JP6917585B2 - Positioning sensors, sensors, and methods - Google Patents

Description

The present invention relates to positioning sensors, sensors, and methods for living organisms such as humans using microwaves.

As a method of knowing the position and state of a person, a method of using a wireless signal is being studied. For example, Patent Document 1 discloses an estimation method capable of knowing the position or state of a person to be detected by analyzing a component including a Doppler shift using a Fourier transform.

Japanese Unexamined Patent Publication No. 2015-117772 Japanese Unexamined Patent Publication No. 2015-072173 Japanese Unexamined Patent Publication No. 2015-119770 Special Table 2014-512526 Gazette Japanese Unexamined Patent Publication No. 2014-215200 Japanese Unexamined Patent Publication No. 2015-117961 Japanese Unexamined Patent Publication No. 2006-329658 JP-A-2015-175700 Japanese Unexamined Patent Publication No. 2008-2446997

F. Adib, Z. Kabelac, D.M. Katabi, and R. Miller, "3D tracking via body radio reflections", 11th USENIX Symp. Net. Systems Design & Impl. (USENIX NSDI '14), Apr. 2014. Dai Sasakawa, Keita Konno, Naoki Honma, Kentaro Nishimori, Nobuyasu Takemura, Tsutomu Mitsui, "Fast Estimation Algorithm for Living Body Radar", 2014 International Symposium on Antennas and Propagation (ISAP 2014), FR3D, pp. 583-584, Dec. 2014 Purapus Cyril, Chou Shun, Tayufer Eddie, Akifumi Hirata, Takashi Ohira, "Reactance Domain MUSIC Method by Espa Antenna", IEICE Technical Report, RCS2002-147, pp. 1-8, August 2002.

However, in the prior art disclosed in Patent Document 1 and the like, the phase on the transmitter side is used to estimate the position or direction of a person, such as the need for a plurality of antennas capable of observing the delay time or phase information of the incoming wave. You need to get the information.

The present invention has been made in view of the above circumstances, and is a positioning sensor capable of estimating the direction in which a moving object exists from a radio signal received on the receiving side without acquiring phase information on the transmitting side. And so on.

In order to solve the above problems, the positioning sensor according to one aspect of the present invention is a positioning sensor, which includes m receiving antennas (m is an integer of 1 or more), a feeding circuit connected to the receiving antenna, and a feeding circuit. Transmission transmitted from the transmitter to a predetermined range in which a moving object may exist from the positioning sensor via the n variable loads (n is an integer of 1 or more) connected to the power supply circuit and the power supply circuit. The receiver that receives the first signal, which is the signal received by the receiving antenna, the controller that sets the impedance value of the variable load, and the setting when the impedance value of the variable load is set by the controller. In the memory that stores the first signal strength value indicating the strength of the first signal corresponding to the impedance value of the variable load, and the complex propagation channel showing the signal propagation characteristics between the transmitter and the receiver. On the other hand, a plurality of candidates are set, a plurality of second signal strength values when the receiver receives the second signal transmitted from the transmitter are calculated, and the second signal strength value is the second signal. The plurality of second signal strength values correspond to the plurality of candidates, and the difference between the first signal strength value and the plurality of second signal strength values is the smallest. The present invention includes a processor that estimates the complex propagation channel by selecting a corresponding candidate and estimates the arrival direction of the first signal with respect to the positioning sensor based on the complex propagation channel.

Further, the sensor according to one aspect of the present invention includes a plurality of the above-mentioned positioning sensors arranged at different positions from each other, and based on the arrival direction of each of the first signals in each of the plurality of positioning sensors, the moving object Estimate the position.

Further, the positioning sensor according to one aspect of the present invention is a positioning sensor, which is connected to m (m is an integer of 1 or more) receiving antennas, a feeding circuit connected to the receiving antenna, and the feeding circuit. The receiving antenna transmits n variable loads (n is an integer of 1 or more) and transmission signals transmitted from the transmitter to a predetermined range in which a moving object can exist from the positioning sensor via the feeding circuit. The controller includes a receiver that receives the first signal, which is a signal received by the user, a controller that sets the impedance value of the variable load, a memory, and a processor, and the controller passes the impedance value of the variable load in K ways. (K is an integer of 2 or more) is set, and the receiver receives each of the first signals corresponding to the impedance value of the variable load set according to each of the K ways L times (L is an integer of 2 or more). The memory is a first signal strength value indicating the strength of the first signal, and the L first signal strength values corresponding to the impedance values of the variable load set according to each K are used. The processor calculates each average value by averaging the L first signal strength values corresponding to the impedance values of the variable load set in each K way, and each K way. By subtracting each corresponding average value from the L first signal strength values corresponding to the impedance value of the variable load set in, K × L second signal strength values are calculated and transmitted. M complex propagation channels showing signal propagation characteristics between the machine and the receiver and having K elements for each of the L complex propagation channels corresponding to the L first signals. Candidates (M is an integer of 2 or more) are set, and for each of the L complex propagation channels, the signal strength estimated to be received by the receiver when the variable load is set according to the K. The M third signal strength values having the K elements indicating the values are calculated, and the second signal strength values corresponding to the M third signal strength values are calculated for each of the L complex propagation channels. The L complex propagation channels are estimated by selecting the candidate corresponding to the minimum difference among the differences from the signal strength value, and the correlation matrix for each L complex propagation channel is calculated. Based on the correlation matrix, the direction of arrival of the first signal with respect to the positioning sensor is estimated.

It should be noted that these general or specific embodiments may be realized in a recording medium such as a system, method, integrated circuit, computer program or computer readable CD-ROM, system, method, integrated circuit, computer program. And any combination of recording media may be realized.

According to the present invention, it is possible to estimate the direction in which a moving object exists from the radio signal received on the receiving side without acquiring the phase information on the transmitting side.

FIG. 1 is a block diagram showing an example of the configuration of the positioning sensor according to the first embodiment. FIG. 2 is a block diagram showing an example of the functional configuration of the processor of the first embodiment. FIG. 3 is a flowchart showing an outline of the direction estimation process of the positioning sensor according to the first embodiment. FIG. 4 is a flowchart showing the details of the direction estimation process of the positioning sensor according to the first embodiment. FIG. 5 is a flowchart showing the details of step S23 shown in FIG. FIG. 6 is a flowchart showing the details of step S24 shown in FIG. FIG. 7 is a diagram showing a circuit model of the antenna model of the first embodiment. FIG. 8 is a diagram showing an example of the configuration of the direction estimation unit according to the second embodiment. FIG. 9 is a flowchart showing the direction estimation process of the direction estimation unit 740 according to the second embodiment. FIG. 10 is a diagram showing a flow of the direction estimation process of the direction estimation unit in the second embodiment. FIG. 11 is a diagram showing an example of the configuration of the direction estimation unit according to the third embodiment. FIG. 12 is a flowchart showing the direction estimation process of the direction estimation unit 840 according to the third embodiment. FIG. 13 is a diagram showing a flow of the direction estimation process of the direction estimation unit 840 in the third embodiment. FIG. 14 is a diagram showing an example of the configuration of the memory and the complex propagation channel estimation unit in the fourth embodiment. FIG. 15 is a diagram showing an example of the configuration of the direction estimation unit according to the fourth embodiment. FIG. 16 is a flowchart showing an estimation process of the memory 600 according to the fourth embodiment. FIG. 17 is a flowchart showing an estimation process of the complex propagation channel estimation unit 710 according to the fourth embodiment. FIG. 18 is a flowchart showing the estimation process of the direction estimation unit 940 according to the fourth embodiment. FIG. 19 is a diagram showing the concept of an experiment using the direction estimation method in the fourth embodiment. FIG. 20 is a diagram showing the experimental results using the estimation method in the fourth embodiment. FIG. 21 is a diagram showing an example of arrangement of a feeding circuit, a variable load, and a receiving antenna in the positioning sensor. FIG. 22 is a diagram showing another example of the arrangement of the feeding circuit, the variable load, and the receiving antenna in the positioning sensor.

(Knowledge that became the basis of the present invention)
As a method of knowing the position or state of a person, a method of using a wireless signal is being studied.

For example, Patent Document 1 discloses a method of knowing the position or state of a person to be detected by analyzing a component including a Doppler shift using a Fourier transform. More specifically, in Patent Document 1, first, an array antenna composed of a plurality of antenna elements is used for both transmission and reception, and a complex propagation channel between the array antennas is observed. The complex propagation channel is represented by a matrix having an element of the number of transmitting antennas × the number of receiving antennas. In the complex propagation channel, the absolute value of each element (complex propagation channel element) represents the amplitude, and the argument of the complex propagation channel element represents the phase. Next, the time response of the complex propagation channel element is Fourier transformed to obtain a frequency response matrix, and then only the AC component is extracted. This operation is equivalent to extracting the Doppler shift component. The extracted AC components are also represented by a matrix. Then, the correlation matrix is obtained from the AC component of the frequency response matrix, and the direction and position of the detection target are detected by estimating the arrival direction.

Further, for example, in Patent Documents 2 to 5, similarly to Patent Document 1, the Doppler component derived from the person (living body) to be detected is extracted and analyzed by Fourier transforming the observed signal. By doing so, a method of sensing the position of the living body and the state such as the heartbeat and respiration of the living body is disclosed. Patent Document 6 discloses a method of performing high-speed beam scanning by adjusting a variable impedance array and estimating the signal arrival direction from the object from the reflected wave. Patent Document 7 discloses a method of estimating the position of a target object by installing sensors having directivity using a plurality of frequencies in different directions and estimating the distance and angle to the target from the reflected waves. Has been done. Patent Document 8 discloses a method of estimating the position of a target object, including a plurality of antennas capable of observing the delay time or phase information of the incoming wave. Patent Document 9 discloses a method of manipulating antenna directivity by configuring an Espa antenna using an inverted F antenna with a feeding circuit.

Further, for example, Non-Patent Document 1 discloses a method of detecting the direction or position of a human body without performing a Fourier transform. In Non-Patent Document 1, as a method of extracting a variable component without performing a Fourier transform, the propagation response of an unmanned state is measured in advance, and the difference between the unmanned state and the manned state is considered to be caused by a person. The position of the person is estimated by analyzing the components. In this method, in order to estimate the position, the frequency response in a wide band of 1 GHz or more is observed, and the propagation time of the extracted reflected wave derived from the person is calculated, so that the antennas are placed at different locations. The distance is estimated, and the position of the person is estimated using the estimated distance. In Non-Patent Document 2, the time response of the complex propagation channels when manned is observed, and the reflection components from the fixed objects such as walls and fixtures are removed by subtracting the complex propagation channels at different times. Extract only the reflected wave.

Further, for example, Non-Patent Document 3 discloses a method of estimating the arrival direction of radio waves using a non-feeding antenna. In Non-Patent Document 3, a device including a one-element feeding antenna and a plurality of non-feeding antennas surrounding the feeding antenna, that is, a single receiver capable of observing the phase is connected to the one-element receiving antenna (feeding antenna). Disclosed is a device in which a plurality of non-feeding antennas to which a variable load is connected are arranged in a circle around a receiving antenna. Since the received signal of the receiver changes according to the variable load value of the non-feeding antenna, the arrival direction of the radio wave is determined from the response (complex signal received at that time) in which the variable load value of the non-feeding antenna is changed. Can be estimated.

However, for example, the single-element antennas disclosed in Patent Documents 4 to 5 are sufficient for detecting the Doppler shift caused by the person's respiration or heartbeat, but are sufficient for estimating the position or direction of the person. Multiple antennas are required that can observe the delay time or phase information of.

That is, it is impossible to estimate the direction and position of a person with a single element antenna as in Patent Documents 4 to 5.

Further, in the methods disclosed in Patent Documents 1 to 6 and the methods disclosed in Non-Patent Documents 1 and 2, a plurality of antennas are used, and the direction and position of a person can be estimated. However, in order to estimate the direction or position of a person, a plurality of precise receivers capable of measuring the delay time and phase of a signal are required. This has a problem of increasing the cost of the device.

Further, in the method disclosed in Non-Patent Document 3, a single receiver capable of observing the phase is connected to a receiving antenna of one element, and a plurality of non-feeding antennas to which a variable load is connected are connected to the receiving antenna. It is arranged in a circle around it. In this method, the direction of the incoming wave is estimated from the response in which the value of the variable load of the non-feeding antenna is changed. However, the method disclosed in Non-Patent Document 3 has a problem that the same received signal needs to arrive every time the value of the variable load is switched, and it is necessary to know the accurate phase value of the received signal. This means that the transmitter and receiver reference oscillators must be perfectly synchronized at the phase level or a common reference oscillator must be used. That is, for example, when the transmitter and the receiver are arranged apart from each other, it is difficult to connect them to each other, so that there is a problem that an expensive reference oscillator capable of synchronizing at the phase level is required. This is because the fluctuation of the complex propagation channel caused by the living body has a period of one second order, and therefore it is necessary to maintain a state in which the phase level is synchronized at least during that period. It is also for distinguishing whether the fluctuation of the complex propagation channel is due to the living body or the frequency difference of the reference oscillator between the transceivers.

In the method disclosed in Patent Document 6, it is possible to estimate the direction in a narrow range using a beam having a narrow directivity, but a beam having a wide directivity is required for estimating the direction in a wide range. .. That is, in the method disclosed in Patent Document 6, since the transmitter itself is unnecessary, the phase information on the transmitter side is unnecessary, but there is a problem that the resolution of direction estimation is low. Similarly, the method disclosed in Patent Document 7 has a problem that when the number of antennas is reduced in a wide range of direction estimation, the overlapping range between the antennas is narrowed and the resolution of the direction estimation is lowered.

Further, in recent years, an array antenna that estimates the direction of existence of a living body in a radio wave propagation environment in which multiple waves exist is used by utilizing the feature that the living body causes Doppler shift in radio waves due to some biological activity such as respiration and heartbeat. The radar used is being studied. That is, a radar that estimates the living body direction by irradiating the living body with radio waves, removing signal components that do not pass through the living body by Fourier transform of the received signal, and estimating the arrival direction of the radio waves reflected from the living body is being studied.

However, in order to configure such an array antenna, a receiver is required for each element antenna, and there is a problem that the hardware scale increases. Further, it is necessary to accurately know the phase difference between the element antennas of the received signal, which also causes an increase in the hardware scale.

In view of these facts, the inventors estimate the direction in which the moving object exists from the radio signal received on the receiving side having a simple hardware configuration (small number of receivers) that does not acquire the phase information on the transmitter side. I came up with positioning sensors, sensors, and methods that can do this.

The positioning sensor according to one aspect of the present invention is a positioning sensor, which is connected to m (m is an integer of 1 or more) receiving antennas, a feeding circuit connected to the receiving antenna, and the feeding circuit. The receiving antenna receives n (n is an integer of 1 or more) variable loads and transmission signals transmitted from the transmitter to a predetermined range in which a moving object may exist from the positioning sensor via the feeding circuit. The receiver that receives the first signal, which is the signal, the controller that sets the impedance value of the variable load, and the impedance of the variable load that is set when the impedance value of the variable load is set by the controller. A plurality of candidates are set for the memory that stores the first signal strength value indicating the strength of the first signal corresponding to the value and the complex propagation channel that shows the signal propagation characteristics between the transmitter and the receiver. Then, a plurality of second signal strength values when the receiver receives the second signal transmitted from the transmitter are calculated, and the second signal strength value indicates the strength of the second signal, and the plurality of values indicate the strength of the second signal. The second signal strength value corresponds to each of the plurality of candidates, and the candidate corresponding to the minimum difference among the differences between the first signal strength value and each of the plurality of second signal strength values is selected. Includes a processor that estimates the complex propagation channel and estimates the direction of arrival of the first signal with respect to the positioning sensor based on the complex propagation channel.

As a result, it is possible to estimate the direction in which the moving object exists from the radio signal received on the receiving side without acquiring the phase information on the transmitting side. Further, since the m receiving antennas are connected to the power feeding circuit, the degree of freedom in arranging the m receiving antennas can be improved.

Further, for example, when the time variation of the first signal strength value is equal to or less than a predetermined value, the processor estimates the first complex propagation channel as the complex propagation channel, and the time variation of the first signal intensity value is the predetermined value. When it is larger than the value, the second complex propagation channel is estimated as the complex propagation channel, the first correlation matrix showing the correlation matrix for the first complex propagation channel is calculated, and the correlation matrix for the second complex propagation channel is shown. The 2 correlation matrix is calculated, the 3rd correlation matrix is calculated by subtracting the 1st correlation matrix from the 2nd correlation matrix, and the arrival of the 1st signal to the positioning sensor based on the 3rd correlation matrix. The angle may be estimated.

Further, for example, when the time variation of the first signal intensity value is equal to or less than the predetermined value, the first signal does not include the reflected signal whose transmission signal is reflected by the moving body, and the time of the first signal intensity value is not included. When the variation is greater than the predetermined value, the first signal may include the reflected signal.

Further, for example, the processor estimates the first complex propagation channel as the complex propagation channel at the first time, and sets the second complex propagation channel as the complex propagation channel at the second time after the first time. Estimate, use the first complex propagation channel and the second complex propagation channel to calculate the phase difference between the first complex propagation channel and the second complex propagation channel, and the phase at which the phase difference is minimized. The third complex propagation channel is calculated by determining the angle and subtracting the first complex propagation channel given the phase angle from the second complex propagation channel given the phase angle, and calculating the third complex propagation channel. The correlation matrix for the propagation channel may be calculated, and the arrival angle of the first signal with respect to the positioning sensor may be estimated based on the correlation matrix.

Further, the sensor according to one aspect of the present invention includes a plurality of the above-mentioned positioning sensors arranged at different positions from each other, and based on the arrival direction of each of the first signals in each of the plurality of positioning sensors, the moving object Estimate the position.

Further, the positioning sensor according to one aspect of the present invention is a positioning sensor, which is connected to m (m is an integer of 1 or more) receiving antennas, a feeding circuit connected to the receiving antenna, and the feeding circuit. The receiving antenna transmits n variable loads (n is an integer of 1 or more) and transmission signals transmitted from the transmitter to a predetermined range in which a moving object can exist from the positioning sensor via the feeding circuit. The controller includes a receiver that receives the first signal, which is a signal received by the user, a controller that sets the impedance value of the variable load, a memory, and a processor, and the controller passes the impedance value of the variable load in K ways. (K is an integer of 2 or more) is set, and the receiver receives each of the first signals corresponding to the impedance value of the variable load set according to each of the K ways L times (L is an integer of 2 or more). The memory is a first signal strength value indicating the strength of the first signal, and the L first signal strength values corresponding to the impedance values of the variable load set according to each K are used. The processor calculates each average value by averaging the L first signal strength values corresponding to the impedance values of the variable load set in each K way, and each K way. By subtracting each corresponding average value from the L first signal strength values corresponding to the impedance value of the variable load set in, K × L second signal strength values are calculated and transmitted. M complex propagation channels showing signal propagation characteristics between the machine and the receiver and having K elements for each of the L complex propagation channels corresponding to the L first signals. Candidates (M is an integer of 2 or more) are set, and for each of the L complex propagation channels, the signal strength estimated to be received by the receiver when the variable load is set according to the K. The M third signal strength values having the K elements indicating the values are calculated, and the second signal strength values corresponding to the M third signal strength values are calculated for each of the L complex propagation channels. The L complex propagation channels are estimated by selecting the candidate corresponding to the minimum difference among the differences from the signal strength value, and the correlation matrix for each L complex propagation channel is calculated. Based on the correlation matrix, the direction of arrival of the first signal with respect to the positioning sensor is estimated.

It should be noted that these general or specific embodiments may be realized in a recording medium such as a system, method, integrated circuit, computer program or computer readable CD-ROM, system, method, integrated circuit, computer program. And any combination of recording media may be realized.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. It should be noted that all of the embodiments described below show a preferred specific example of the present invention. Numerical values, shapes, materials, components, arrangement positions and connection forms of components, steps, order of steps, etc. shown in the following embodiments are examples, and are not intended to limit the present invention. Further, among the components in the following embodiments, the components not described in the independent claims indicating the highest level concept of the present invention will be described as arbitrary components constituting the more preferable form. In the present specification and the drawings, components having substantially the same functional configuration are designated by the same reference numerals, so that duplicate description will be omitted.

(Embodiment 1)
[1-1. Positioning sensor configuration]
FIG. 1 is a block diagram showing an example of the configuration of the positioning sensor according to the first embodiment. FIG. 2 is a block diagram showing an example of the functional configuration of the processor of the first embodiment.

The positioning sensor 100 shown in FIG. 1 includes m (m is an integer of 1 or more) receiving antennas 10, a feeding circuit 20 connected to the m receiving antenna 10, and n (m) connected to the feeding circuit 20. It includes a variable load 30 (n is an integer of 1 or more), a receiver 40, a controller 50, a memory 60, and a processor 70. The positioning sensor 100 may further include a transmitter 80 to which the transmitting antenna 81 is connected. Positioning sensor 100 estimates the direction theta _R in the presence of biological 90 to be detected.

The m receiving antennas 10 form an array antenna by arranging them in the first direction. The m receiving antennas 10 may form an array antenna by arranging them in the first direction and the second direction.

The receiver 40 receives the first signal via the power supply circuit 20. The first signal received by the receiver 40 is a signal received by the receiving antenna 10 from the positioning sensor 100 in a predetermined range in which a moving object may exist.

For example, one transmitting antenna 81 connected to the transmitter 80 transmits a signal (that is, a transmitting wave) generated by the transmitter 80. Then, the signals (that is, reflected waves) that have reached the m receiving antennas 10 are modulated by the n variable loads 30 connected to the feeding circuit 20 and again observed by the receiver 40 via the feeding circuit 20. ..

The controller 50 controls n variable loads 30. More specifically, the controller 50 sets the impedance values of n variable loads 30.

When the impedance values of n variable loads 30 are set by the controller 50, the memory 60 sets a first signal strength value indicating the strength of the first signal corresponding to the set impedance values of the n variable loads 30. Remember. That is, the memory 60 sets the first signal strength value of the first signal received by the receiver 40 when the impedance values of the n variable loads 30 are set to the first values by the controller 50, together with the first value. Remember. More specifically, the memory 60 stores the first signal strength value of the first signal received by the receiver 40 in synchronization with the controller 50. Therefore, in the memory 60, the first signal strength values corresponding to the changes of n variable loads 30 are stored in time series. The memory 60 stores the first signal strength value as strength information. In the present embodiment, the stored first signal strength value is only the amplitude. That is, the phase cannot be observed.

The processor 70 performs various processes using the first signal strength value stored in the memory 60. The functional configuration of the processor 70 will be described with reference to FIG.

As shown in FIG. 2, the processor 70 functionally includes a complex propagation channel estimation unit 71 and a direction estimation unit 74.

The complex propagation channel estimation unit 71 includes a signal calculation unit 72 and a comparison calculation unit 73.

The signal calculation unit 72 calculates the second signal strength value of the second signal from the trial complex propagation channel set to a predetermined value. Specifically, the signal calculation unit 72 sets a plurality of candidates for the complex propagation channel showing the signal propagation characteristics between the transmitter 80 and the receiver 40, and the second signal transmitted from the transmitter 80. Is calculated by assuming that the receiver 40 has received the above. Here, the second signal strength value indicates the strength of the second signal. Further, each of the plurality of second signal strength values corresponds to a plurality of candidates.

The comparison calculation unit 73 uses the value of the variable load 30 to select a candidate corresponding to the minimum difference among the differences between the first signal strength value and each of the plurality of second signal strength values, thereby selecting the complex propagation channel. Search for the value of. That is, the comparison calculation unit 73 calculates a plurality of differences by calculating the difference between the first signal strength value and the second signal strength value for each of the plurality of second signal strength values. Then, the comparison calculation unit 73 selects a candidate corresponding to the second signal strength value from which the minimum difference is obtained from the plurality of calculated differences. The comparison calculation unit 73 estimates the complex propagation channel corresponding to the selected candidate as the complex propagation channel when the receiver 40 receives the first signal. In this way, the complex propagation channel estimation unit 71 estimates the complex propagation channel when the receiver 12 receives the first signal from the first intensity signal value output from the memory 60.

_{The direction estimation unit 74 estimates the arrival direction θ R} of the first signal with respect to the positioning sensor 100 based on the complex propagation channel estimated by the complex propagation channel estimation unit 71. In the present embodiment, as shown in FIG. 1, the first signal is a reflected wave of the living body 90. Therefore, the direction estimation unit 74 can estimate the direction in which the living body 90 exists from the complex propagation channel estimated by the complex propagation channel estimation unit 71.

[1-2. Positioning sensor operation]
The operation of the estimation process of the positioning sensor 100 configured as described above will be described. FIG. 3 is a flowchart showing an outline of the direction estimation process of the positioning sensor according to the first embodiment.

First, in the positioning sensor 100, the controller 50 sets the impedance value of the variable load 30 (S11).

The receiver 40 receives the first signal (S12).

When the impedance values of n variable loads 30 are set by the controller 50, the memory 60 sets a first signal strength value indicating the strength of the first signal corresponding to the set impedance values of the n variable loads 30. Remember (S13).

The processor 70 sets a plurality of candidates for the complex propagation channel exhibiting the signal propagation characteristics between the transmitter 80 and the receiver 40 (S14).

The processor 70 calculates a plurality of second signal strength values assuming that the receiver 40 has received the second signal transmitted from the transmitter 80 (S15).

The processor 70 estimates the complex propagation channel by selecting a candidate corresponding to the minimum difference among the differences between the first signal strength value and each of the plurality of second signal strength values (S16).

The processor 70 estimates the direction of arrival of the first signal with respect to the positioning sensor 100 based on the complex propagation channel (S17).

Hereinafter, the details of the direction estimation process of the positioning sensor 100 described with reference to FIG. 3 will be described with reference to FIGS. 4, 5 and 6.

FIG. 4 is a flowchart showing the details of the direction estimation process of the positioning sensor according to the first embodiment. FIG. 5 is a flowchart showing the details of step S23 shown in FIG. FIG. 6 is a flowchart showing the details of step S24 shown in FIG.

As shown in FIG. 4, first, the transmitter 80 starts transmitting a signal (S21). In the present embodiment, the transmitter 80 shown in FIG. 1 transmits a signal (transmitted wave) from the transmitting antenna 81.

Here, the living body 90 is stationary in the _{direction θ R} when viewed from the array antenna composed of m receiving antennas 10.

By the way, the positioning sensor 100 measures and stores the ^{intensity information y (l)} _{meas (S22).} Here, the intensity information y ^(l) _meas is the first signal intensity value of the first signal received by the receiver 40. l is an index number and indicates the number of times the complex propagation channel is estimated from the intensity information.

More specifically, as shown in FIG. 5, first, the controller 50 sets the values of n variable loads 30 (S31). Here, the positioning sensor 100 will be described as including m receiving antennas 10 terminated by the variable load 30 respectively. In this case, the values of n variable loads 30 (variable impedance values) can be expressed as _{Z k} = [z _k1 , ..., z _{kn] using the number of trials k.} Subsequently, the receiver 40 measures the signal strength | yk | (S32). The positioning sensor 100 changes the values of n variable loads 30 and repeats the processes of S31 and S32. The positioning sensor 100 measures the signal strength | yk | by changing n variable loads 30 in K ways. _{The values Z k} of n variable loads 30 in K ways are different from each other (Z ₁ ≠ Z ₂ ... ≠ Z k). ^{Then, the memory 60 accumulates the intensity information y (l)} _meas measured by the receiver 40 when the values of the n variable loads 30 are changed in K ways (S33). The K intensity information y ^(l) _meas thus obtained can be represented by a vector as shown below.

Here, l is the index number described above. [・] ^T represents transpose.

で表すことができる。 The signal intensity y (l) k of this received signal is assumed to be s when the signal reflected from the living body is s.

Can be represented by.

Γ _Pk represents the reflectance coefficient corresponding to the combination of impedance values of the k-th variable load. The intensity information represented by the equations 1 and 2 is output to the complex propagation channel estimation unit 71 as the first signal.

Next, the positioning sensor 100 ^{estimates the complex propagation channel h (l)} when the receiver 40 receives the first signal from the ^{intensity information y (l)} _meas (S23).

More specifically, as shown in FIG. 6, first, the complex propagation channel estimation unit 71 sets the trial complex propagation channel h ^(l) _test (S41). Here, the trial complex propagation channel h ^(l) _test is set by an arbitrary value (real part, imaginary part), that is, a predetermined value shown below.

Subsequently, the complex propagation channel estimation unit 71 calculates the trial intensity information y ^(l) _test ^{from the trial complex propagation channel h (l)} _test (S42). Here, the trial intensity information y ^(l) _test is the intensity information estimated to have been received by the receiver 40 at the time of the known variable load in step S22, and is used as the second signal intensity value of the second signal described above. Applicable. The trial strength information y ^(l) _test is calculated as shown below.

Subsequently, the complex propagation channel estimation unit 71 determines the intensity information y ^(l) _meas ^{, which is the first signal intensity value of the first signal, and the trial intensity information y (l)} _test, which is the second signal intensity value of the second signal. The difference (error e) from the above is calculated (S43). Here, the difference (error e) is calculated by the following equation 5.

Subsequently, the complex propagation channel estimation unit 71, the difference e is exploring the trial complex propagation channel ^h _{(l) test} becomes smaller, the difference e becomes minimum trial complex propagation channel ^h _{(l) test} the complex propagation channel It ^{is output as h (l)} (S44).

Hereinafter, the description will be given by returning to FIG.

The positioning sensor 100 further executes the measurement process described in step S22 L times, and performs the estimation process described in step S23 each time.

Next, the positioning sensor 100 estimates the direction of the living body 90 from ^{the complex propagation channels h (1)} , ..., H ^{(l) estimated in step S23 (S24).}

[1-3. Principle of estimation processing]
Next, the principle that the complex propagation channel estimation unit 71 estimates the trial intensity information y ^(l) _test (second signal intensity) ^{from the trial complex propagation channel h (l)} _{test will be described.}

FIG. 7 is a diagram showing a circuit model of the antenna model of the first embodiment.

_Here, S A, _{S F,} gamma _P respectively indicate the S-parameter matrix of the antenna 10A and the power supply circuit 20 and the variable load 30 is expressed by the following formula 6 Formula 8.

_{Here, S FF, S FA, S} FP, S AF, S AA, S AP, S PF, S PA, S PP is a block matrix of _{S F.} In addition, S _FF , S _FA , S _FP , S _AF , _{SA A} , _SAP , S _PF , S _PA , and S _PP subscripts F, A, and P are the power supply port, antenna port, and variable load, respectively. Indicates the port.

Further, Γ _P is a diagonal matrix representing the reflection coefficient of the variable load 30.

The reflection coefficient of the # _i- th variable load 30 is expressed by the following equation 9.

Here, z _Pi and z ₀ indicate the impedance value and the reference impedance value of the variable load 30, respectively.

Since the S-parameters of the antenna 10A and the feeding circuit 20 are determined at the time of manufacturing the circuit, they can be measured in advance. Further, the impedance value of the variable load 30 can also be measured in advance. Therefore, the S-parameter matrix, elements, and impedance values of the variable load shown in Equations 6 to 8 are all known.

At this time, the signal incident from the feeding circuit 20 to the antenna 10A is a _A , the signal incident from the antenna 10A to the feeding circuit 20 is b _A, and the signal incident from the feeding circuit 20 to the variable load 30 is a _P , which is variable. The signal incident from the load 30 to the feeding circuit 20 is b _P , the signal incident from the feeding end to the feeding circuit 20 is a _P, and the signal reflected from the feeding circuit 20 to the feeding end is b _F.

At this time, the following relational expression holds.

と書ける。式１６および式１７より、

式１９を式１４に代入すると、

が得られる。式２０を整理すると、

となる。ここで、

である。式２２および式２３を用いることによって、給電端に入力した信号ａ_Ｆに対してアンテナ１０Ａに入射する信号ａ_Ａを計算することができる。 From Equations 10 to 12,

Can be written. From Equation 16 and Equation 17,

Substituting Equation 19 into Equation 14

Is obtained. If you organize Equation 20,

Will be. here,

Is. By using Equation 22 and Equation 23, it is possible to calculate the signal a _A incident on the antenna 10A for signals a _F inputted to the feeding end.

# _{Assuming that the complex directivity of the i-} th antenna 10A is Di (θ), the observed combined directivity is expressed by the following equation 24.

Thereby, the directivity when the port P is terminated by an arbitrary variable load 30 can be calculated. Here, the complex directivity of the antenna 10A is known because it can be measured in advance. Here, directivity at the time of transmission of the input signals a _F to the feed end F to the explanation, that is, since it has dealt with the case of using the antenna 10A as a transmitting antenna, the antenna is the reversibility is established, wherein The same applies to the directivity of 24 at the time of reception. That is, the above can be said in the same manner when the antenna 10A is replaced with the receiving antenna 10.

[1-4. Effect etc.]
According to the positioning sensor 100 and the method using the positioning sensor 100 of the present embodiment, the direction in which the moving object exists is estimated from the radio signal received on the receiving side without acquiring the phase information on the transmitter side. be able to. Further, since the m receiving antennas 10 are connected to the power feeding circuit 20, the degree of freedom in arranging the m receiving antennas 10 can be improved.

Further, according to the method using the positioning sensor 100 and the positioning sensor 100 of the present embodiment, the phase measurement is not required and the phase level synchronization between the transmitters and receivers is not required, so that the transmitter and the transmitter are relatively inexpensive. The receiver can be used. Further, since the phase measurement becomes unnecessary by using the non-feeding antenna, the number of receivers can be reduced.

More specifically, the positioning sensor 100 of the present embodiment includes a power feeding circuit 20 and m receiving antennas 10 connected to n variable loads 30, and observes a received signal with a single receiver 40. .. Since the characteristics of the m receiving antennas 10 are known, the phase information on the transmitter side can be obtained by acquiring the receiving intensity (RSSI: Received Signal Strength Indicator) at the receiver by shaking the load condition of the receiving antenna 10. The complex propagation channel can be estimated without acquisition. In other words, by changing the variable load (impedance value) of the receiving antenna, the reflectance changes and the directivity of the receiving antenna changes in a pseudo manner. Therefore, the directivity of the receiving antenna can be changed pseudo-multiple times (more than the unknown number of the complex propagation channel), and the simultaneous equations can be created from the receiving intensity of the received signal received by the receiver at that time. Then, the complex propagation channel can be estimated by solving the simultaneous equations by the steepest descent method.

In this way, the complex propagation channel that reaches the receiving antenna connected to the receiver and the non-feeding antenna from the transmitting antenna outside the positioning sensor 100 is estimated only from the receiving strength without preparing a plurality of receivers. can do. Further, since the direction can be estimated only from the reception intensity and the observation of the phase information is unnecessary, the positioning sensor 100 of the present embodiment has a simple hardware configuration that does not acquire the phase information on the transmitter side, that is, inexpensive. It will be possible to use existing transmitters and receivers.

(Embodiment 2)
The signal received by the positioning sensor 100 in the first embodiment includes a direct wave, a reflected wave derived from a fixed object, and the like, in addition to the reflected wave in which the signal (transmitted wave) transmitted from the transmitter 80 is reflected by the living body 90. , Reflected waves that do not pass through the living body 90 are also included. In the second embodiment, a method of estimating the direction of the living body 90 in consideration of the fact that the reflected wave that does not pass through the living body 90 is also included will be described. In the following, the same points as those in the first embodiment will be omitted, and different points will be mainly described.

[2-1. Positioning sensor configuration]
The positioning sensor (not shown) according to the present embodiment has a different configuration of the direction estimation unit 740 from the positioning sensor 100 in the first embodiment.

FIG. 8 is a diagram showing an example of the configuration of the direction estimation unit according to the second embodiment.

The direction estimation unit 740 estimates the arrival direction of the first signal from the complex propagation channel estimated by the complex propagation channel estimation unit 71. In the present embodiment, as shown in FIG. 8, the direction estimation unit 740 includes an instantaneous correlation matrix calculation unit 741, a storage unit 742, a third correlation matrix calculation unit 743, and an arrival angle estimation unit 744.

The instantaneous correlation matrix calculation unit 741 calculates the first correlation matrix from the first complex propagation channel estimated by the complex propagation channel estimation unit 71, and stores it in the storage unit 742. Further, the instantaneous correlation matrix calculation unit 741 calculates the second correlation matrix from the second complex propagation channel estimated by the complex propagation channel estimation unit 71.

In the present embodiment, the complex propagation channel estimation unit 71 uses the first complex propagation channel as the complex propagation channel when the time variation of the first signal strength of the first signal received by the receiver 40 is equal to or less than a predetermined value. presume. Further, the complex propagation channel estimation unit 71 estimates the second complex propagation channel as the complex propagation channel when the time variation of the first signal strength of the first signal received by the receiver 40 is larger than a predetermined value. Here, the first signal in which the time variation of the first signal strength is equal to or less than a predetermined value does not include the reflected signal transmitted from the transmitting antenna 81 and reflected by the living body 90. This is because when the time variation of the first signal strength is equal to or less than a predetermined value, the receiver 40 receives the first signal in an unmanned state (a state in which the living body 90 does not exist). On the other hand, the first signal in which the time variation of the first signal strength is larger than a predetermined value includes a reflected signal transmitted from the transmitting antenna 81 and reflected by the living body 90. This is because when the time variation of the first signal strength is larger than a predetermined value, it corresponds to the receiver 40 receiving the first signal in a manned state (a state in which the living body 90 exists).

The storage unit 742 is realized by a storage device such as an HDD (Hard Disk Drive) or a non-volatile memory, and stores the first correlation matrix calculated by the instantaneous correlation matrix calculation unit 741.

The third correlation matrix calculation unit 743 obtains a difference matrix obtained by subtracting the first correlation matrix stored in the storage unit 742 from the second correlation matrix calculated by the instantaneous correlation matrix calculation unit 741 as the third correlation matrix. Calculate as.

The arrival angle estimation unit 744 estimates the arrival angle of the first signal from the third correlation matrix calculated by the third correlation matrix calculation unit 743.

[2-2. Operation of measurement sensor]
The operation of the direction estimation process of the positioning sensor 100 according to the second embodiment configured as described above will be described. FIG. 9 is a flowchart showing the direction estimation process of the direction estimation unit according to the second embodiment. FIG. 10 is a diagram showing a flow of the direction estimation process of the direction estimation unit in the second embodiment.

First, the complex propagation channel estimation unit 71 estimates the first complex propagation channel in a state known to be unmanned (unmanned state) by the complex propagation channel estimation unit 71 before estimating the direction of the living body 90. The direction estimation unit 740 calculates the first correlation matrix from the first complex propagation channel estimated by the complex propagation channel estimation unit 71, and stores it in the storage unit 742 (S51).

_{More specifically, the instantaneous correlation matrix calculation unit 741 calculates the instantaneous correlation matrix R 01} from the first complex propagation channel h in the unmanned state estimated by the complex propagation channel estimation unit 71 as shown in the following equation 25. do. In Equation 25, {・} ^H represents the complex conjugate transpose.

Then, as shown in the equation 26, the instantaneous correlation matrix calculation unit 741 calculates the instantaneous correlation matrix represented by the equation 25 L times and averages the matrix. This is defined as the first correlation matrix R _1.

Next, the complex propagation channel estimation unit 71 estimates the second complex propagation channel in a state known to be manned (manned state). The direction estimation unit 740 calculates the second correlation matrix from the second complex propagation channel estimated by the complex propagation channel estimation unit 71 (S52).

_{More specifically, the instantaneous correlation matrix calculation unit 741 similarly obtains the instantaneous correlation matrix R 02} from the second complex propagation channel h in the manned state estimated by the complex propagation channel estimation unit 71 as shown in the following equation 27. Calculate to.

Then, as shown in Equation 27, the instantaneous correlation matrix calculation unit 741 calculates the matrix obtained by calculating and averaging the instantaneous correlation matrix represented by Equation 28 L times. This is defined as the second correlation matrix R _2.

Next, the direction estimation unit 740 calculates the difference matrix obtained by subtracting the first correlation matrix stored in the storage unit 742 from the second correlation matrix calculated in step S52 as the third correlation matrix (S53).

More specifically, the third correlation matrix calculation unit 743 _{subtracts the second correlation matrix R 2} shown in the equation 28 from _{the first correlation matrix R 1} shown in the equation 26, and the third correlation matrix R ₃ (R). ₃ = R _2- R ₁ ) is obtained.

Next, the direction estimation unit 740 estimates the arrival direction of the first signal by estimating the arrival angle of the first signal from the calculated third correlation matrix (S54).

Here, as described above, the first correlation matrix R ₁ is calculated from the first complex propagation channel estimated when unmanned, and is a complex propagation channel other than the living body 90 such as a direct wave or a reflected wave from a wall. Corresponds to the ingredients. On the other hand, the second correlation matrix R ₂ is calculated from the complex propagation channel observed when manned, and the component passing through the living body 90 and the fixed component not passing through the living body 90 are added together.

Therefore, by the second correlation matrix R ₂ subtracts the first correlation matrix R _1, only components ideally passed through the living body 90 remains. That is, the arrival angle estimation unit 744, by using a third correlation matrix R _3, can also estimate the direction of arrival angle or biological 90 of the first signal in a multi-path environment, such as indoors.

[2-3. Effect etc.]
According to the positioning sensor and the method using the positioning sensor of the present embodiment, even in a multiple wave environment such as indoors, a moving body exists from the wireless signal received on the receiving side without acquiring the phase information on the transmitting side. It is possible to estimate the direction of the wave.

(Embodiment 3)
In the second embodiment, a method of estimating the direction of the living body 90 by removing complex propagation channel components other than the living body 90 such as a direct wave and a reflected wave from a wall has been described, but the present invention is not limited to this. In the third embodiment, a method of estimating the direction of the living body 90 by removing the complex propagation channel component other than the living body 90 by a method different from that of the second embodiment will be described. In the following, the same points as those in the first embodiment will be omitted, and different points will be mainly described.

[3-1. Positioning sensor configuration]
The positioning sensor (not shown) according to the present embodiment has a different configuration of the direction estimation unit 840 from the positioning sensor 100 in the first embodiment.

FIG. 11 is a diagram showing an example of the configuration of the direction estimation unit according to the third embodiment.

The direction estimation unit 840 estimates the arrival direction of the first signal from the complex propagation channel estimated by the complex propagation channel estimation unit 71. In the present embodiment, as shown in FIG. 11, the direction estimation unit 840 includes a storage unit 845, a phase angle calculation unit 846, a correlation matrix calculation unit 847, and an arrival angle estimation unit 848.

The storage unit 845 is realized by a storage device such as an HDD (Hard Disk Drive) or a non-volatile memory, and stores the first complex propagation channel estimated by the complex propagation channel estimation unit 71. In the present embodiment, the storage unit 845 stores the first complex propagation channel estimated as the complex propagation channel at a predetermined time by the complex propagation channel estimation unit 71.

The phase angle calculation unit 846 compares the phase difference between the first complex propagation channel stored in the storage unit 845 and the second complex propagation channel estimated by the complex propagation channel estimation unit 71. Here, the second complex propagation channel is estimated by the complex propagation channel estimation unit 71 as a complex propagation channel at a time after a predetermined time.

Then, the phase angle calculation unit 846 searches for the phase rotation (phase angle) at which the average of the phase differences is minimized, and the first complex propagation is performed from the second complex propagation channel to which the searched phase rotation (phase angle) is given. The third complex propagation channel, which is the difference obtained by subtracting the channels, is calculated.

The correlation matrix calculation unit 847 calculates the correlation matrix from the third complex propagation channel calculated by the phase angle calculation unit 846.

The arrival angle estimation unit 848 estimates the arrival angle of the first signal from the correlation matrix calculated by the correlation matrix calculation unit 847.

[3-2. Positioning sensor operation]
The operation of the direction estimation process of the positioning sensor 100 according to the third embodiment configured as described above will be described. FIG. 12 is a flowchart showing the direction estimation process of the direction estimation unit according to the third embodiment. FIG. 13 is a diagram showing a flow of the direction estimation process of the direction estimation unit in the third embodiment.

First, the complex propagation channel estimation unit 71 stores the complex propagation channel estimated at a certain time point (predetermined time) in the storage unit 845 as ^{the first complex propagation channel h (1).} Here, the complex propagation channel estimated after that (time after a predetermined time) is referred to as the second complex propagation channel h ^(l) . Here, l is a measurement number corresponding to the observation time (estimated time).

Next, the direction estimation unit 740 compares the phase difference between the first complex propagation channel stored in the storage unit 845 and the second complex propagation channel estimated at a time after a predetermined time (S61). The phase rotation (phase angle) at which the average of the phase differences is minimized is searched for (S62).

More specifically, in a general multi-wave environment, it is considered that the direct wave and the reflected wave via the wall have much higher signal strength than the signal passing through the living body. Therefore, it can be considered that the phases of all the complex propagation channel elements do not fluctuate significantly. On the other hand, it is considered that the first complex propagation channel and the second complex propagation channel estimated by the positioning sensor 100 in the third embodiment are multiplied by a random phase. This is because the positioning sensor 100 estimates the first complex propagation channel and the second complex propagation channel only from the intensity information. The absolute channel phase cannot be estimated.

Therefore, assuming that there is no change in the fixed components that are the main components of ^{the first complex propagation channel h (1)} and the second complex propagation channel h ^(l) , the phase angle calculation unit 846 uses the following equation 29. The correction phase θ _l that minimizes the indicated Δp ^(l) may be searched for and determined.

Next, the direction estimation unit 740 calculates the third complex propagation channel obtained by subtracting the first complex propagation channel from the second complex propagation channel given the phase rotation (phase angle) searched in step S62. (S63).

More specifically, the phase angle calculation unit 846 calculates the difference channel as shown in the following equation 30 by using the _{correction phase θ l searched by the equation 29.} This difference channel is referred to as a third complex propagation channel Δh ^(l).

Next, the direction estimation unit 740 calculates the correlation matrix from the third complex propagation channel calculated in step S63 (S64).

More specifically, the correlation matrix calculation unit 847 calculates the correlation matrix R from ^{the third complex propagation channel Δh (l) shown in Equation 30 as in Equation 31 below.}

Here, as described above, since the difference channel (third complex propagation channel) is used in the process of the subtraction process using the equation 30, the correlation matrix R shown in the equation 31 always has a fixed component erased and is a living body. Only the 90-derived component remains.

Therefore, if the correlation matrix R shown in Equation 31 is known, various direction estimation processes can be applied. According to such a direction estimation method, it is not necessary to separately estimate the first complex propagation channel when unattended, and the direction of the living body 90 can be estimated even when the propagation environment changes such as the fixture moving.

[3-3. Effect etc.]
According to the positioning sensor and the method using the positioning sensor of the present embodiment, even if the propagation environment changes in a multiple wave environment such as indoors, the radio received on the receiving side without acquiring the phase information on the transmitter side. From the signal, it is possible to estimate the direction in which the moving object exists.

(Embodiment 4)
In the first to third embodiments, the complex propagation channel is estimated from the first signal strength of the first signal received by the receiver 40, and the direction of the living body 90 is estimated, but the present invention is not limited to this. The complex propagation channel may be estimated from the signal strength optimized for the first signal strength of the first signal received by the receiver 40, and the direction of the living body 90 may be estimated. Hereinafter, as the fourth embodiment, the same points as those in the first embodiment will be omitted, and different points will be mainly described.

[4-1. Positioning sensor configuration]
The positioning sensor (not shown) according to the present embodiment has a different configuration of the memory 600, the complex propagation channel estimation unit 45, and the direction estimation unit 940 from the positioning sensor 100 in the first embodiment and the like. The controller 50 in the positioning sensor 100 controls the impedance value of the variable load 30 as described above. Hereinafter, the controller 50 will be described as controlling the combination of the impedance values of the variable loads 30 of the m receiving antennas 10 in K ways (K is an integer of 2 or more).

FIG. 14 is a diagram showing an example of the configuration of the memory and the complex propagation channel estimation unit in the fourth embodiment.

The memory 600 accumulates the first signal strength of the first signal received by the receiver 40 in each of the K combinations of impedance values of the variable load 30 L times (L is an integer of 2 or more), and each of the K combinations. The first average signal strength, which is the average value of the first signal strength of L times in the above, is calculated. The memory 600 calculates and stores K × L first difference signal strengths obtained by subtracting the first average signal strength from the accumulated first signal strength, which is the first signal strength of L times in each of the K combinations. do.

In the present embodiment, as shown in FIG. 14, the memory 600 records the strength information (first signal strength) of the first signal for each combination of the impedance values (load in the figure) of the variable load 30 as shown in K. , And observe this L times. That is, K × L strength information of the first signal (first signal strength) is recorded.

Here, paying attention to the first combination of loads, the positioning sensor according to the present embodiment makes L observations, so that the memory 600 has the first signal # 1-1 to the first signal # 1. A total of L intensity information (first signal intensity # 1-1 to first signal intensity # 1-L) of −L is accumulated. Then, the memory 600 calculates the average signal strength # 1 which is the average value of the L strength information (first signal strength), and the accumulated first signal strength # 1-1 to the first signal strength # 1-L. Subtract the average signal strength # 1 from. As a result, the first difference signal strength # 1-1 to the first difference signal strength # 1-L are obtained.

The same process is performed for all K load combinations.

As described above, the memory 600 stores the first signal strengths of the K × L first signals received by the receiver 40, and in addition, the K × L first signals whose first signal strengths are optimized. 1 Accumulate the difference signal strength.

As shown in FIG. 14, the complex propagation channel estimation unit 710 includes a difference signal calculation unit 720 and a comparison calculation unit 730.

The difference signal calculation unit 720 sets L trial difference complex propagation channels having predetermined values, and calculates K second difference signal intensities in each of the set L trial difference complex propagation channels. do.

The comparison calculation unit 730 cooperates with the difference signal calculation unit 720 to minimize the difference between the K-like first difference signal strength stored in the memory 600 and the calculated second difference signal strength. Search for channel values. Then, the comparison calculation unit 730 estimates the L trial difference complex propagation channels having the searched values as the L complex difference propagation channels when the receiver 40 receives the first signal.

In the present embodiment, the difference signal calculation unit 720 first sets the trial difference complex propagation channel (# 1) corresponding to the first observation to an arbitrary value. Assuming that this trial difference complex propagation channel (# 1) is correct, the trial difference signal strength # 1-1 to the trial difference signal strength # K-1 (total of K) corresponding to the load combination is calculated by Equation 2. calculate. Here, the trial difference signal strength is strength information estimated to have been received by the receiver 40 when the corresponding load combination is used, and corresponds to the second difference signal strength described above.

Subsequently, the comparison calculation unit 730 subtracts the K first difference signal strengths calculated by the memory 600 by the K trial difference signal strengths (second difference signal strengths) calculated by the difference signal calculation unit 720. And compare. Here, the subtraction is performed by the difference signal strengths having the same load combination. As a result, K difference values can be obtained. The comparison calculation unit 730 evaluates using an evaluation function such as adding up the absolute values of the obtained K difference values, and feeds back the evaluation result to the difference signal calculation unit 720.

Then, the difference signal calculation unit 720 resets the trial difference complex propagation channel (# 1) based on the feedback result, and calculates K trial difference signal strengths (second difference signal strength) from this. Then, the comparison calculation unit 730 performs the above-mentioned comparison calculation again.

The complex propagation channel estimation unit 710 estimates the complex difference propagation channel by repeating such a procedure many times so as to minimize the comparison calculation result. Further, for the estimation of the complex difference propagation channel, for example, the steepest descent method can be used. The complex propagation channel estimation unit 710 estimates L time-series complex difference propagation channels by repeating such processing L times.

FIG. 15 is a diagram showing an example of the configuration of the direction estimation unit according to the fourth embodiment.

The direction estimation unit 940 includes a correlation matrix calculation unit 941 and an arrival angle estimation unit 942, and estimates the arrival direction of the first signal from the complex difference propagation channel estimated by the complex propagation channel estimation unit 710. The correlation matrix calculation unit 941 calculates the correlation matrix from the L complex difference propagation channels estimated by the complex propagation channel estimation unit 710. The arrival angle estimation unit 942 estimates the arrival direction of the first signal by estimating the arrival angle of the first signal from the correlation matrix calculated by the correlation matrix calculation unit 941.

In the present embodiment, the correlation matrix calculation unit 941 converts each of the complex difference propagation channels estimated by the complex propagation channel estimation unit 710 into an instantaneous correlation matrix. The correlation matrix calculation unit 941 calculates the correlation matrix by averaging the converted total L instantaneous correlation matrices for each element. The arrival angle estimation unit 942 estimates the arrival angle of the first signal from the correlation matrix calculated by the correlation matrix calculation unit 941. The arrival angle of the first signal corresponds to the direction of the living body 90 to be detected as described above.

[4-2. Positioning sensor operation]
The operations of the memory 600, the complex propagation channel estimation unit 710, and the direction estimation unit 940 configured as described above will be described.

FIG. 16 is a flowchart showing a memory estimation process according to the fourth embodiment.

First, the memory 600 accumulates the first signal strength of the first signal received by the receiver 40 in each of the K combinations of impedance values of the variable load 30 L times (L is an integer of 2 or more) (S71).

Next, the memory 600 calculates the first average signal strength, which is the average value of the first signal strength of the L times in each of the K combinations (S72).

Next, the memory 600 calculates K × L first difference signal strengths obtained by subtracting the first average signal strength from the accumulated first signal strength, which is the first signal strength of L times in each of the K combinations. And accumulate (S73).

FIG. 17 is a flowchart showing an estimation process of the complex propagation channel estimation unit according to the fourth embodiment.

First, the complex propagation channel estimation unit 710 sets L trial difference complex propagation channels each having a predetermined value (S81).

Next, the complex propagation channel estimation unit 710 calculates the second difference signal strength in K ways in each of the set L trial difference complex propagation channels (S82).

Next, the complex propagation channel estimation unit 710 searches for the value of the trial difference complex propagation channel that minimizes the difference between the K-like first difference signal strength stored in the memory 600 and the calculated second difference signal strength. (S83).

Then, the complex propagation channel estimation unit 710 estimates L trial difference complex propagation channels having the searched values as L complex difference propagation channels when the receiver 40 receives the first signal (S84). ..

FIG. 18 is a flowchart showing the estimation process of the direction estimation unit according to the fourth embodiment.

First, the direction estimation unit 940 calculates the correlation matrix from the L complex difference propagation channels estimated by the complex propagation channel estimation unit 710 (S91).

Next, the direction estimation unit 940 estimates the arrival direction of the first signal by estimating the arrival degree of the first signal from the correlation matrix calculated in step S91 (S92).

[4-3. Effect etc.]
As described above, according to the positioning sensor and the method using the positioning sensor of the present embodiment, even in a multiple wave environment such as indoors, a moving object is used from a wireless signal received on the receiving side without acquiring phase information on the transmitting side. It is possible to estimate the direction in which the is present.

More specifically, the positioning sensor of the present embodiment includes a feeding circuit and m receiving antennas connected to n variable loads, and observes the received signal with a single receiver. Since the characteristics of m receiving antennas are known, the phase information on the transmitter side can be obtained by changing the load conditions of the receiving antennas according to K and acquiring the receiving intensity (RSSI: Received Signal Strength Indicator) at the receiver. The complex difference propagation channel can be estimated by the steepest descent method or the like without obtaining. That is, by changing the variable load (impedance value) of the receiving antenna, the reflectance changes, and the directivity of the receiving antenna changes in a pseudo manner. Therefore, the directivity of the receiving antenna can be changed pseudo-multiple times (more than the unknown number of the complex propagation channel), and the simultaneous equations can be created from the receiving intensity of the received signal received by the receiver at that time. Then, the complex difference propagation channel can be estimated by solving the simultaneous equations by the steepest descent method.

In addition, since the evaluation by the experiment was performed in order to confirm the effect which concerns on Embodiment 4, it will be described below.

FIG. 19 is a diagram showing the concept of an experiment using the direction estimation method in the fourth embodiment.

In the antenna configuration in the experimental system shown in FIG. 19, a 1.47 GHz band 1-element square patch antenna was used as the transmitting antenna, and a 3-element patch array antenna using a 1-element square patch antenna and a 2-element non-feeding antenna was used as the receiving antenna. The height of the transmitting antenna and the receiving antenna was set to 1.05 m, which was adjusted to the height of the abdomen of the subject (living body). The distance between the transmitting antenna and the receiving antenna was set to 3.5 m, and the distance between the receiving antenna and the subject was set to 1.5 m. In addition, the subject was placed upright and stationary at a position of −20 ° with respect to the front of the antenna. The observation time was 12.8 seconds, the number of combinations of variable load values was K = 16, and the number of observations was L = 128.

FIG. 20 is a diagram showing the experimental results using the estimation method in the fourth embodiment. In FIG. 20, the MUSIC (MUSIC Signal Classification) method is used for the direction estimation process.

In FIG. 20, the horizontal axis is the angle with respect to the front of the antenna, and the vertical axis is the intensity of the MUSIC spectrum. Further, the maximum value of the MUSIC spectrum corresponds to the arrival direction. The solid line A shows the experimental result using the estimation method according to the fourth embodiment. Further, as a comparative example, the dotted line B shows the experimental result using the conventional estimation method. Here, the conventional method is a method of acquiring phase information on the transmitter side. The experimental results shown by the dotted line B are obtained by observing all complex propagation channels using a 3-element square patch array antenna, excluding fixed reflection components from the 12.8-second observation data, and then estimating the direction. It is a thing.

From the results shown in FIG. 20, it can be seen that the living body direction can be estimated with high accuracy by the estimation method according to the fourth embodiment. The angular error was 0.7 °.

In this way, it was confirmed that the biological direction can be estimated with an accuracy comparable to that of the conventional method.

The positioning sensor and the method using the positioning sensor according to one aspect of the present invention have been described above based on the embodiments, but the present invention is not limited to these embodiments. As long as the gist of the present invention is not deviated, various modifications that can be conceived by those skilled in the art are applied to the present embodiment, or a form constructed by combining components in different embodiments is also included in the scope of the present invention.

For example, in the first to fourth embodiments, an example of estimating the direction of the living body 90 has been described, but the present invention is not limited to the living body 90. It can also be applied to various moving objects (machines, etc.) that give a Doppler effect to reflected waves by their activity when a high-frequency signal is irradiated.

Further, for example, using sensors having two or more positioning sensors in different locations in the first to fourth embodiments, the position of the moving body is based on the arrival direction of the first signal estimated by each of the two or more positioning sensors. May be estimated. More specifically, it is a method of estimating the position of a sensor having two or more positioning sensors in different places according to the first to fourth embodiments, and the first signal is transmitted from a transmitting antenna and reflected by a moving body. The position of the moving object may be estimated by using, for example, trigonometry, based on the arrival direction of the first signal including the reflected signal and estimated from each of the two or more positioning sensors. This is because the position where the arrival directions of the first signals estimated from each of the two or more positioning sensors intersect can be estimated as the position of the moving object.

In the positioning sensor, when the number of n variable loads 30 is the same as the number of m receiving antennas 10, they may be arranged in the vicinity of the array antennas as shown in FIG. Further, when the number of the n variable loads 30 is larger than the number of the m receiving antennas 10, they may be arranged on the branch wiring as shown in FIG. 22. FIG. 21 is a diagram showing an example of arrangement of a feeding circuit, a variable load, and a receiving antenna in the positioning sensor. FIG. 22 is a diagram showing another example of the arrangement of the feeding circuit, the variable load, and the receiving antenna in the positioning sensor.

Further, the present invention can be realized not only as a positioning sensor provided with such characteristic components, but also as an estimation method in which the characteristic components included in the positioning sensor are steps. can. It can also be realized as a computer program that causes a computer to execute each characteristic step included in such a method. Needless to say, such a computer program can be distributed via a non-temporary recording medium such as a CD-ROM that can be read by a computer or a communication network such as the Internet.

The present invention can be used in a direction estimation method, a position estimation method, and a direction estimation device for estimating the direction and position of a moving body using a radio signal, and in particular, a measuring instrument for measuring the direction and position of a moving body including a living body and a machine. A direction estimation method installed in home appliances that control according to the direction and position of a moving object, a monitoring device that detects the intrusion of a moving object, and a direction estimation method using a direction estimation method, a position estimation method, and a scattered cross-sectional area. Can be used for.

10 Receiving antenna 10A Antenna 20 Feeding circuit 30 Variable load 40 Receiver 50 Controller 60, 600 Memory 70 Processor 71 Complex propagation channel estimation unit 72 Signal calculation unit 73, 730 Comparison calculation unit 74, 740, 840, 940 Direction estimation unit 80 Transmission Machine 81 Transmitting antenna 90 Living body 100 Positioning sensor 720 Difference signal calculation unit 741 Instantaneous correlation matrix calculation unit 742, 845 Storage unit 743 Third correlation matrix calculation unit 744, 942 Arrival angle estimation unit 846 Phase angle calculation unit 847, 941 Correlation matrix calculation Part 848 Arrival angle estimation part

Claims (3)

It ’s a positioning sensor,
With m receiving antennas (m is an integer of 1 or more),
The power supply circuit connected to the receiving antenna and
N variable loads (n is an integer of 1 or more) connected to the power supply circuit and
A receiver that receives a first signal, which is a signal received by the receiving antenna, a transmission signal transmitted from the transmitter to a predetermined range in which a moving object may exist from the positioning sensor via the power feeding circuit.
A controller that sets the impedance value of the variable load, and
When the impedance value of the variable load is set by the controller, a memory that stores a first signal strength value indicating the strength of the first signal corresponding to the set impedance value of the variable load, and a memory.
A plurality of candidates are set for a complex propagation channel showing signal propagation characteristics between the transmitter and the receiver, and a plurality of candidates when the receiver receives a second signal transmitted from the transmitter. The second signal strength value is calculated, the second signal strength value indicates the strength of the second signal, and the plurality of second signal strength values correspond to the plurality of candidates, respectively, and are combined with the first signal strength value. The complex propagation channel is estimated by selecting a candidate corresponding to the minimum difference among the differences from each of the plurality of second signal strength values, and the first one with respect to the positioning sensor based on the complex propagation channel. It is equipped with a processor that estimates the direction of arrival of the signal.
Positioning sensor. The positioning sensors according to claim 1, which are arranged at different positions from each other, are provided.
The position of the moving object is estimated based on the arrival direction of each of the first signals in each of the plurality of positioning sensors.
sensor. It is a method of estimating the direction of arrival of a signal in a positioning sensor.
The positioning sensor has m (m is an integer of 1 or more) receiving antennas, a feeding circuit connected to the receiving antenna, and n variable (n is an integer of 1 or more) connected to the feeding circuit. Equipped with a load, a receiver, a controller,
The impedance value of the variable load is set by the controller, and the impedance value is set.
The receiver receives a first signal, which is a signal received by the receiving antenna, from the positioning sensor to a predetermined range in which a moving object may exist, via the feeding circuit.
When the impedance value of the variable load is set by the controller, the first signal strength value indicating the strength of the first signal corresponding to the set variable load value is stored.
A plurality of candidates are set for the complex propagation channel showing the signal propagation characteristics between the transmitter and the receiver.
A plurality of second signal strength values when the receiver receives the second signal transmitted from the transmitter are calculated, and the second signal strength value indicates the strength of the second signal, and the plurality of second signals are shown. 2 signal strength corresponds to the above multiple candidates,
The complex propagation channel is estimated by selecting a candidate corresponding to the minimum difference among the differences between the first signal strength value and each of the plurality of second signal strength values.
The direction of arrival of the first signal with respect to the positioning sensor is estimated based on the complex propagation channel.
Method.

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