阅读说明：本技术 推定装置及推定方法 (Estimation device and estimation method ) 是由 饭塚翔一 中山武司 本间尚树 于 2019-03-13 设计创作，主要内容包括：提供能够更高精度地推定运动物体的方向或位置的推定装置及推定方法。推定装置具有：发送天线部(11)；发送信号生成部(13),生成多载波信号；发送部(12),将多载波信号输出至发送天线部(11)；接收天线部(21)；接收部(22),对接收信号进行观测,该接受信号包含发送出的多载波信号经过运动物体反射、散射所得的反射信号；复传递函数计算部(23),根据观测到的多个接收信号,计算出多个表示各发送天线元件与各接收天线元件之间的传播特性的复传递函数；运动物体相关矩阵计算部(24),针对每个副载波计算出复传递函数中的运动物体相关矩阵；副载波统一部(25),统一运动物体相关矩阵；以及推定处理部(26),使用通过统一而得到的统一运动物体相关矩阵推定运动物体所在的方向或位置。(Provided are an estimation device and an estimation method capable of estimating the direction or position of a moving object with higher accuracy. The estimation device has: a transmitting antenna unit (11); a transmission signal generation unit (13) that generates a multicarrier signal; a transmission unit (12) that outputs a multicarrier signal to the transmission antenna unit (11); a receiving antenna unit (21); a reception unit (22) for observing a reception signal including a reflection signal obtained by reflecting and scattering a transmitted multicarrier signal by a moving object; a complex transfer function calculation unit (23) which calculates a plurality of complex transfer functions representing propagation characteristics between each transmitting antenna element and each receiving antenna element, based on a plurality of observed received signals; a moving object correlation matrix calculation unit (24) that calculates a moving object correlation matrix in the complex transfer function for each subcarrier; a subcarrier unifying unit (25) for unifying correlation matrices of moving objects; and an estimation processing unit (26) for estimating the direction or position of the moving object using the unified moving object correlation matrix obtained by the unification.)

1. An estimation device for estimating the position of a target,

the estimation device estimates the direction or position of a moving object, and includes:

a transmitting antenna unit having M transmitting antenna elements, wherein M is a natural number of 1 or more, and M ≧ 2 when N is 1;

a transmission signal generation unit that generates a multicarrier signal in which a plurality of subcarrier signals are modulated;

a transmission unit that outputs the multicarrier signal to the transmission antenna unit, thereby causing the transmission antenna unit to transmit the multicarrier signal;

a reception antenna unit having N reception antenna elements, where N is a natural number of 1 or more, and N ≧ 2 when M is 1;

a reception unit configured to observe a reception signal, which is received by each of the N reception antenna elements and includes a reflected signal obtained by reflecting or scattering the multicarrier signal transmitted by each of the M transmission antenna elements by a moving object, during a 1 st period corresponding to a cycle of an operation of the moving object;

a complex transfer function calculation unit that calculates, for each of M × N combinations that are all combinations that can be obtained when the M transmitting antenna elements and the N receiving antenna elements 1 to 1 are combined, a plurality of complex transfer functions indicating propagation characteristics between the transmitting antenna element and the receiving antenna element in each of a plurality of subcarriers corresponding to the plurality of subcarrier signals, using the plurality of received signals observed in the reception unit in the 1 st period;

a moving object correlation matrix calculation unit that (i) sequentially records the plurality of complex transfer functions calculated by the complex transfer function calculation unit in time series, which is an order in which the plurality of received signals are observed, and (ii) extracts a component related to a moving object from the plurality of complex transfer functions sequentially recorded in time series, thereby calculating a moving object correlation matrix of an M × N matrix for each of the plurality of subcarriers, and for each of the M × N combinations;

a subcarrier unifying unit that unifies the moving object correlation matrix calculated for each of the plurality of subcarriers by a predetermined method to calculate a unified moving object correlation matrix; and

and an estimation processing unit configured to estimate a direction or position of the moving object using the unified moving object correlation matrix calculated by the subcarrier unifying unit, with the estimation device being a reference of the direction or position.

2. The estimation device according to claim 1, wherein,

the moving object correlation matrix calculation unit calculates 2 or more pieces of difference information indicating differences of 2 complex transfer functions at 2 times at predetermined intervals among the multiple complex transfer functions recorded sequentially in time series for each of the multiple subcarriers and for each of the M × N combinations, and calculates the moving object correlation matrix using the 2 or more pieces of calculated difference information.

3. The estimation device according to claim 1, wherein,

the moving object correlation matrix calculation unit calculates an average value in a 2 nd period of the plurality of complex transfer functions recorded in time series for each of the plurality of subcarriers and for each of the M × N combinations, subtracts the average value from each of the plurality of complex transfer functions in the 2 nd period, and calculates the moving object correlation matrix using the subtraction result.

4. The estimation device according to any one of claims 1 to 3, wherein,

the subcarrier unifying section calculates the unified moving object correlation matrix by calculating an average of a plurality of moving object correlation matrices calculated in the plurality of subcarriers, respectively, to an average of 1 subcarrier.

5. The estimation device according to any one of claims 1 to 3, wherein,

the subcarrier unifying section calculates the unified moving object correlation matrix by calculating median numbers of a plurality of moving object correlation matrices calculated in the plurality of subcarriers, respectively, for each corresponding component.

6. The estimation device according to any one of claims 1 to 3, wherein,

the multi-carrier signal is an OFDM signal.

7. An estimation device for estimating the position of a target,

the estimation device estimates the direction or position of a moving object, and includes:

a transmitting antenna unit having M transmitting antenna elements, wherein M is a natural number of 1 or more, and M ≧ 2 when N is 1;

a transmission signal generation unit that generates a transmission signal;

a transmitting section that outputs the transmission signal to the transmitting antenna section, thereby causing the transmitting antenna section to transmit the transmission signal;

a reception antenna unit having N reception antenna elements, where N is a natural number of 1 or more, and N ≧ 2 when M is 1;

a reception unit configured to observe a reception signal received by each of the N reception antenna elements and including a reflected signal obtained by reflecting or scattering the transmission signal transmitted from each of the M transmission antenna elements by a moving object, the reception signal corresponding to a 1 st period of a cycle of the motion of the moving object;

a complex transfer function calculation unit that calculates, using the plurality of received signals observed in the reception unit during the 1 st period, a plurality of complex transfer functions representing propagation characteristics between the transmitting antenna element and the receiving antenna element in each of M × N combinations that are all combinations that can be obtained when the M transmitting antenna elements and the N receiving antenna elements are combined 1 to 1;

a moving object correlation matrix calculation unit that, for each of the M × N combinations, (i) sequentially records the plurality of complex transfer functions calculated by the complex transfer function calculation unit in time series in the order in which the plurality of received signals are observed, (ii) calculates an average value in a period 2 of the plurality of complex transfer functions sequentially recorded in time series, and (iii) calculates a moving object correlation matrix of an M × N matrix by subtracting the average value from the complex transfer function for each of the plurality of complex transfer functions in the period 2; and

and an estimation processing unit configured to estimate a direction or position of the moving object using the estimation device as a reference of the direction or position, using the moving object correlation matrix calculated by the moving object correlation matrix calculation unit.

8. A method of estimating the position of a target,

the estimation method is an estimation method performed by an estimation device,

the estimation device includes a transmission antenna unit having M transmission antenna elements and a reception antenna unit having N reception antenna elements, wherein M is a natural number of 1 or more, M ≧ 2 when N is 1, N is a natural number of 1 or more, N ≧ 2 when M is 1,

generating a multi-carrier signal modulated with a plurality of sub-carrier signals,

causing the transmitting antenna section to transmit the multicarrier signal by outputting the multicarrier signal to the transmitting antenna section,

observing reception signals received by each of the N reception antenna elements, the reception signals including reflection signals obtained by reflecting or scattering the multicarrier signals transmitted by each of the M transmission antenna elements by a moving object, during a 1 st period corresponding to a cycle of an operation of the moving object,

using the plurality of received signals observed in the 1 st period, for each of M × N combinations that are all combinations that can be obtained when the M transmitting antenna elements and the N receiving antenna elements are combined 1-to-1, a plurality of complex transfer functions representing propagation characteristics between the transmitting antenna elements and the receiving antenna elements in the combination are calculated for each of a plurality of subcarriers corresponding to the plurality of subcarrier signals,

for each of the plurality of subcarriers and for each of the M × N combinations, (i) successively recording a plurality of the complex transfer functions calculated in time series in an order in which the plurality of received signals are observed, (ii) calculating a moving object correlation matrix of an M × N matrix for each of the plurality of subcarriers by extracting a component related to a moving object from the plurality of complex transfer functions recorded successively in time series,

unifying the moving object correlation matrices calculated for each of the plurality of subcarriers by a prescribed method to thereby calculate a unified moving object correlation matrix,

and using the calculated unified moving object correlation matrix to use the estimation device as a reference of the direction or the position to estimate the direction or the position of the moving object.

9. A method of estimating the position of a target,

the estimation method is an estimation method performed by an estimation device,

the estimation device includes a transmission antenna unit having M transmission antenna elements and a reception antenna unit having N reception antenna elements, wherein M is a natural number of 1 or more, M ≧ 2 when N is 1, N is a natural number of 1 or more, N ≧ 2 when M is 1,

a transmission signal is generated and transmitted to the mobile station,

causing the transmitting antenna section to transmit the transmission signal by outputting the transmission signal to the transmitting antenna section,

observing reception signals received by each of the N reception antenna elements, the reception signals including reflection signals obtained by reflecting or scattering the transmission signals transmitted from each of the M transmission antenna elements by a moving object, the observation being performed during a 1 st period corresponding to a cycle of the motion of the moving object,

using a plurality of received signals observed in the 1 st period, calculating a plurality of complex transfer functions representing propagation characteristics between the transmitting antenna element and the receiving antenna element in each of M × N combinations, which are all combinations that can be obtained when the M transmitting antenna elements and the N receiving antenna elements are combined 1 to 1,

for each of the M x N combinations, (i) successively recording a plurality of the complex transfer functions calculated in time series in an order in which the plurality of received signals are observed, (ii) calculating an average value in a 2 nd period of the plurality of complex transfer functions successively recorded in time series, (iii) calculating a moving object correlation matrix of an M x N matrix by subtracting the average value from each of the plurality of complex transfer functions in the 2 nd period,

and using the calculated correlation matrix of the moving object and taking the estimation device as a reference of the direction or the position to estimate the direction or the position of the moving object.

Technical Field

The present disclosure relates to an estimation device and an estimation method for estimating a direction or a position of a moving object using a wireless signal.

Background

As a method of knowing the position of a person or the like, a method using a wireless signal is being studied (for example, see patent documents 1 to 4). Patent documents 1, 2, and 3 disclose techniques for estimating the position or state of a person as a detection target by analyzing a component including a doppler shift by using difference amount calculation. Patent documents 4 and 5 disclose doppler sensors using OFDM (Orthogonal Frequency Division Multiplexing) signals.

Disclosure of Invention

Problems to be solved by the invention

The existing method is difficult to estimate the direction or position of a moving object relative to the device with higher precision.

Means for solving the problems

In order to achieve the above object, an estimation device according to one aspect of the present disclosure estimates a direction or a position in which a moving object is present, and includes: a transmitting antenna unit having M (M is a natural number of 1 or more, M ≧ 2 when N is 1) transmitting antenna elements; a transmission signal generation unit that generates a multicarrier signal in which a plurality of subcarrier signals are modulated; a transmission unit that outputs the multicarrier signal to the transmission antenna unit, thereby causing the transmission antenna unit to transmit the multicarrier signal; a reception antenna unit having N (N is a natural number of 1 or more, where N ≧ 2 when M is 1) reception antenna elements; a reception unit configured to observe a reception signal, which is received by each of the N reception antenna elements and includes a reflected signal obtained by reflecting or scattering the multicarrier signal transmitted by each of the M transmission antenna elements by a moving object, during a 1 st period corresponding to a cycle of an operation of the moving object; a complex transfer function calculation unit that calculates, for each of M × N combinations that are all combinations that can be obtained when the M transmitting antenna elements and the N receiving antenna elements 1 to 1 are combined, a plurality of complex transfer functions indicating propagation characteristics between the transmitting antenna element and the receiving antenna element in each of a plurality of subcarriers corresponding to the plurality of subcarrier signals, using the plurality of received signals observed in the reception unit in the 1 st period; a moving object correlation matrix calculation unit that (i) sequentially records the plurality of complex transfer functions calculated by the complex transfer function calculation unit in time series, which is an order in which the plurality of received signals are observed, and (ii) extracts a component related to a moving object from the plurality of complex transfer functions sequentially recorded in time series, thereby calculating a moving object correlation matrix of an M × N matrix for each of the plurality of subcarriers, and for each of the M × N combinations; a subcarrier unifying unit that unifies the moving object correlation matrix calculated for each of the plurality of subcarriers by a predetermined method to calculate a unified moving object correlation matrix; and an estimation processing unit configured to estimate a direction or position of the moving object using the unified moving object correlation matrix calculated by the subcarrier unifying unit, with the estimation device being a reference of the direction or position.

In addition, an estimation device according to another aspect of the present disclosure estimates a direction or a position in which a moving object is present, and includes: a transmitting antenna unit having M (M is a natural number of 1 or more, M ≧ 2 when N is 1) transmitting antenna elements; a transmission signal generation unit that generates a transmission signal; a transmitting section that outputs the transmission signal to the transmitting antenna section, thereby causing the transmitting antenna section to transmit the transmission signal; a reception antenna unit having N (N is a natural number of 1 or more, where N ≧ 2 when M is 1) reception antenna elements; a reception unit configured to observe a reception signal received by each of the N reception antenna elements and including a reflected signal obtained by reflecting or scattering the transmission signal transmitted from each of the M transmission antenna elements by a moving object, the reception signal corresponding to a 1 st period of a cycle of the motion of the moving object; a complex transfer function calculation unit that calculates, using the plurality of received signals observed in the reception unit during the 1 st period, a plurality of complex transfer functions representing propagation characteristics between the transmitting antenna element and the receiving antenna element in each of M × N combinations that are all combinations that can be obtained when the M transmitting antenna elements and the N receiving antenna elements are combined 1 to 1; a moving object correlation matrix calculation unit that, for each of the M × N combinations, (i) sequentially records the plurality of complex transfer functions calculated by the complex transfer function calculation unit in time series in the order in which the plurality of received signals are observed, (ii) calculates an average value in a period 2 of the plurality of complex transfer functions sequentially recorded in time series, and (iii) calculates a moving object correlation matrix of an M × N matrix by subtracting the average value from the complex transfer function for each of the plurality of complex transfer functions in the period 2; and an estimation processing unit configured to estimate a direction or position of the moving object using the estimation device as a reference of the direction or position, using the moving object correlation matrix calculated by the moving object correlation matrix calculation unit.

These general and specific aspects may be implemented by a system, a method, an integrated circuit, a computer program, a computer-readable storage medium such as a CD-ROM, or any combination of the system, the method, the integrated circuit, the computer program, and the storage medium.

ADVANTAGEOUS EFFECTS OF INVENTION

According to the present disclosure, the direction or position of a moving object with respect to the present apparatus can be estimated with higher accuracy.

Drawings

Fig. 1 is a block diagram showing an example of the configuration of an estimation device according to an embodiment.

Fig. 2 is a diagram showing an example of a detection target of the estimation device shown in fig. 1.

Fig. 3 is a diagram schematically showing the transmission of signal waves in the antenna unit shown in fig. 1.

Fig. 4 is a schematic diagram showing an example of 2 times at a predetermined interval used for calculating difference information in embodiment 1.

Fig. 5 is a schematic diagram showing an example of 2 times at predetermined intervals different from those in fig. 4.

Fig. 6 is a flowchart showing an estimation process of the estimation device in the embodiment.

Fig. 7 is a diagram schematically showing signal processing in the moving object correlation matrix calculation in modification 2.

Detailed Description

(knowledge as a basis for the present disclosure)

As a method of knowing the position of a person, a method using a wireless signal is being studied.

For example, patent documents 1 and 2 disclose techniques for transmitting a radio signal to a predetermined area, receiving the radio signal reflected by a detection target by a plurality of antennas, and estimating a complex transfer function between the transmitting and receiving antennas. The complex transfer function is a function of a complex number indicating a relationship between an input and an output, and here, indicates a propagation characteristic between the transmitting and receiving antennas. The number of elements of the complex transfer function is equal to the product of the number of transmit antennas and the number of receive antennas.

Patent document 3 discloses a technique for estimating the posture of a living body using RCS (Radar Cross Section) obtained from received power in a configuration similar to that of patent document 2. The RCS is an index indicating the area of an object that reflects a transmission wave, and the RCS of a living body varies depending on the posture.

Patent document 1 also discloses a technique of determining the position or state of a person to be detected by analyzing a component including a doppler shift using fourier transform. More specifically, the time waveform of the elements of the complex transfer function is fourier transformed by recording the time-dependent changes of the elements. Biological activities such as respiration and heartbeat by a living body such as a person give a small doppler effect to reflected waves. Therefore, the components including the doppler shift include influences caused by the biological activity of the human being. On the other hand, the components without doppler shift are not affected by the biological activity of the human being, that is, correspond to reflected waves from a fixed object or direct waves between transmitting and receiving antennas. That is, patent document 1 discloses a technique that can know the position or state of a person to be detected using a component included in a predetermined frequency range in a waveform after fourier transform.

Patent document 2 discloses a method of extracting a component including a minute doppler shift including an influence of a living body by recording a change with time of an element of a complex transfer function and analyzing difference information thereof. That is, patent document 2 discloses a technique for obtaining the position or state of a person to be detected using the difference information.

On the other hand, patent document 3 discloses an OFDM doppler radar that transmits a pulse using an OFDM (Orthogonal Frequency Division Multiplexing) signal and detects a doppler shift caused by a moving object to be detected. Patent document 4 discloses a high-speed processing method for OFDM doppler radar that does not require fourier transform.

Patent documents 6 and 7 disclose techniques for improving the estimation accuracy of a complex transfer function between transmitting and receiving antennas by transmitting an OFDM signal. Patent document 5 discloses that the received noise component can be reduced by averaging the complex transfer function for each subcarrier, and patent document 7 discloses that the received noise component can be reduced by selecting the subcarrier having the largest received power.

However, in the methods of patent documents 1, 2, and 3, since a non-modulated wave is used as a transmission signal, it is difficult to use the method in a commercially available device, and dedicated hardware is required. That is, it is difficult to use communication equipment that is currently widespread, and users need to add dedicated hardware to the existing communication devices.

In addition, the methods of patent documents 4 and 5 require a wide bandwidth because the transmission pulse needs to be made steep in order to obtain sufficient accuracy. The cost of the hardware is therefore high compared to consumer oriented communication devices.

In addition, when it is desired to apply the estimation method using the complex transfer function of the OFDM signal of patent documents 6 and 7 to the biological radar, the biological components included in the noise are cancelled by averaging the complex transfer functions of the subcarriers of the OFDM, and thus, it is impossible to estimate with high accuracy.

Therefore, the inventors have invented an estimation device and the like that can estimate the direction or position of a moving object with respect to the own device at higher accuracy using a multicarrier signal represented by OFDM at low cost and with high accuracy using an existing communication device.

That is, an estimation device according to an aspect of the present disclosure estimates a direction or a position in which a moving object is present, and includes: a transmitting antenna unit having M (M is a natural number of 1 or more, M ≧ 2 when N is 1) transmitting antenna elements; a transmission signal generation unit that generates a multicarrier signal in which a plurality of subcarrier signals are modulated; a transmission unit that outputs the multicarrier signal to the transmission antenna unit, thereby causing the transmission antenna unit to transmit the multicarrier signal; a reception antenna unit having N (N is a natural number of 1 or more, where N ≧ 2 when M is 1) reception antenna elements; a reception unit configured to observe a reception signal, which is received by each of the N reception antenna elements and includes a reflected signal obtained by reflecting or scattering the multicarrier signal transmitted by each of the M transmission antenna elements by a moving object, during a 1 st period corresponding to a cycle of an operation of the moving object; a complex transfer function calculation unit that calculates, for each of M × N combinations that are all combinations that can be obtained when the M transmitting antenna elements and the N receiving antenna elements 1 to 1 are combined, a plurality of complex transfer functions indicating propagation characteristics between the transmitting antenna element and the receiving antenna element in each of a plurality of subcarriers corresponding to the plurality of subcarrier signals, using the plurality of received signals observed in the reception unit in the 1 st period; a moving object correlation matrix calculation unit that (i) sequentially records the plurality of complex transfer functions calculated by the complex transfer function calculation unit in time series, which is an order in which the plurality of received signals are observed, and (ii) extracts a component related to a moving object from the plurality of complex transfer functions sequentially recorded in time series, thereby calculating a moving object correlation matrix of an M × N matrix for each of the plurality of subcarriers, and for each of the M × N combinations; a subcarrier unifying unit that unifies the moving object correlation matrix calculated for each of the plurality of subcarriers by a predetermined method to calculate a unified moving object correlation matrix; and an estimation processing unit configured to estimate a direction or position of the moving object using the unified moving object correlation matrix calculated by the subcarrier unifying unit, with the estimation device being a reference of the direction or position.

With this configuration, by using the multicarrier signal as the transmission signal, it is possible to estimate the direction or position of the moving object such as a living body with respect to the estimation device, along with the original communication device.

In addition, the estimation device estimates the direction or position of the living body with respect to the estimation device using a unified moving object correlation matrix obtained by unifying a plurality of moving object correlation matrices obtained for each of a plurality of subcarriers. Therefore, the position of the living body can be estimated with higher accuracy than in the case of using a single subcarrier.

The moving object correlation matrix calculation unit may calculate 2 or more pieces of difference information indicating differences of 2 complex transfer functions at 2 times at predetermined intervals among the plurality of complex transfer functions recorded in time series for each of the plurality of subcarriers and for each of the M × N combinations, and may calculate the moving object correlation matrix using the 2 or more pieces of calculated difference information.

Thus, by averaging 2 or more pieces of difference information, the influence of instantaneous noise can be reduced, and the estimation accuracy of the direction or position can be further improved.

Further, the moving object correlation matrix calculation unit may calculate an average value in a 2 nd period of the plurality of complex transfer functions recorded in time series for each of the plurality of subcarriers and for each of the M × N combinations, subtract the average value from each of the plurality of complex transfer functions in the 2 nd period, and calculate the moving object correlation matrix using a subtraction result obtained.

Thus, the moving object correlation matrix can be calculated by simple calculation such as averaging and subtraction without performing complicated calculation such as fourier transform and calculation of a plurality of differences. Therefore, the processing load for calculating the correlation matrix of the moving object can be reduced.

In addition, the subcarrier unifying section may calculate the unified moving object correlation matrix by averaging a plurality of moving object correlation matrices calculated in the plurality of subcarriers, respectively, to an average of 1 subcarrier.

Thus, the moving object information included in the moving object correlation matrix of each subcarrier is overlapped by calculating the average of the moving object correlation matrix to the average of 1 subcarrier, instead of the average of the complex transfer function which cancels out the fluctuation of the living body, and the subsequent estimation processing section performs processing at once using the uniform moving object correlation matrix. This allows the matrix rank to be restored during calculation, and the accuracy of estimation of the direction or position, which is the calculation result, can be improved.

In addition, the subcarrier unifying section may calculate the unified moving object correlation matrix by calculating median numbers of a plurality of moving object correlation matrices for each corresponding component, the median numbers of the plurality of moving object correlation matrices being calculated in the plurality of subcarriers, respectively.

Therefore, it is possible to easily unify a plurality of moving object correlation matrices corresponding to a plurality of subcarriers, respectively.

In addition, the multi-carrier signal may be an OFDM (Orthogonal frequency division Multiplexing) signal.

An estimation device according to another aspect of the present disclosure estimates a direction or a position in which a moving object is present, and includes: a transmitting antenna unit having M (M is a natural number of 1 or more, M ≧ 2 when N is 1) transmitting antenna elements; a transmission signal generation unit that generates a transmission signal; a transmitting section that outputs the transmission signal to the transmitting antenna section, thereby causing the transmitting antenna section to transmit the transmission signal; a reception antenna unit having N (N is a natural number of 1 or more, where N ≧ 2 when M is 1) reception antenna elements; a reception unit configured to observe a reception signal received by each of the N reception antenna elements and including a reflected signal obtained by reflecting or scattering the transmission signal transmitted from each of the M transmission antenna elements by a moving object, the reception signal corresponding to a 1 st period of a cycle of the motion of the moving object; a complex transfer function calculation unit that calculates, using the plurality of reception signals observed in the reception unit in the 1 st period, a plurality of complex transfer functions representing propagation characteristics between the transmission antenna element and the reception antenna element in each of M × N combinations that are all combinations that can be obtained when the M transmission antenna elements and the N reception antenna elements 1 to 1 are combined; a moving object correlation matrix calculation unit that, for each of the M × N combinations, (i) sequentially records the plurality of complex transfer functions calculated by the complex transfer function calculation unit in time series in the order in which the plurality of received signals are observed, (ii) calculates an average value in a period 2 of the plurality of complex transfer functions sequentially recorded in time series, and (iii) calculates a moving object correlation matrix of an M × N matrix by subtracting the average value from the complex transfer function for each of the plurality of complex transfer functions in the period 2; and an estimation processing section that estimates a direction or position in which the moving object is present, using the moving object correlation matrix calculated by the moving object correlation matrix calculation section, with the estimation device as a reference for the direction or position.

These general and specific aspects may be implemented by a system, a method, an integrated circuit, a computer program, a computer-readable storage medium such as a CD-ROM, or any combination of the system, the method, the integrated circuit, the computer program, and the storage medium.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. The embodiments described below all represent preferred specific examples of the present disclosure. The numerical values, shapes, materials, constituent elements, arrangement positions and connection forms of the constituent elements, steps, order of the steps, and the like shown in the following embodiments are examples, and are not intended to limit the present disclosure. Among the components in the following embodiments, components not described in the independent claims representing the uppermost concept of the present disclosure will be described as arbitrary components constituting a more preferable embodiment. In the present specification and the drawings, the same reference numerals are given to components having substantially the same functional configuration, and overlapping description is omitted.

(embodiment mode)

Next, a method of estimating the position of a moving object (biological body) to be detected by the estimation device 10 according to the embodiment will be described with reference to the drawings.

[ Structure of estimation device 10]

Fig. 1 is a block diagram showing an example of the configuration of an estimation device 10 according to the embodiment. Fig. 2 is a diagram showing an example of a detection target of the estimation device 10 shown in fig. 1.

The estimation device 10 shown in fig. 1 includes a transmitting antenna unit 11, a transmitting unit 12, a transmission signal generating unit 13, a receiving antenna unit 21, a receiving unit 22, a complex transfer function calculating unit 23, a moving object correlation matrix calculating unit 24, a subcarrier unifying unit 25, and an estimation processing unit 26. The estimation device 10 estimates the position of the living body 50 as a moving object, using the estimation device 10 as a reference of the direction or position.

[ transmitting antenna section 11]

The transmitting antenna unit 11 has M transmitting antenna elements. Here, M is a natural number of 1 or more. In addition, as for the number of receiving antenna elements N described below, when N is 1, M is a natural number of 2 or more. In the present embodiment, the transmitting antenna unit 11 has M_TA (M)_TA natural number of 2 or more) transmitting antenna elements. That is, the transmitting antenna part 11 has a structure consisting of M_TA transmission array antenna composed of a plurality of transmission antenna elements. M_TEach of the transmission antenna elements transmits a multicarrier signal (transmission wave) generated by the transmission unit 12 described below.

[ Transmission Signal Generation section 13]

The transmission signal generating unit 13 generates a multicarrier signal in which a plurality of subcarrier signals are modulated. Specifically, the transmission signal generator 13 generates a plurality of subcarrier signals corresponding to a plurality of subcarriers having different frequency bands, and multiplexes the generated plurality of subcarrier signals to generate a multicarrier signal. In the present embodiment, the transmission signal generating unit 13 generates an OFDM signal composed of S subcarriers as a multicarrier signal with high efficiency of using a Frequency band as an example, but the generation of a multicarrier signal obtained by multicarrier modulation is not limited to the generation of an OFDM signal in which subcarriers are orthogonal to each other, and other multicarrier signals such as a simple FDM (Frequency division multiplexing) signal may be generated.

The signal generated by the transmission signal generating unit 13 may be a signal common to the signal for communication.

[ transmitting part 12]

The transmission unit 12 applies appropriate processing to the signal generated by the transmission signal generation unit 13 to generate a transmission wave. The processing performed here is, for example, up-conversion of a signal from a band of an IF (Intermediate Frequency) to a band of an RF (Radio Frequency), amplification of a signal to an appropriate transmission level, or the like. As shown in fig. 2, the transmission unit 12 outputs the processed multicarrier signal to the transmission antenna unit 11, thereby causing the transmission antenna unit 11 to transmit the multicarrier signal. Thereby, M of the slave transmitting antenna unit 11_TEach of the plurality of transmit antenna elements transmits a multicarrier signal.

[ receiving antenna part 21]

The receiving antenna section 21 has N receiving antenna elements. Here, N is a natural number of 1 or more. When M, which is the number of transmitting antenna elements, is 1, N is a natural number of 2 or more. In the present embodiment, the receiving antenna unit 21 has M_RA (M)_RA natural number of 2 or more) receiving antenna elements. That is, the receiving antenna part 21 has a structure consisting of M_RA receiving array antenna composed of a plurality of receiving antenna elements. For example, as shown in FIG. 2, M_RRespective reception of a plurality of receiving antenna elements from the M_TEach of the transmitting antenna elements transmits a signal (reception signal) reflected by the living body 50.

[ receiving section 22]

The reception unit 22 observes a reception signal received by each of the N reception antenna elements and including a reflected signal obtained by reflecting or scattering a moving object from a multicarrier signal transmitted by each of the M transmission antenna elements for a 1 st period corresponding to a cycle of an operation of the moving object. Here, the moving object is a living body 50 as shown in fig. 2. The cycle of the motion of the moving object corresponds to, for example, a cycle derived from the activity of the living body 50. The period of the motion derived from the living body 50 is a period derived from the living body (living body fluctuation period) including at least half or more of respiration, heartbeat, and body movement of the living body 50.

The receiving part 22 will be composed of M_RA receiving dayThe high-frequency signal received by the line element is converted into a low-frequency signal that can be signal-processed. And the receiving parts 22 respectively correspond to M_RThe OFDM signals are demodulated into S subcarrier signals, respectively. Each of the S subcarrier signals is represented by an IQ symbol. The receiving part 22 will at least pass pair in the 1 st period by M_RS x M obtained by converting received high-frequency signals of receiving antenna elements_RThe group subcarrier signal is output to the complex transfer function calculation section 23. The receiving unit 22 may continuously observe the reception signal received by the receiving antenna unit 21, and continuously or periodically transmit S × M to the complex transfer function calculating unit 23_RGroup subcarrier signals.

[ Complex transfer function calculation section 23]

The complex transfer function calculating unit 23 uses a plurality of reception signals observed in the 1 st period in the receiving unit 22 for the received signal M_TA transmitting antenna element and N_RIn all combinations that can be achieved when the plurality of receiving antenna elements 1 are combined 1 by 1, that is, M × N combinations, a plurality of complex transfer functions indicating propagation characteristics between the transmitting antenna element and the receiving antenna element in each of a plurality of subcarriers corresponding to a plurality of subcarrier signals are calculated.

In the present embodiment, the complex transfer function calculation unit 23 uses the S × M transferred from the reception unit 22_RThe group subcarrier signals are obtained by calculating a complex transfer function indicating propagation characteristics between each transmitting antenna element and each receiving antenna element for each of the S subcarrier signals. Next, the description of sxm will be more specifically made with reference to fig. 2 and 3_RA method of calculating a complex transfer function for a subcarrier signal in a group of subcarrier signals. I.e. for S × M_REach of the group subcarrier signals similarly performs the complex transfer function calculation method described below.

In fig. 2 and 3, the transmission array antenna composed of the plurality of transmission antenna elements of the transmission antenna section 11 and the reception array antenna composed of the plurality of reception antenna elements of the reception antenna section 21 are both linear arrays of the element spacing d. The direction of the living body 50 viewed from the front of the transmission array antenna is represented by θ_TLet θ be the direction of the living body 50 viewed from the front of the receiving array antenna_R. Assuming that the distance between the living body 50 and the transmission array antenna and the distance between the living body 50 and the reception array antenna are sufficiently larger than the opening width of each array antenna, the transmission wave from the transmission array antenna and the reflection wave through the living body reaching the reception array antenna are regarded as plane waves.

As shown in fig. 2 and 3, M from the transmitting antenna part 11_TThe transmission waves transmitted by the transmitting antenna elements at an angle θ T are reflected by the living body 50 at an angle θ_RTo the receiving array antenna.

In this case, the complex transfer function calculation unit 23 can calculate a complex transfer function matrix from one subcarrier signal observed using the reception array antenna and the reception unit 22. One subcarrier signal is formed by multiple received signal vectors x ═ x1, …, x_MR]And (4) showing. The complex transfer function vector can, for example, be passed through h₀Calculated as x/s. Here, s is a retransmission signal, and is set to be known. The calculated complex transfer function matrix also includes reflected waves such as direct waves and reflected waves from a fixed object that do not pass through the living body 50.

Among the methods of calculating the complex transfer function from one subcarrier signal are methods of dividing a known signal such as a pilot signal or a guard interval signal by a received IQ symbol.

The complex transfer function calculation section 23 performs the calculation of the complex transfer function matrix for each of the S subcarrier signals, and outputs the obtained S complex transfer function matrices to the moving object correlation matrix calculation section 24.

The complex transfer function calculating unit 23 may continuously or periodically use each of the plurality of subcarrier signals output from the receiving unit 22 to continuously obtain the complex transfer function matrix. With this configuration, even when the estimation device 10 is configured to share hardware of the communication device, the estimation device 10 can use the complex transfer function matrix calculated continuously for use in the processing of the communication device.

[ moving object correlation matrix calculation section 24]

The moving object correlation matrix calculation unit 24 sequentially records the plurality of complex transfer function matrices calculated by the complex transfer function calculation unit 23 for each of the plurality of subcarriers and for each of the M × N combinations in time series which is the order in which the plurality of received signals are observed. Then, the moving object correlation matrix calculation unit 24 extracts a component related to the moving object from a plurality of complex transfer functions sequentially recorded in time series for each of the plurality of subcarriers and for each of the M × N combinations, thereby calculating a moving object correlation matrix expressed by a matrix of M × N dimensions for each of the plurality of subcarriers.

The moving object correlation matrix is a matrix in which a reflected wave or a scattered wave (biological component) via the biological body 50 included in the received signal is extracted. Some methods for obtaining a biological component from a complex transfer function recorded in time series use fourier transform disclosed in patent document 1 or difference information disclosed in patent document 2. In the present embodiment, a method of using the difference information will be specifically described. The following steps are performed for the complex transfer function matrices calculated for each of all subcarriers, but since all are expressed by the same formula and steps, the steps for obtaining a moving object correlation matrix for any one subcarrier will be described as typical.

First, the moving object correlation matrix calculation unit 24 calculates difference information of a plurality of complex transfer functions, which are sequentially recorded in time series for each of a plurality of subcarriers and for each of M × N combinations. That is, the moving object correlation matrix calculation unit 24 calculates 2 or more pieces of difference information representing differences between the 2 complex transfer functions at 2 times at predetermined intervals among the plurality of complex transfer functions, and expressed by a matrix of M × N dimensions. The moving object correlation matrix calculation section 24 calculates a moving object correlation matrix using the calculated 2 or more pieces of difference information. Here, the starting point of the 2 times at the predetermined interval in each of the 2 or more pieces of difference information is different times. The predetermined interval may be substantially half of the period derived from the living body 50 (living body fluctuation period).

Fig. 4 is a schematic diagram showing an example of 2 times at predetermined intervals used in calculating difference information in the embodiment. Fig. 5 is a schematic diagram showing an example of 2 times at predetermined intervals different from those in fig. 4. In fig. 4, the vertical axis represents the fluctuating channel value, and the horizontal axis represents time. In addition, T_measRepresenting the observed time of the received signal. The observation time T_measIs the above-mentioned period 1. Observation time T_measThe period corresponds to a maximum period of biological variation including at least one of respiration, heartbeat, and body movement of the living body, that is, a maximum period derived from biological variation. In the example shown in fig. 4, the observation time is set to approximately 3 seconds corresponding to the cycle of the respiratory activity of the living body 50.

At an observation time T as shown in FIG. 4_measWhen a time-varying channel, which is a plurality of complex transfer functions calculated from a received signal observed by the receiving unit 22, is sequentially recorded, the observation time T_measCorresponding to the maximum period of biological variation, and therefore the observation time T_measThe maximum value and the minimum value of the fluctuation of the organism 50 are included without fail. Here, if the maximum biological variation period is T_maxThe minimum period derived from the biological variation (biological variation minimum period) is denoted as T_minThen their half period is T_max/2、T_minThe time difference of/2 corresponds to the fluctuation of the living body 50. Therefore, the predetermined interval T in calculating the difference information of the complex transfer function can be set to T_max/2≦T≦T_minThe range of/2. In this way, even if the predetermined interval T is set to approximately half of the period (living body fluctuation period) derived from the living body 50, the living body-derived component can be extracted from the time-varying channel of 1 period of the living body 50.

In the example shown in fig. 4, the moving object correlation matrix calculation unit 24 calculates difference information indicating the difference in the complex transfer function between 2 times at a predetermined interval T, which is a time different from the time T + T, for example, and the moving object correlation matrix calculation unit 24 calculates the difference information a plurality of times at the predetermined interval T with the time obtained by shifting △ T each time as the starting point, that is, the moving object correlation matrix calculation unit 24 further performs the calculation of the difference information at the predetermined interval T (for different sets of complex transfer functions) at 2 different times, and here, calculates the difference information is to remove the complex transfer function component via a fixed object other than the living body 50 and to retain only the complex transfer function component via the living body 50.

In the present embodiment, the number of transmitting antenna elements and the number of receiving antenna elements are both 2 or more (i.e., a plurality of). Therefore, the number of difference values (difference information) corresponding to the complex transfer functions of the transmitting antenna unit 11 and the receiving antenna unit 21 becomes (the number of transmitting antenna elements: M)_T) X (number of receiving antenna elements: m_R) They are summed up to define a complex difference channel matrix H (l, m). The complex transfer function calculation unit 23 calculates a complex difference channel matrix H (l, m) as difference information, which is expressed as follows.

[ equation 1]

Here, 1 ≦ l, m ≦ N (l ≠ m, N is the total number of measurements). In addition, l and m are each a positive integer representing a measurement number, and are sampling times.

The elements of the complex difference channel matrix H (l, M) are arranged to calculate M represented by (formula 1)_RM_TComplex difference channel of x1 vector.

[ formula 2]

Here, vec (-) represents the transformation of the matrix into vectors, [. ]]T denotes transposition. In the example shown in fig. 4, N is the number of channel observations, and C is included in correspondence with N_tOr C_t+TThe number of vertices (data used for computation) of the trapezoid at 2 instants at equal time intervals T. At an observation time T_measIs 3 seconds, measuredWhen the number of observation was 100, N was 300.

The complex transfer function vector calculated by the complex transfer function calculation unit 23 includes, for example, a reflected wave that does not pass through the living body 50, such as a direct wave or a reflected wave from a fixed object, as shown in fig. 3. On the other hand, in the complex difference channel vector, all reflected waves that do not pass through the living body 50 are removed by the difference calculation of the complex transfer function vector at 2 times, and only the reflected waves originating from the living body are included. If this difference calculation is performed, there is a disadvantage that the complex transfer function of the reflected wave from the living body 50 is also subtracted, but the amplitude and phase of the reflected wave passing through the living body 50 constantly change with time due to the biological activity such as respiration and heartbeat, and therefore the complex difference channel vector does not become completely 0. That is, if the complex transfer function vectors at 2 different times are subtracted from each other, a vector obtained by multiplying the complex transfer function vector passing through the living body 50 by a coefficient remains.

The reason why the moving object correlation matrix calculation unit 24 calculates the difference information for a plurality of groups (complex transfer functions at different 2 times) is to reduce the influence of instantaneous noise by averaging a plurality of times and improve the accuracy of direction estimation as described below. The predetermined interval T at the time of calculating the difference information may be any predetermined interval, for example, a predetermined interval T 'between 2 times such as time T' and time T '+ T' shown in fig. 5, instead of the fixed value shown in fig. 4.

Next, the moving object correlation matrix calculation section 24 calculates a correlation matrix (hereinafter, referred to as "instantaneous correlation matrix") shown in (equation 2) from the complex difference channel vector. The 2 moments at the prescribed intervals, i.e., the differential time, are instantaneous and are thus called.

[ formula 3]

R_i(l,m)＝h_v(l,m)h_v ^H(l, m) (formula 2)

Here, [. cndot. ] H denotes a complex conjugate transpose.

In addition, the moving object correlation matrix calculation section 24 may further average (average operation) the instantaneous correlation matrix as shown in (equation 3). As described above, the influence of instantaneous noise can be weakened, and the accuracy of direction estimation can be improved.

[ formula 4]

Here, not only the estimation accuracy is improved compared to the case of using the instantaneous correlation matrix of (expression 2), but also it becomes possible to simultaneously estimate a plurality of arrival waves by using the correlation matrix of (expression 3). The correlation matrix obtained by (equation 3) in this way is referred to as a moving object correlation matrix.

The moving object correlation matrix calculation section 24 calculates the moving object correlation matrix obtained in the above-described procedure for all S subcarriers, and outputs the calculated moving object correlation matrix to the subcarrier unifying section 25. Since the complex transfer function of the living body 50 has frequency dependency and is different for each subcarrier, the S moving object correlation matrices calculated here have different components.

[ sub-carrier unifying unit 25]

The subcarrier unifying section 25 calculates a new moving object correlation matrix, i.e., a unified moving object correlation matrix, by unifying S moving object correlation matrices calculated for each of the S subcarriers by the moving object correlation matrix calculating section 24. As a method of unifying correlation matrices of moving objects, there is the following method: (i) averaging all components of a correlation matrix of the moving object; (ii) taking the median of each component of the correlation matrix of the moving object; and (iii) calculating the absolute value of the correlation matrix of the moving object, judging that the subcarriers with large absolute values and the subcarriers with small absolute values are large noise components except the moving object, removing the noise components at a predetermined ratio, and averaging the remaining correlation matrices of the moving object. In this embodiment, a method of averaging the components will be described using an equation.

In this way, the subcarrier unifying unit 25 can calculate the unified moving object correlation matrix by calculating the average of a plurality of moving object correlation matrices calculated in a plurality of subcarriers, respectively, to the average of 1 subcarrier. In this case, the subcarrier unifying unit 25 calculates a unified moving object correlation matrix by accumulating S components belonging to each of M × N components of S moving object correlation matrices obtained for each of S subcarriers, and dividing the accumulated value by S.

In addition, the subcarrier unifying section 25 may calculate the unified moving object correlation matrix by calculating the median of a plurality of moving object correlation matrices, which are calculated in a plurality of subcarriers, respectively, for each corresponding component. In this case, the subcarrier unifying unit 25 calculates the unified moving object correlation matrix by determining the median of S components belonging to each M × N component of the S moving object correlation matrices obtained for each of the S subcarriers.

The moving object correlation matrix for each subcarrier calculated by the moving object correlation matrix calculation unit 24 is set to R_iWhen (i is the subcarrier number), the subcarrier unifying unit 25 averages as shown in the following (equation 4).

[ formula 5]

By this averaging, the components included in the S moving object correlation matrices obtained from the respective S subcarriers can be unified into a single matrix, i.e., a unified moving object correlation matrix, and the accuracy of estimating the biological position can be improved.

[ estimation processing unit 26]

The estimation processing unit 26 estimates the direction or position of the moving object using the unified moving object correlation matrix calculated by the subcarrier unifying unit 25, with the estimation device 10 being used as a reference for the direction or position. The position estimation uses an arrival direction estimation algorithm such as MUSIC (Multiple Signal Classification) or Capon. The estimation method based on the MUSIC algorithm is explained here.

If the eigenvalue decomposition is performed on the moving object correlation matrix after the subcarriers shown in (equation 4) are unified, it can be written that:

[ formula 6]

R＝UΛU^H

[ formula 7]

[ formula 8]

In this connection, it is possible to use,

[ formula 9]

Is the number of elements M_RIs determined by the feature vector of (a),

[ equation 10]

Is a feature value corresponding to the feature vector, and is set as

[ formula 11]

The order of (a). L is the number of arrival waves, i.e., the number of living bodies to be detected.

In addition, a steering vector (direction vector) of the transmission array antenna is defined as:

[ formula 12]

The steering vector (direction vector) of the receiving array antenna is defined as:

[ formula 13]

Here, k is the number of waves. And, the steering vectors are multiplied together,

[ formula 14]

A steering vector is defined in consideration of angle information of both transmitting and receiving array antennas, and the MUSIC method is applied thereto.

That is, the estimation processing unit 26 can use the multiplied guide vector based on the MUSIC method, and perform the evaluation function P as shown below_music(θ) the local maximum value is searched for, and the direction of the transmission wave and the direction of the arrival wave are estimated.

[ formula 15]

In the present embodiment, two angles (θ) need to be aligned_T，θ_R) Since the maximum value of the evaluation function is searched, 2-dimensional search processing is performed. Then, the estimation processing unit 26 estimates two angles (θ) based on the two angles thus obtained_T，θ_R) The transmission direction of the transmission wave to the living body 50 and the arrival direction of the reflected wave from the living body 50 are estimated, and the position of the living body 50 is estimated from the intersection of the two estimated directions.

[ operation of the estimation device 10]

The operation of the estimation process of the estimation device 10 configured as described above will be described. Fig. 6 is a flowchart showing an estimation process of the estimation device 10 according to the embodiment.

First, the estimation device 10 starts from M_TEach transmitting antenna element transmits a multicarrier signal modulated with S subcarrier signals (S10).

Then, the estimation device 10 observes the received signal including the reflected signal reflected or scattered by the living body 50 for the 1 st period corresponding to the cycle of the motion of the moving object (S11).

Next, the estimation device 10 demodulates S subcarrier signals by performing multicarrier demodulation on the plurality of received signals observed in the 1 st period (S12).

Next, the estimation device 10 calculates a plurality of complex transfer functions indicating propagation characteristics between each transmitting antenna element and each receiving antenna element for each of the S subcarriers, using a plurality of reception signals observed in the reception unit 22 in the 1 st period (S13). These processes are performed in parallel or sequentially for each subcarrier. The details are as described above, and therefore, the description herein is omitted. The same applies below.

Next, the estimation device 10 calculates a moving object correlation matrix for each of the S subcarriers by extracting a component relating to the moving object from the complex transfer function of each of the S subcarriers (S14). This process is explained as the process performed by the moving object correlation matrix calculation unit 24, and thus a detailed explanation is omitted. Thus, S moving object correlation matrices are obtained.

Next, the estimation device 10 calculates a unified moving object correlation matrix by unifying the obtained S moving object correlation matrices by performing calculation for each of the S subcarriers (S15). This process is described as a process performed by the subcarrier consolidation unit 25, and thus a detailed description thereof is omitted.

Then, the estimation device 10 estimates the direction or position of the living body 50 using the calculated uniform moving object correlation matrix with the estimation device 10 as a reference of the direction or position (S16). That is, the estimation device 10 estimates the direction or position of the living body 50 with respect to the estimation device 10. Since this process is described as a process performed by the estimation processing unit 26, a detailed description thereof is omitted.

[ Effect and the like ]

According to the estimation device 10 and the estimation method of the present embodiment, by using a multicarrier signal such as OFDM for the transmission signal, the direction or position of the living body 50 with respect to the estimation device 10 can be estimated by using the original multicarrier transmitter-receiver. For example, an OFDM receiver is widely used as a conventional communication device, such as a mobile phone, a television broadcast receiver, and a wireless LAN device, and is lower in cost than a case of using a non-modulated signal.

In addition, in the estimation device 10, the direction or position of the living body 50 with respect to the estimation device 10 is estimated using a unified moving object correlation matrix obtained by unifying a plurality of moving object correlation matrices obtained for each of a plurality of subcarriers. Therefore, the position of the living body can be estimated with higher accuracy than in the case of using a single subcarrier. In particular, in the present embodiment, the moving object information included in the moving object correlation matrix of each subcarrier is superimposed by averaging a plurality of moving object correlation matrices obtained in correspondence with a plurality of subcarriers, not by averaging the complex transfer functions that cancel the fluctuation of the living body 50, and is processed at once by the estimation processing unit 26 thereafter. This makes it possible to restore the matrix rank during calculation, and to improve the estimation accuracy of the direction or position, which is the calculation result.

(modification 1)

The estimation device 10 according to the above-described embodiment has been described by taking as an example a device using a MIMO (Multiple Input Multiple Output) system in which both the transmitting antenna element and the receiving antenna element are plural, but is not limited thereto. The estimation device may be a device of SIMO (Single Input Multiple Output) or MISO (Multiple Input Single Output) system using a Single antenna element as one of a transmission antenna and a reception antenna.

In this case, each matrix described in the embodiment is in the form of a vector, but the same operation can be applied, and finally the direction of the living body 50 with respect to the estimation device can be estimated.

[ Effect and the like ]

According to this modification, the number of calculations of hardware and signal processing can be reduced by using a single transmitting antenna element or single receiving antenna element. Therefore, when information on the position of the living body 50 with respect to the estimation device is not required and information on the direction of the living body 50 is required, it can be realized at a lower cost than the MIMO system.

(modification 2)

In the moving object correlation matrix calculation unit 24 in the embodiment, the difference information is calculated to extract a component related to the moving object for each received signal of each subcarrier. Patent document 1 also discloses a method using fourier transform. However, in any of the methods, calculation with a large amount of calculation such as fourier transform or multiple difference calculation is required, and this is a problem when the method is mounted on commercially available inexpensive equipment. This modification realizes the processing of extracting the moving object components by the processing with a small amount of calculation.

Moving object correlation matrix calculation unit 24 according to modification 2

The operation of the moving object correlation matrix calculation unit 24 in the present modification will be described with reference to a schematic diagram of a reception waveform shown in fig. 7. The following description will be made as a representative example of a procedure for obtaining a moving object correlation matrix for a certain subcarrier, since the calculation processing of the moving object correlation matrix is performed for all subcarriers, respectively, but all operations are the same.

First, the moving object correlation matrix calculation section 24 calculates an average value in the 2 nd period of the complex transfer function (waveform shown by 1000 in fig. 7) output by the complex transfer function calculation section 23. Here, the 2 nd period is preferably the same as or longer than the 1 st period corresponding to the cycle of the activity of the living body 50, for example. In fig. 7, the 2 nd period is represented by 2 sections 1002A and 1002B. The average value calculated here corresponds to a complex transfer function component via a fixed object other than the living body 50. In order to flexibly cope with a change in environment other than a living body, the length of the period may be variable based on the amplitude of the complex transfer function or the like.

Next, the moving object correlation matrix calculation unit 24 calculates a complex transfer function (waveform shown by 1001 in fig. 7) excluding the complex transfer function component via the fixed object other than the living body 50 by subtracting the average value from the original complex transfer function.

Then, the moving object correlation matrix calculation unit 24 extracts a fluctuation component corresponding to the biological component included in the complex transfer function. More specifically, the values obtained by integrating the amplitudes shown in the lower part of fig. 7 in the time direction (the areas of the smeared portions of the waveforms shown by 1001 of fig. 7), the mean square, and the average absolute values are given. The integrated value, mean square, and average absolute value are information equivalent to the moving object correlation matrix in the embodiment.

That is, the moving object correlation matrix calculation unit 24 calculates an average value in the 2 nd period of a plurality of complex transfer functions recorded in time series for each of a plurality of subcarriers and for each of M × N combinations, subtracts the average value from the complex transfer function for each of the plurality of complex transfer functions in the 2 nd period, and calculates the moving object correlation matrix using the subtraction result.

The moving object correlation matrix for each subcarrier calculated in this way is output to the subcarrier integrating unit 25, and is processed in the same manner as in the embodiment to estimate the direction or position of the living body 50 with respect to the estimation device 10. That is, the estimation device in this case includes: a transmitting antenna unit having M (M is a natural number of 1 or more, M ≧ 2 when N is 1) transmitting antenna elements; a transmission signal generation unit that generates a transmission signal; a transmitting section that outputs the transmission signal to the transmitting antenna section, thereby causing the transmitting antenna section to transmit the transmission signal; a reception antenna unit having N (N is a natural number of 1 or more, where N ≧ 2 when M is 1) reception antenna elements; a reception unit configured to observe a reception signal received by each of the N reception antenna elements and including a reflected signal obtained by reflecting or scattering the transmission signal transmitted from each of the M transmission antenna elements by a moving object, the reception signal corresponding to a 1 st period of a cycle of the motion of the moving object; a complex transfer function calculation unit that calculates, using the plurality of received signals observed in the reception unit during the 1 st period, a plurality of complex transfer functions representing propagation characteristics between the transmitting antenna element and the receiving antenna element in each of M × N combinations that are all combinations that can be obtained when the M transmitting antenna elements and the N receiving antenna elements are combined 1 to 1; a moving object correlation matrix calculation unit that, for each of the M × N combinations, (i) sequentially records the plurality of complex transfer functions calculated by the complex transfer function calculation unit in time series in the order in which the plurality of received signals are observed, (ii) calculates an average value in a period 2 of the plurality of complex transfer functions sequentially recorded in time series, and (iii) calculates a moving object correlation matrix of an M × N matrix by subtracting the average value from the complex transfer function for each of the plurality of complex transfer functions in the period 2; and an estimation processing unit configured to estimate a direction or position of the moving object using the estimation device as a reference of the direction or position, using the moving object correlation matrix calculated by the moving object correlation matrix calculation unit.

The operation of the moving object correlation matrix calculation unit 24 in the present modification is not limited to the case where the transmission wave is used for a multicarrier signal, and the same applies to the case where the transmission wave is used for a single carrier signal.

[ Effect and the like ]

According to the present modification, the moving object correlation matrix calculation unit 24 can calculate the moving object correlation matrix by simple calculation such as averaging and subtraction without performing complicated calculation such as fourier transform and calculation of a plurality of differences. Therefore, the processing load for calculating the correlation matrix of the moving object can be reduced. In addition, compared to a case where an unmanned waveform or the like is prepared in advance, since a component to be subtracted is generated from the latest received waveform, the present invention can also be applied to a change in environment such as opening and closing of a detection gate.

As described above, according to the present disclosure, it is possible to realize an estimation device and an estimation method that can estimate the direction or position of a moving object with respect to the own device in a short time and with high accuracy using a wireless signal.

The estimation device and the estimation method according to one embodiment of the present disclosure have been described above based on the embodiments, but the present disclosure is not limited to these embodiments. Various modifications of the present embodiment, or a combination of components of different embodiments, which are suggested to one skilled in the art, are also included in the scope of the present disclosure, as long as they do not depart from the spirit of the present disclosure.

For example, in the above-described embodiment and modifications 1 and 2 thereof, the direction estimation and the position estimation of the living body 50 have been described as examples, but the target of the estimation process is not limited to the living body 50. The target of the estimation processing may be various moving objects (machines or the like) to which the reflected wave doppler effect is given due to movement or motion when a high-frequency signal is irradiated.

The present disclosure having such characteristic components can be realized not only as an estimation device but also as an estimation method or the like in which the characteristic components included in the estimation device are used as steps. The present invention can also be realized as a computer program for causing a computer to execute the characteristic steps included in the above-described method. It is also possible to distribute such a computer program via a non-transitory storage medium readable by a computer such as a CD-ROM or a communication network such as the internet.

The estimation device according to one or more embodiments has been described above based on the embodiments, but the present disclosure is not limited to the embodiments. Various modifications of the present embodiment, or a combination of components of different embodiments, which are suggested to one skilled in the art, are also included in the scope of the present disclosure, as long as they do not depart from the spirit of the present disclosure.

Industrial applicability of the invention

The present disclosure can be used in an estimation device and an estimation method for estimating the direction or position of a moving object using a wireless signal, and particularly, can be used in a positioning sensor mounted on a measuring device for measuring the direction or position of a moving object including a living body and a machine, a home appliance for performing control corresponding to the direction or position of a moving object, a monitoring device for detecting intrusion of a moving object, and the like, and a direction estimation method.

Quantitative interpretation of a reference number

10 estimating device

11 transmitting antenna part

12 transmitting part

13 transmission signal generating section

21 receiving antenna part

22 receiving part

23 complex transfer function calculating part

24 moving object correlation matrix calculating section

25 sub-carrier integration part

26 estimation processing part

50 organisms

Complex transfer function before 1000 minus mean

1001 complex transfer function after subtraction of the mean value

1002A, 1002B averaging the complex transfer functions for a predetermined period