 401 External Server

Claims

1. A sensor includes one or more transmitting stations and one or more receiving stations. The transmitting station has a transmitting array antenna for transmitting signals, and the receiving station has a receiving array antenna for receiving signals. In this sensor, it includes: A biological component extraction unit that receives, through the receiving array antenna, the signals transmitted by the transmitting station and affected by a living body, and extracts the signal components affected by the living body from the received signals; A position spectrum function calculation unit that calculates a corresponding number of position spectrum functions according to the signal components, where the number of position spectrum functions corresponds to the number of combinations between the transmitting station and the receiving station, and the position spectrum function corresponds to the likelihood of the position of the living body; A weight function calculation unit that calculates a corresponding number of weight functions based on the distance between the living body and the transmitting antenna and the distance between the living body and the receiving antenna, where the weight function represents the reliability of the position spectrum function of the receiving station at each coordinate within the measurement range; A comprehensive position spectrum function calculation unit that outputs a comprehensively combined position spectrum function using the position spectrum function calculated by the position spectrum function calculation unit and the weight function calculated by the weight function calculation unit; And A position estimation unit that estimates the position of the living body by detecting the maximum value from the comprehensively combined position spectrum function.

2. The sensor according to claim 1, wherein One or more of the transmitting stations are two or more transmitting stations, or One or more of the receiving stations are two or more receiving stations.

3. The sensor according to claim 1, wherein One or more of the transmitting stations are two or more transmitting stations, and One or more of the receiving stations are two or more receiving stations.

4. The sensor according to claim 1, wherein The weight function calculation unit calculates the weight function based on the positional relationship between the coordinate, the transmitting array antenna, and the receiving array antenna.

5. The sensor according to claim 1, wherein The weight function calculation unit calculates a Rayleigh distribution or a normal distribution as the weight function.

6. The sensor according to claim 1, wherein One or more of the transmitting stations are two or more transmitting stations that control the transmission timing or transmission frequency so as not to transmit simultaneously from the transmitting array antenna.

7. The sensor according to claim 1, wherein The comprehensive position spectrum function calculation unit comprehensively combines into one function by multiplying or adding the calculated multiple position spectrum functions and weight functions to each other.

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

9. A position estimation method performed by a sensor. The sensor includes one or more transmitting stations and one or more receiving stations. The transmitting station has a transmitting array antenna for transmitting signals, and the receiving station has a receiving array antenna for receiving signals. The position estimation method includes: A step of receiving, by the receiving array antenna, a signal transmitted by the transmitting station and affected by a living body, and extracting, from the received signal, a signal component affected by the living body; A step of calculating, based on the signal component, a corresponding number of position spectrum functions corresponding to the likelihood of the position of the living body, the number of the position spectrum functions being corresponding to the number of combinations between the transmitting station and the receiving station; A step of calculating, based on the distance between the living body and the transmitting antenna and the distance between the living body and the receiving antenna, a corresponding number of weight functions corresponding to the number of combinations between the transmitting station and the receiving station, the weight function indicating the reliability of the position spectrum function of the receiving station at each coordinate within the measurement range; A step of outputting a synthesized position spectrum function using the calculated position spectrum function and the calculated weight function; And A step of estimating the position of the living body by detecting a maximum value from the synthesized position spectrum function.

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