JP2016191584A - Moving body detecting device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a technique capable of improving determination precision of presence or absence of a moving body.SOLUTION: A generation part 17 sets distance from a moving body detecting device 1 to be a variable x, based on a synthetic wave of a transmission wave VT, and reflected waves VR by a plurality of reflection objects 300, and generates a determination function as a complex signal in that amplitude and a phase change according to a value of the variable x. The determination function is a synthetic signal of a plurality of individual complex signals corresponding to the plurality of reflection objects 300 each. Each of the plurality of individual complex signals changes according to differential distance between the variable x, and distance to the reflection objects 300 corresponding to the individual complex signals. A moving body determination part 111 obtains a differential vector between a second complex planar vector for indicating a temporal change of a first complex planar vector, and a third complex planar vector that is included in the temporal change, and indicates an influence of movement of an object not to be detected, and determines presence or absence of the moving body based on the differential vector.SELECTED DRAWING: Figure 2

Description

  The present invention relates to moving object detection.

  Various techniques have been proposed for moving object detection for determining the presence or absence of moving objects such as people. For example, Patent Document 1 describes a technique for determining the presence or absence of a person using a Doppler sensor.

  Patent Document 2 and Non-Patent Document 1 disclose distance measuring techniques for measuring the distance to an object.

Japanese Patent No. 5252639 JP 2007-93576 A

Ishikawa, et al., “Distance measurement method using phase difference of distance spectrum in standing wave radar”, IEICE Transactions B, IEICE, 2010, Vol. J93-B, no. 7, p. 1017-1024

  When determining the presence or absence of a moving object, it is desired to improve the determination accuracy.

  Therefore, the present invention has been made in view of the above-described problems, and an object thereof is to provide a technique capable of improving the determination accuracy of the presence or absence of moving objects.

  In order to solve the above-described problem, an aspect of the moving object detection device according to the present invention is a moving object detection device that determines the presence or absence of a moving object to be detected, the signal generator generating a transmission wave, and transmitting the transmission wave Based on the combined wave of the antenna to be transmitted, the transmitted wave, and the reflected wave of the plurality of reflecting objects including the moving object, which is received by the antenna, the distance from the moving object detection device as a variable, A generation unit that generates a determination function that is a complex signal whose amplitude and phase change according to the value, and a time change of the first complex plane vector that represents the value of the determination function when the variable is the target distance. A determination unit configured to determine the presence or absence of the moving object, wherein the determination function is a composite signal of a plurality of individual complex signals corresponding to the plurality of reflectors, respectively. Each with the variable It changes according to a difference distance between the distance to the reflector according to the individual complex signal, and the determination unit includes a second complex plane vector representing a time change of the first complex plane vector, and the time. A difference vector from the third complex plane vector representing the influence of the motion of the non-detected object included in the change is obtained, and the presence or absence of the moving object is determined based on the difference vector.

  Further, in one aspect of the moving object detection device according to the present invention, the amplitude of the individual complex signal is between the variable and the distance if the distance to the reflector according to the individual complex signal is constant. The absolute value of the difference distance tends to decrease, and the determination unit represents the value of the determination function when the variable is the target distance for each of a plurality of target distances within the determination range. The time change of the first complex plane vector is obtained, and the determination unit corresponds to each of the plurality of target distances based on the time change of the first complex plane vector obtained for each of the plurality of target distances. The difference vector is obtained, and the presence or absence of the moving object within the determination range is determined based on the obtained difference vector.

  Moreover, in one aspect of the moving object detection device according to the present invention, the determination unit changes the time of a fourth complex plane vector representing the value of the determination function when the variable is a distance to the non-detection target. And the time change of the first complex plane vector, and the third complex plane vector is obtained based on the obtained time changes of the first and fourth complex plane vectors.

  Moreover, in one aspect of the moving object detection device according to the present invention, the determination unit obtains a time change of the real axis coordinate of the first complex plane vector and a time change of the imaginary axis coordinate of the first complex plane vector. Thus, the time change of the first complex plane vector is obtained, and the determination unit uses the time change of the real axis coordinate of the first complex plane vector as the real axis coordinate of the second complex plane vector, and The time change of the imaginary axis coordinate of the plane vector is defined as the imaginary axis coordinate of the second complex plane vector, and the difference between the real axis coordinate of the second complex plane vector and the real axis coordinate of the third complex plane vector; The difference vector is obtained by obtaining the difference between the imaginary axis coordinate of the two complex plane vector and the imaginary axis coordinate of the third complex plane vector.

  Further, in one aspect of the moving object detection device according to the present invention, the determination unit extracts and extracts a frequency component corresponding to the movement of the moving object from each of the real axis coordinate and the imaginary axis coordinate of the difference vector. The presence or absence of the moving object is determined based on the frequency component.

  Further, in one aspect of the moving object detection device according to the present invention, the determination unit determines the presence or absence of the moving object in each of the real axis coordinate and the imaginary axis coordinate of the first complex plane vector. Only the frequency component corresponding to the movement of is used.

  According to one aspect of the present invention, the accuracy of determining the presence or absence of moving objects is improved.

It is a figure which shows the mode in the garage where a moving body detection apparatus is introduced. It is a figure which shows the structure of a moving body detection apparatus. It is a figure which shows a sink function. It is a figure which shows multiple types of complex plane vectors on a complex plane. It is a flowchart which shows an example of operation | movement of a moving body determination part. It is a flowchart which shows an example of operation | movement of a moving body determination part. It is a flowchart which shows an example of operation | movement of a moving body determination part. It is a flowchart which shows an example of operation | movement of a moving body determination part. It is a figure which shows an example of the relationship between (DELTA) Z (xz, t) and (DELTA) Z (xdoor, t). It is a figure which shows an example of (DELTA) Zn (xz, t). It is a figure which shows an example of the relationship between L (xz, t) and a unit vector. It is a figure which shows an example of (DELTA) W (xz, t) which shows the influence of the motion of a door. It is a flowchart which shows an example of operation | movement of a moving body determination part.

<Introduction example of motion detection device>
FIG. 1 is a diagram showing an example of a system in which a moving object detection device 1 according to the present embodiment is introduced. The moving body detection device 1 according to the present embodiment detects, for example, the presence or absence of a person who is a moving body. As shown in FIG. 1, the moving object detection device 1 is introduced into, for example, a movable garage (reception berth) 500 included in a mechanical parking facility. The moving body detection device 1 determines the presence or absence of a person in the garage 500. In FIG. 1, the inside of the garage 500 when viewed from the side is shown.

  A metal door (shutter) 501 is provided at the doorway of the garage 500. When the car 600 enters the garage 500, the door 501 is opened by an operation on the operation panel. Then, after the car 600 enters the garage 500 and stops, the door 501 is closed. After the door 501 is closed, if the moving object detection device 1 determines that there is no person in the garage 500, the garage 500 moves. In the present embodiment, the moving object detection device 1 always performs moving object detection. The management device that manages the mechanical parking facility refers to the moving object detection result of the moving object detection device 1 for several seconds after the door 501 is closed. Then, when no moving object is detected by the moving object detection device 1 for several seconds, the management apparatus controls the garage 500 and moves.

  The moving body detection apparatus 1 is arrange | positioned at the back | inner side of the garage 500, for example. The moving body detection apparatus 1 outputs the transmission wave VT and receives the reflected wave VR at the reflector for the transmission wave VT. And the moving body detection apparatus 1 determines the presence or absence of the person in the garage 500 based on the transmission wave VT and the reflected wave VR.

<Configuration of moving object detection device>
FIG. 2 is a diagram illustrating a configuration of the moving object detection apparatus 1. As shown in FIG. 2, the moving object detection apparatus 1 includes an antenna 10, a control unit 11, a signal generator 12, detectors 13 and 14, and an A / D converter 15. These components are accommodated in one case 16, for example. The moving body detection device 1 transmits a transmission wave (traveling wave) VT generated by the signal generator 12 from the antenna 10 and receives the reflected waves VR of the plurality of reflectors 300 for the transmission wave VT by the antenna 10. . Then, the moving body detection device 1 detects the human wave in the garage 500 based on a standing wave (combined wave) generated by combining the transmission wave VT and the plurality of reflected waves VR received by the antenna 10. Determine presence or absence. The plurality of reflectors 300 include a person in the garage 500 and a door 501 of the garage 500.

  The signal generator 12 can change the frequency of the transmission wave VT to be output in accordance with an instruction from the control unit 11. The detectors 13 and 14 detect standing wave power at different positions, and output a detection signal indicating the detected power. The A / D converter 15 converts the detection signals output from the detectors 13 and 14 from an analog format to a digital format and outputs the result.

  The control unit 11 is, for example, a microcomputer configured with a CPU (Central Processing Unit) or the like. The control unit 11 is a kind of digital circuit, and determines the presence or absence of a person based on a digital detection signal output from the A / D converter 15. The control unit 11 includes a function generation unit 110, a moving body determination unit 111, and a frequency control unit 112 as functional blocks. Based on the detection signal output from the A / D converter 15, the function generation unit 110 generates a determination function to be described later. The moving body determination unit 111 determines the presence or absence of a person in the garage 500 based on the determination function generated by the function generation unit 110. The frequency control unit 112 controls the frequency of the transmission wave VT generated by the signal generator 12.

  In the moving body detection apparatus 1 having the above configuration, the generator 17 that generates a determination function based on a standing wave (combined wave) by the detectors 13 and 14, the A / D converter 15, and the function generator 110. It is configured. The A / D converter 15 may be included in the control unit 11 that is a microcomputer.

<Decision function>
Next, a method for generating a determination function will be described. In the following description, in order to distinguish a plurality of reflectors 300, a plurality of consecutive positive integers from No. 1 are assigned to the plurality of reflectors 300, respectively.

  In the present embodiment, the x-axis is determined as shown in FIG. The origin x = 0 of the x axis may be an arbitrary point, but in the present embodiment, for example, the position of the signal generator 12 is the origin. When the amplitude and frequency of the transmission wave VT are A and f, respectively, and the speed of light is c, the transmission wave VT is expressed by the following equation (1).

  The frequency f is changed from f = f0−fw / 2 to f = f0 + fw / 2 by the control of the signal generator 12 by the frequency control unit 112.

  Assuming that the distance to the k-th reflector 300 is dk, and the ratio of the magnitude of the reflected wave VR to the transmitted wave VT and the phase difference between them at any point on the x-axis are γk and φk, respectively, The reflected wave VRk from the reflector 300 is expressed by the following equation (2).

  When there are n (≧ 1) reflectors 300, the standing wave power p (f, x) at a certain frequency f is expressed by the following equation (3).

  Here, the frequency f can be expressed by the following equation (4), where f0 is the center frequency and fd is the variable representing the change in frequency.

  At points x = x1, x2 between the signal generator 12 and the antenna 10 as shown in FIG. 2, γk << 1 may be considered in view of the proximity of the signal source and the space propagation loss. it can. In this case, p (f, x) can be approximated as the following expression (5) as a function of fd.

  However, Θ in the equation (5) is expressed by the following equation (6).

  In the present embodiment, the transmission wave VT is, for example, a radio wave in the 24 GHz band, and the occupied bandwidth of the transmission wave VT is 76 MHz or less. Therefore, it can be considered that f0 >> fd. In this case, Θ can be approximated by the following equation (7).

  When the detectors 13 and 14 detect the standing wave power p (fd, x) at two locations where Θ = 0 and Θ = π / 2, the detectors 13 and 14 will explain below. Two detection signals orthogonal to each other are output.

  In Expression (7), if the position x where Θ = 0 is the detection position x1, x1 = 0. If the position x where Θ = π / 2 is the detection position x2, then x2 = −λ / 8. However, λ = c / f0.

  Therefore, the standing wave power p (fd, x1) detected at the position of x = x1 and the standing wave power p (fd, x2) detected at the position of x = x2 are expressed by Equation (5). Therefore, it is expressed by the following formulas (8) and (9).

  In the present embodiment, the detector 13 detects the power of the standing wave at the position of x = x1, and outputs the detection signal p (fd, 0) represented by the equation (8). On the other hand, the detector 14 detects the power of the standing wave at the position of x = x2, and outputs a detection signal p (fd, −λ / 8) represented by Expression (9). The A / D converter 15 converts the analog detection signal p (fd, 0) and the detection signal p (fd, −λ / 8) output from the detectors 13 and 14 into a digital format and converts the detection signal p (fd, −λ / 8) into a digital format. Output to.

  When p (fd, 0) and p (fd, −λ / 8) differentiated by fd are respectively pdiff (fd, 0) and pdiff (fd, −λ / 8), pdiff (fd, 0) , Pdiff (fd, −λ / 8) is expressed by the following equations (10) and (11).

  An analysis signal pa (fd) having −pdiff (fd, −λ / 8) as a real part and −pdiff (fd, 0) as an imaginary part is expressed by the following expression (12).

  When the analytic signal pa (fd) is Fourier-transformed with respect to fd, a signal P (x) represented by the following equation (13) is obtained.

  Sa (z) in the equation (13) is a sink function and is represented by the following equation (14).

  The signal P (x) is a function having the distance x as a variable. The signal P (x) is shown as a distance spectrum P (x) in Non-Patent Document 1 described above.

  In the present embodiment, the function generation unit 110 of the control unit 11 generates a signal P (x) based on the detection signals p (fd, 0) and p (fd, −λ / 8) from the A / D converter 15. Ask for. The function generation unit 110 uses the obtained signal P (x) as the determination function P (x). The function generator 110 generates signals pdiff (fd, 0) and pdiff (fd, −λ) represented by the equations (10) and (11) from the detection signals p (fd, 0) and p (fd, −λ / 8). / 8) is obtained, and the analysis signal pa (fd) represented by the equation (12) is obtained from the signals pdiff (fd, 0) and pdiff (fd, −λ / 8). Then, the function generator 110 obtains a determination function P (x) from the analysis signal pa (fd).

  When there is one reflector 300 (n = 1), the amplitude of the determination function P (x) is x = d1, that is, when the distance x matches the distance d1 to the reflector 300 (x -D1 = 0), the maximum.

  It can be said that the determination function P (x) is a complex signal in which the distance x is a variable and the amplitude and phase change according to the value of the variable. Equation (13) can be rewritten as the following Equation (15).

  Equation (15) can be rewritten as the following Equation (16).

  Dk (x) and Ek (x) are expressed by the following equations (17) and (18).

Dk (x) e ^{jEk (x)} is a complex signal corresponding to the kth reflector 300, and indicates the influence of the kth reflector 300 on P (x). When Dk (x) e ^{jEk (x)} is called an individual complex signal, the determination function P (x) is a plurality of individual complex signals D1 (x) corresponding to the first to nth reflectors 300, respectively. ^{e jE1 (x) ~Dn (x} ) e jEn (x) the sum combined signal, i.e. the combined signal of the plurality of discrete complex signals ^{D1 (x) e jE1 (x} ) ~Dn (x) e jEn (x) It can be said that. The individual complex signal Dk (x) e ^{jEk (x)} is the difference distance between the variable x and the distance dk to the kth reflector 300 according to the individual complex signal Dk (x) e ^{jEk (x).} It changes according to. Specifically, as shown in equation (17), the amplitude Dk individual complex signal Dk ^{(x) e JEK (x)} (x) is a variable x, the individual complex signal Dk ^{(x) e JEK (} It changes according to the difference distance (x-dk) between the distance dk to the reflector 300 according to ^x) .

Furthermore, since the amplitude Dk (x) of the individual complex signal Dk (x) e ^{jEk (x)} includes the ^sinc function in the expression indicating the amplitude Dk (x), if the distance dk is constant, The absolute value | x−dk | of the difference distance (x−dk) tends to decrease as the absolute value | x−dk | increases.

  FIG. 3 shows the relationship between (x-dk) and Sa (x-dk). As shown in FIG. 3, Sa (x-dk) tends to decrease as (x-dk) increases or (x-dk) decreases. Therefore, Sa (2πfw / c × (x−dk)) in the equation (17) tends to decrease as the absolute value | x−dk | increases. Therefore, if the distance dk is constant, the amplitude Dk (x) tends to decrease as the absolute value | x−dk | increases. Therefore, the amplitude Dk (x) becomes maximum when x = dk.

  In the determination function P (x), when the variable x matches the distance dk to the k-th reflector 300 due to the presence of Sa (2πfw / c × (x−dk)), a plurality of reflectors are used. Of 300, the influence of the kth reflector 300 is relatively strong.

  As described above, the generation unit 17 obtains the determination function P (x) based on the standing wave. The moving body determination unit 111 of the control unit 11 determines the presence or absence of a person based on the determination function P (x) obtained by the generation unit 17. Hereinafter, the individual complex signal may be referred to as an “influence signal”. Further, when there is no need to particularly distinguish the distances d1 to dn, each is referred to as a distance d.

<Motion detection>
When the kth reflector 300 is a moving object, the reflector 300 moves, and therefore the distance dk to the reflector 300 changes. As a result, as can be seen from the equation (15), the amplitude | P (x) | and the phase arg (P (x)) of the determination function P (x) change. Therefore, the moving object can be detected by observing the time change of the amplitude | P (xz) | of the function value P (xz) (complex signal P (xz)) of the determination function P (x) at a certain target distance xz. It becomes. Similarly, a moving object can be detected by observing a temporal change in the phase arg (P (xz)) of the function value P (xz).

  On the other hand, the determination function P (x) is a composite signal of a plurality of influence signals (individual complex signals) that change in accordance with the difference distance between the distance x and the distance d to the corresponding reflector 300. . When the non-detection target moves, the influence signal corresponding to the non-detection target changes because the distance d to the non-detection target changes due to the movement of the non-detection target. Therefore, the amplitude and phase of the determination function P (x) change under the influence of the movement of the non-detection target. Therefore, each of the temporal changes in the amplitude and phase of the function value P (xz) includes the influence of the motion of the non-detection target.

  Since the garage 500 shown in FIG. 1 is provided with the door 501, the amplitude and phase of the determination function P (x) change due to vibration of the door 501 caused by wind or the like. Therefore, when it is determined whether or not there is a person in the garage 500 based on the temporal change in the amplitude and phase of the function value P (xz), no person is present in the garage 500 due to the vibration of the door 501. Nevertheless, there is a possibility of erroneously determining that a person exists.

  As described above, each of the temporal changes in the amplitude and phase of the function value P (xz) includes the influence of the non-detection target, and therefore, based on the temporal changes in the amplitude and phase of the function value P (xz). In order to appropriately determine the presence or absence of the detection target, it is necessary to remove the influence of the non-detection target included in the time change from the time change.

  However, as described above, the determination function P (x) is a combined signal of a plurality of influence signals that change in accordance with the difference distance between the distance x and the distance d to the corresponding reflector 300. Therefore, when the function value P (xz) is divided into the amplitude and the phase and each is processed individually, it is difficult to remove only the influence of the non-detection object from the time change of the amplitude or the phase. . This point will be described below. Hereinafter, a case where n = 2, that is, a case where a plurality of reflecting objects 300 are configured by two reflecting objects 300 of a detection target object and a non-detection target object will be described as an example.

If the detection object is the first reflection object 300, the influence signal corresponding to the detection object is D1 (x) e ^{jE1 (x)} . If the non-detection target is the second reflector 300, the influence signal corresponding to the non-detection target is D2 (x) e ^{jE2 (x)} . The value D1 (xz) e ^{jE1 (xz)} of the influence signal D1 (x) e ^{jE1 (x) at} the target distance xz and the value D2 (xz ⁾ of the influence signal D2 (x) e ^{jE2 (x)} at the target distance xz ) When e ^{jE2 (xz)} is displayed as a vector on the complex plane, for example, it is as shown in FIG. In the present embodiment, a vector on the complex plane is referred to as a “complex plane vector”.

In FIG. 4, the complex plane vector W1 represents the value D1 (xz) e ^{jE1 (xz)} corresponding to the detection target, and the complex plane vector W2 represents the value D2 (xz) e corresponding to the non-detection target. ^{jE1 (xz)} is represented. The complex plane vector Z represents the function value P (xz). As shown in FIG. 4, a combined vector obtained by adding the complex plane vector W1 and the complex plane vector W2 is a complex plane vector Z.

Here, as shown in FIG. 4, a case is considered where the phase of the complex plane vector W1 changes by ΔθW1 due to the movement of the detection target object, and the phase of the complex plane vector W2 changes by ΔθW2 due to the movement of the non-detection target object. . Since the complex plane vector Z is a composite vector of the complex plane vectors W1 and W2, when the phase of the complex plane vector W1 changes by ΔθW1 and the phase of the complex plane vector W2 changes by ΔθW2, the complex plane vector Z Does not necessarily change by the sum of ΔθW1 and ΔθW2. That is, the phase change amount ΔθZ of the complex plane vector Z is not necessarily the sum of ΔθW1 and ΔθW2. Therefore, the phase change amount ΔθW2 of the complex plane vector W2 indicating the influence of the non-detection target can be obtained, and even if ΔθW2 is subtracted from the phase change amount ΔθZ of the complex plane vector Z, the influence of the detection target is shown. The phase change amount ΔθW1 of the complex plane vector W1 cannot be obtained. That is, even if the amount of time change in the phase of the value D2 (xz) e ^{jE2 (xz)} corresponding to the non-detection target is known and the amount of time change is subtracted from the amount of time change in the phase of the function value P (xz). The time variation of the phase of the value D1 (xz) e ^{jE1 (xz)} corresponding to the detection object cannot be obtained. Therefore, from the temporal change amount of the phase of the function value P (xz), only the temporal change amount of the phase of the value D2 (xz) e ^{jE2 (xz)} corresponding to the non-detection target object, that is, the movement of the non-detection target object is detected. It is difficult to remove only the influence.

The same applies to the amplitude. From the time variation of the amplitude of the function value P (xz), only the time variation of the amplitude of the value D2 (xz) e ^{jE2 (xz)} corresponding to the non-detection target, that is, non-detection. It is difficult to remove only the influence of the movement of the object.

  Thus, in each of the change amount of the amplitude of the function value P (xz) and the change amount of the phase, the influence of the movement of the plurality of reflectors 300 does not appear linearly. Therefore, the function value P (xz) is expressed as the amplitude. When processing is divided into phases, there is a possibility that the presence or absence of a detection target cannot be properly determined.

  Therefore, in the present embodiment, the moving object determination unit 111 does not consider the function value P (xz) separately from the amplitude and the phase, but treats the function value P (xz) as a complex plane vector, and the complex plane vector. The presence or absence of a person in the garage 500 is determined based on the time change. Hereinafter, the moving object detection method in the present embodiment will be described in detail.

When the function value P (xz) is represented by a complex plane vector Z (xz) and the value Dk (xz) e ^{jEk (xz)} is represented by a complex plane vector Wk (xz), the following equation (19) is obtained from the equation (16). Is obtained.

  As shown in Expression (19), the complex plane vector Z (xz) is a vector obtained by adding a plurality of complex plane vectors W1 (xz) to Wn (xz). That is, the complex plane vector Z (xz) is a combined vector of a plurality of complex plane vectors W1 (xz) to Wn (xz) that indicate the influence of the plurality of reflectors 300, respectively.

  Let the complex plane vector Z (xz) and the complex plane vector Wk (xz) at time t be Z (xz, t) and Wk (xz, t), respectively. Then, a complex plane vector ΔZ (xz, t) representing a time change of the complex plane vector Z (xz, t) and a complex plane vector ΔWk (xz, t) representing a time change of the complex plane vector Wk (xz, t) are obtained. It represents with the following formula | equation (20), (21).

  As shown in the equation (20), the complex plane vector ΔZ (xz, t) is obtained at the time (t−Δt) slightly before the complex plane vector Z (xz, t) at the time t. This is a difference vector obtained by subtracting the complex plane vector Z (xz, t−Δt). Similarly, the complex plane vector ΔWk (xz, t) is a time (t−Δt) slightly earlier than the complex plane vector Wk (xz, t) at time t, as shown in Expression (21). ) Is a difference vector obtained by subtracting the complex plane vector Wk (xz, t−Δt).

  Equation (20) can be rewritten into Equation (22) below using Equation (21).

  As shown in the equation (22), the complex plane vector ΔZ (xz, t) is a plurality of complex plane vectors ΔW1 (xz, t) to ΔWn (xz, t) each indicating the influence of the plurality of reflectors 300. This is a composite vector. Hereinafter, when it is not necessary to particularly distinguish the complex plane vectors ΔW1 (xz, t) to ΔWn (xz, t), they may be referred to as complex plane vectors ΔW (xz, t), respectively.

  Since the complex plane vector ΔW (xz, t) corresponding to the stationary non-detected object is zero, the complex plane vector ΔZ (xz, t) indicates the influence of the moving non-detected object. By subtracting the plane vector ΔW (xz, t), a complex plane vector ΔW (xz, t) corresponding to the detection target can be obtained. That is, only the influence of the movement of the non-detection target can be removed from the time change of the function value P (xz). Therefore, a difference vector between the complex plane vector ΔZ (xz, t) and the complex plane vector ΔW (xz, t) indicating the influence of the motion of the non-detection target is obtained, and the presence / absence of the detection target is determined based on the difference vector. Therefore, appropriate motion detection can be performed. That is, the complex plane vector ΔZ (xz, t) representing the time change of the complex plane vector Z (xz) representing the function value P (xz) and the influence of the motion of the non-detection target included in the time change. Appropriate moving object detection can be performed by determining the presence or absence of a moving object based on a difference vector from the complex plane vector ΔW (xz, t).

  In the present embodiment, the moving object determination unit 111 calculates a complex plane vector ΔZ (xz, t) from the determination function P (x) determined by the generation unit 17. In addition, the moving object determination unit 111 obtains a complex plane vector ΔW (xz, t) that represents the influence of the motion of the non-detection target. In the present embodiment, since the door 501 of the garage 500 moves, the moving body determination unit 111 obtains a complex plane vector ΔW (xz, t) that represents the influence of the movement of the door 501. Then, the moving object determination unit 111 obtains a difference vector between the complex plane vector ΔZ (xz, t) and the complex plane vector ΔW (xz, t) that represents the influence of the movement of the door 501, and based on the difference vector. The presence or absence of a person in the garage 500 is determined.

  In the present embodiment, each of the complex plane vector Z (xz, t), the complex plane vector ΔZ (xz, t), the complex plane vector W (xz, t), and the complex plane vector ΔW (xz, t) The process is divided into axis coordinates and imaginary axis coordinates.

  When the real axis coordinate and the imaginary axis coordinate of the complex plane vector Z (xz, t) are U (xz, t) and V (xz, t), respectively, the complex plane vector Z (xz, t) is expressed by the following equation (23 ).

  U (xz, t) is the real part of the function value P (xz), and V (xz, t) is the imaginary part of the function value P (xz). The function value P (xz) is expressed by the following equation (24) when expressed in rectangular coordinates.

  The expression (24) can be rewritten as the following expression (27) using REALk (xz) and IMAGEk (xz) represented by the following expressions (25) and (26).

  U (xz) and V (xz) are expressed by the following equations (28) and (29).

  As shown in the equation (28), the real part U (xz) is a sum of a plurality of real parts REAL1 (xz) to REALn (xz) each indicating the influence of the plurality of reflectors 300. Further, as shown in Expression (29), the imaginary part V (xz) is a sum of a plurality of imaginary parts IMAGE1 (xz) to IMAGEn (xz) each indicating the influence of the plurality of reflectors 300. Therefore, unlike the amplitude and phase of the function value P (xz), the influence of the plurality of reflectors 300 appears linearly in each of the real part U (xz) and the imaginary part V (xz).

  U (xz) and V (xz) at time t are U (xz, t) and V (xz, t), respectively, and the real and imaginary axis coordinates of the complex plane vector ΔZ (xz, t) are ΔU, respectively. Assuming that (xz, t) and ΔV (xz, t), ΔU (xz, t) and ΔV (xz, t) are expressed by the following equations (30) and (31).

  When the real axis coordinate and the imaginary axis coordinate of the complex plane vector ΔWk (xz, t) are respectively ΔXk (xz, t) and ΔYk (xz, t), ΔU (xz, t) and ΔV (xz, t) are as follows: (32) and (33).

  As shown in the equation (32), ΔU (xz, t) is a sum of ΔX1 (xz, t) to ΔXn (xz, t) indicating the influence of the plurality of reflectors 300, respectively. Therefore, the influence of the plurality of reflectors 300 appears linearly in ΔU (xz, t), similarly to U (xz, t). Similarly, ΔV (xz, t) is a sum of ΔY1 (xz, t) to ΔYn (xz, t) indicating the influence of the plurality of reflectors 300, as shown in Expression (33). Therefore, the influence of the plurality of reflectors 300 appears linearly in ΔV (xz, t), similarly to V (xz, t).

  When performing the moving object detection, the moving object determination unit 111 first obtains the real part U (xz) and the imaginary part V (xz) of the function value P (xz) from the determination function P (x). Next, the moving body determination unit 111 obtains ΔU (xz, t) and ΔV (xz, t) using the equations (30) and (31). This means that the complex plane vector ΔZ (xz, t) is obtained. In addition, the moving object determination unit 111 obtains ΔX (xz, t) and ΔY (xz, t) of the complex plane vector ΔW (xz, t) representing the influence of the movement of the door 501. This means that a complex plane vector ΔW (xz, t) representing the influence of the movement of the door 501 is obtained. Then, the moving object determination unit 111 obtains a value obtained by subtracting ΔX (xz, t) from ΔU (xz, t) and a value obtained by subtracting ΔY (xz, t) from ΔV (xz, t). The value obtained by subtracting ΔX (xz, t) from ΔU (xz, t) is the real axis coordinate of the difference vector J between the complex plane vector ΔZ (xz, t) and the complex plane vector ΔW (xz, t). , ΔV (xz, t) minus ΔY (xz, t) is the imaginary axis coordinate of the difference vector J. The moving body determination unit 111 determines the presence or absence of a person in the garage 500 based on the real axis coordinates and the imaginary coordinates of the difference vector J. Assuming that the real axis coordinate and the imaginary axis coordinate of the difference vector J are ΔUc (xz, t) and ΔVc (xz, t), respectively, ΔUc (xz, t), ΔVc (xz, t) and the difference vector J (34), (35), and (36).

  When determining whether or not there is a person in the garage 500 based on ΔUc (xz, t) and ΔVc (xz, t), the moving object determination unit 111 uses ΔUc (xz, t) and ΔVc (xz, t). For example, a determination value R represented by the following equation (37) is obtained. The determination value R is the size of the difference vector J.

  The moving body determination unit 111 determines that there is a person in the garage 500 when the determination value R is greater than the threshold value. On the other hand, the moving body determination unit 111 determines that there is no person in the garage 500 when the determination value R is equal to or less than the threshold value. The moving object determination unit 111 determines that there is a person in the garage 500 when the determination value R is equal to or greater than the threshold value, and determines that there is no person in the garage 500 when the determination value R is less than the threshold value. good. Moreover, the moving body determination part 111 may determine the determination value R by another method.

<How to find ΔW (xz, t) indicating the influence of the movement of the non-detection object (door)>
Next, an example of how to obtain the complex plane vector ΔW (xz, t) indicating the influence of the motion of the non-detection target object necessary for moving object detection will be described. In the following description, it is assumed that the distance x to the door 501 of the garage 500 is xdoor.

  The moving body determination unit 111 uses the ratios RATIO_U (xz) and RATIO_V (xz) represented by the following formulas (38) and (39) obtained when the door 501 is moving, A complex plane vector ΔW (xz, t) indicating the influence of motion is obtained.

  ΔU (xdoor, t) in equation (38) is a complex plane vector representing the function value P (xdoor) of the determination function P (x) when the variable x is the distance xdoor to the moving door 501. The real axis coordinates of ΔZ (xdoor, t) representing the time change of Z (xdoor) are shown. On the other hand, ΔV (xdoor, t) in the equation (39) indicates an imaginary axis coordinate of ΔZ (xdoor, t). Therefore, the complex plane vector ΔZ (xdoor, t) is obtained by obtaining ΔU (xdoor, t) and ΔV (xdoor, t).

  Here, as can be seen from the above formulas (25), (26), (28), (29), etc., the formula representing U (x, t) and V (x, t) has a sink function Sa (2πfw). / C × (x−dk)) is included, U (xdoor, t) and V (xdoor, t) are affected by the door 501 when the variable x is the distance xdoor to the door 501. Appears strongly. Therefore, ΔU (xdoor, t) and ΔV (xdoor, t) strongly show the influence of the movement of the door 501 at time t, and ΔU (xdoor, t) and ΔV (xdoor, t) It can be considered that the movement of the door 501 at t is shown. Since the reflector 300 other than the person and the door 501 hardly moves in the garage 500, ΔU (xz, t) and ΔV (xz, t) are obtained when there is no person at the distance xz. It can be considered that only the influence of the movement of the door 501 is received. That is, ΔU (xz, t) and ΔV (xz, t) are vectors ΔZ (xdoor, t) (size and direction) indicated by ΔU (xdoor, t) and ΔV (xdoor, t). When moving, it can be said that the movement of the door 501 shows the influence on the complex plane vector Z (xz, t) at the distance xz. Therefore, ΔU (xz, t) / ΔU (xdoor, t) and ΔV (xz, t) / ΔV (xdoor, t) are vectors ΔZ (xdoor, t) (ΔU (xdoor, t) representing the movement of the door 501. ) And ΔV (xdoor, t)) as a reference, the influence of the movement of the door 501 on the complex plane vector Z (xz, t) is shown. That is, ΔU (xz, t) / ΔU (xdoor, t) and ΔV (xz, t) / ΔV (xdoor, t) are based on ΔZ (xdoor, t) representing the movement of the door 501. The influence of the movement of the door 501 included in the complex plane vector ΔZ (xz, t) (ΔU (xz, t) and ΔV (xz, t)) is shown.

  However, when a person is present at the position of the distance xz, the influence of the person's movement also appears in ΔU (xz, t) and ΔV (xz, t). Therefore, in the present embodiment, as shown in the equation (38), the time average of ΔU (xz, t) / ΔU (xdoor, t) (M ΔU (xz, t at different times t) ) / ΔU (xdoor, t)) is reduced, thereby reducing the influence of the human motion that appears in ΔU (xz, t). Similarly, as shown in the equation (39), the time average of ΔV (xz, t) / ΔV (xdoor, t) (M ΔV (xz, t) / ΔV (xdoor at different times t) , T), the influence of human movement appearing in ΔV (xz, t) is reduced. Therefore, it can be said that the ratios RATIO_U (xz) and RATIO_V (xz) indicate the influence of the movement of the door 501 on Z (xz) when ΔZ (xdoor) representing the movement of the door 501 is used as a reference. .

  Based on the complex plane vectors ΔU (xdoor, t) and ΔV (xdoor, t) at the time t and the ratios RATIO_U (xz) and RATIO_V (xz), the moving object determination unit 111 sets the door 501 at the time t. A complex plane vector ΔW (xz, t) indicating the influence of motion is obtained. Specifically, the moving object determination unit 111 obtains the real axis coordinate ΔX (xz, t) of the complex plane vector ΔW (xz, t) indicating the influence of the movement of the door 501 using the following equation (40). The imaginary axis coordinate ΔY (xz, t) of the complex plane vector ΔW (xz, t) indicating the influence of the movement of the door 501 is obtained using the following equation (41).

  The above equations (34) and (35) can be rewritten as follows using equations (40) and (41).

  When the moving object determination unit 111 obtains the complex plane vector ΔW (xz, t) at the time t indicating the influence of the movement of the door 501, Expressions (34) and (35) (Expressions (40) and (41)) are obtained. The real axis coordinate ΔUc (xz, t) and the imaginary axis coordinate ΔVc (xz.t) of the difference vector J are obtained. And the moving body determination part 111 determines the presence or absence of the person in the garage 500 based on real axis coordinate (DELTA) Uc (xz, t) and imaginary time coordinate (DELTA) Vc (xz.t) as mentioned above.

  The ratios RATIO_U (xz, t) and RATIO_V (xz, t) may be obtained in advance and stored in the control unit 11 in advance. Further, the ratios RATIO_U (xz, t) and RATIO_V (xz, t) may be obtained when the moving object determination unit 111 performs moving object detection.

<Specific examples of moving object detection processing>
Next, various specific examples of the operation of the moving object determination unit 111 will be described.

<First operation example>
FIG. 5 is a flowchart showing a first operation example of the moving object determination unit 111. In this example, the moving body determination unit 111 determines whether there is a person in the seat of the car 600 in the garage 500. It is assumed that the distance from the moving body detection device 1 to the seat is 5 m, for example. That is, the moving object determination unit 111 determines whether or not a person is present at a position 5 m from the moving object detection device 1. In this example, there is a door 501 at a position 6 m from the moving object detection device 1 (xdoor = 6 m). In this example, the ratios RATIO_U (xz, t) and RATIO_V (xz, t) are obtained in advance and stored in the control unit 11.

  As shown in FIG. 5, in step s1, the moving object determination unit 111 performs the object detection for each predetermined time Δt based on the determination function P (x) generated by the function generation unit 110 as described above. U (xz) and V (xz) when the distance xz is 5 m are obtained. Furthermore, the moving object determination unit 111 obtains U (xdoor) and V (xdoor) when the distance xdoor is 6 m for each predetermined time Δt based on the determination function P (x).

  Next, in step s2, the moving object determination unit 111 calculates ΔU (xz, t) and ΔV (xz, t), and ΔU (xdoor, t) and ΔV (xdoor, t).

  Next, in step s3, the moving object determination unit 111 calculates the ratios RATIO_U (xz, t) and RATIO_V (xz, t) stored in advance in the control unit 11, and ΔU (xdoor, t) and ΔV ( ΔX (xz, t) and ΔY (xz, t) represented by equations (40) and (41) are obtained using xdoor, t).

  Next, in step s4, the moving object determination unit 111 determines ΔU (xz, t) and ΔV (xz, t) obtained in step s2, and ΔX (xz, t) and ΔY (xz, t) obtained in step s3. Are used to determine ΔUc (xz, t) and ΔVc (xz, t) represented by equations (34) and (35).

  Next, in step s5, the moving object determination unit 111 calculates a determination value R shown in Expression (37) using ΔUc (xz, t) and ΔVc (xz, t) obtained in step s4. In step s6, the moving object determination unit 111 determines whether or not there is a person at a distance x = 5 m based on the determination value R. When the determination value R is larger than the threshold value, the moving object determination unit 111 determines that there is a person at a distance x = 5 m in the garage 500, and when the determination value R is equal to or less than the threshold value. Determines that no person is present at a distance x = 5 m in the garage 500.

  The moving object determination unit 111 repeatedly executes the moving object detection process from the above steps s1 to s6 every predetermined time.

<Second operation example>
FIG. 6 is a flowchart showing a second operation example of the moving object determination unit 111. In this example, similarly to the first operation example, the moving object determination unit 111 determines whether or not there is a person at a position 5 m from the moving object detection device 1, and the door 501 at a position 6 m from the moving object detection device 1 is detected. Exists (xdoor = 6 m). On the other hand, in this example, the ratios RATIO_U (xz, t) and RATIO_V (xz, t) stored in advance in the control unit 11 are updated by the moving object determination unit 111 in the moving object detection process. The moving object determination unit 111 repeatedly executes the moving object detection process shown in FIG. 6 every predetermined time.

  As illustrated in FIG. 6, the moving object determination unit 111 executes the above-described steps s1 and s2, and ΔU (xz, t), ΔV (xz, t), ΔU (xdoor, t), and ΔV (xdoor, t )

  Next, in step s11, the moving body determination unit 111 determines whether the door 501 is moving using ΔU (xdoor, t) and ΔV (xdoor, t). The moving body determination unit 111 obtains the determination value S using, for example, the following formula (44). And the moving body determination part 111 determines with the door 501 moving, when the determination value S is larger than a threshold value. On the other hand, the moving body determination part 111 determines with the door 501 not moving, when the determination value S is below a threshold value.

  If the moving object determination unit 111 determines that the door 501 is moving in step s11, the moving object determination unit 111 updates RATIO_U (xz, t) and RATIO_V (xz, t) in step s12. Specifically, the moving object determination unit 111 calculates ΔU (xz, t), ΔV (xz, t), ΔU (xdoor, t), and ΔV (xdoor, t) obtained in step s2, and Equations (38), Using (39), RATIO_U (xz, t) and RATIO_V (xz, t) are newly obtained. Then, the moving object determination unit 111 replaces RATIO_U (xz, t) and RATIO_V (xz, t) stored in the control unit 11 with newly obtained RATIO_U (xz, t) and RATIO_V (xz, t). . Accordingly, RATIO_U (xz, t) and RATIO_V (xz, t) stored in the control unit 11 are updated.

  When step s12 is executed, the moving object determination unit 111 executes step s3 to obtain ΔX (xz, t) and ΔY (xz, t). Here, RATIO_U (xz, t) and RATIO_V (xz, t) updated in step s12 are used. Thereafter, the moving object determination unit 111 performs steps s4 to s6 in the same manner. In step s11, if the moving body determination unit 111 determines that the door 501 is not moving, the moving body determination unit 111 executes steps s3 to s6 without executing step s12.

  Thus, in this operation example, RATIO_U (xz, t) and RATIO_V (xz, t) are updated in the moving object detection process. Since the influence of the movement of the door 501 on ΔU (xz, t) and ΔV (xz, t) is not constant and changes in real time depending on the distance to the door 501, RATIO_U (xz, t) and RATIO_V ( By updating xz, t), the determination accuracy of the presence or absence of a person in the garage 500 is further improved.

<Third operation example>
FIG. 7 is a flowchart showing a third operation example of the moving object determination unit 111. In this example, the moving body determination unit 111 determines whether or not there is a person within a range of 3 m to 5 m from the moving body detection device 1. That is, in this example, the determination range of the moving object detection device 1 is in the range of 3 m to 5 m from the moving object detection device 1. Thereby, the moving body determination unit 111 can determine whether or not there is a person in the car 600 of the garage 500. In this example, nine target distances xz within the determination range are used. Specifically, 3 m, 3.25 m, 3.5 m, 3.75 m, 4 m, 4.25 m, 4.5 m, 4.75 m, and 5 m are used as the target distance xz. In this example, RATIO_U (xz, t) and RATIO_V (xz, t) at each of the nine target distances xz are obtained in advance and stored in the control unit 11. The moving object determination unit 111 updates nine sets of RATIO_U (xz, t) and RATIO_V (xz, t) corresponding to the nine target distances xz, respectively. Further, in this example, as in the first and second operation examples, there is a door 501 at a position 6 m from the moving body detection device 1 (xdoor = 6 m). The moving object determination unit 111 repeatedly executes the moving object detection process shown in FIG. 7 every predetermined time.

  As illustrated in FIG. 7, in step s21, the moving object determination unit 111 determines U (xz) and V (9) at each of nine target distances xz of 3m to 5m based on the determination function P (x). xz) is obtained every predetermined time Δt. Furthermore, the moving object determination unit 111 obtains U (xdoor) and V (xdoor) when the distance xdoor is 6 m for each predetermined time Δt based on the determination function P (x).

  Next, in step s22, the moving object determination unit 111 performs ΔU (xz, t) and ΔV (xz, t), ΔU (xdoor, t), and ΔV (9) at each of nine target distances xz from 3 m to 5 m. xdoor, t).

  Next, the moving body determination unit 111 executes the above-described step s11 to determine whether or not the door 501 is moving.

  If the moving body determination unit 111 determines in step s11 that the door 501 is moving, in step s23, nine sets of RATIO_U (xz, t) and RATIO_V (RATIO_V (9) respectively corresponding to the nine target distances xz of 3 m to 5 m. xz, t) is updated. Specifically, the moving object determination unit 111 calculates ΔU (xz, t), ΔV (xz, t), ΔU (xdoor, t), and ΔV (xdoor, t) obtained in step s22, Equation (38), Using (39), nine sets of RATIO_U (xz, t) and RATIO_V (xz, t) respectively corresponding to the nine target distances xz are obtained. Then, the moving object determination unit 111 calculates nine sets of RATIO_U (xz, t) and RATIO_V (xz, t) stored in the control unit 11 as nine sets of RATIO_U (xz, t) and RATIO_V ( xz, t). As a result, nine sets of RATIO_U (xz, t) and RATIO_V (xz, t) respectively corresponding to nine target distances xz of 3 m to 5 m are updated.

  When step s23 is executed, the moving object determination unit 111, in step s24, nine sets of RATIO_U (xz, t) and RATIO_V (xz, t) in the control unit 11, and ΔU (xdoor, t) and ΔV (xdoor, t) are used to determine ΔX (xz, t) and ΔY (xz, t) at each of nine target distances xz of 3 to 5 m. Here, nine sets of RATIO_U (xz, t) and RATIO_V (xz, t) updated in step s23 are used.

  Next, in step s25, the moving object determination unit 111 determines ΔU (xz, t) and ΔV (xz, t) obtained in step s22, and ΔX (xz, t) and ΔY (xz, t) obtained in step s24. Are used to determine ΔUc (xz, t) and ΔVc (xz, t) at each of nine target distances xz from 3 m to 5 m. As a result, nine sets of ΔUc (xz, t) and ΔVc (xz, t) respectively corresponding to the nine target distances xz are obtained.

  Next, in step s26, the moving object determination unit 111 calculates a determination value R for each of the nine sets of ΔUc (xz, t) and ΔVc (xz, t) obtained in step s25. As a result, nine determination values R respectively corresponding to nine target distances xz of 3 m to 5 m are obtained.

  Next, in step s27, when the maximum value of the nine determination values R obtained in step s26 is larger than the threshold value, the moving object determination unit 111 determines the determination range from 3 m to 5 m from the moving object detection device 1. It is determined that there is a person in the car 600. On the other hand, when the maximum value is equal to or smaller than the threshold value, the moving object determination unit 111 determines that there is no person within the determination range of 3 m to 5 m from the moving object detection device 1, that is, the car 600.

  If the moving object determination unit 111 determines in step s11 that the door 501 is not moving, the moving object determination unit 111 executes steps s24 to s27 without executing step s23, and determines whether there is a person within the determination range.

  Thus, in this example, ΔUc (xz, t) and ΔVc (xz, t) are obtained for each of a plurality of target distances xz within the determination range of 3 m to 5 m. In other words, the difference vector J is obtained for each of the plurality of target distances xz within the determination range. When a person is present at the position of the target distance xz, the magnitude of the difference vector J is increased, so that at least one of ΔUc (xz, t) and ΔVc (xz, t) is increased. Therefore, by determining the presence / absence of a person based on ΔUc (xz, t) and ΔVc (xz, t) obtained for a plurality of target distances xz within the determination range, the presence / absence of a person within the determination range Can be determined appropriately.

<Fourth operation example>
FIG. 8 is a flowchart showing a fourth operation example of the moving object determination unit 111. In this example, the moving body determination unit 111 determines whether or not there is a person within a range of 0 to 5 m from the moving body detection device 1. That is, the determination range of the moving body detection device 1 is a range of 0 to 5 m from the moving body detection device 1. Thereby, the moving body determination unit 111 can determine whether or not there is a person in the garage 500 for the entire region of the garage 500. In this example, 21 target distances xz within the determination range are used. Specifically, 0 m, 0.25 m, 0.5 m, 0.75 m, 1 m, 1.25 m, 1.5 m, 1.75 m, 2 m, 2.25 m, 2.5 m, 2.75 m, 3 m, 3 m, .25m, 3.5m, 3.75m, 4m, 4.25m, 4.5m, 4.75m, 5m are used as the target distance xz. In this example, RATIO_U (xz, t) and RATIO_V (xz, t) at each of the 21 target distances xz are obtained in advance and stored in the control unit 11. The moving object determination unit 111 updates 21 sets of RATIO_U (xz, t) and RATIO_V (xz, t) corresponding to the 21 target distances xz. Further, in this example, as in the first and second operation examples, there is a door 501 at a position 6 m from the moving body detection device 1 (xdoor = 6 m). The moving object determination unit 111 repeatedly executes the moving object detection process shown in FIG. 8 every predetermined time.

  As illustrated in FIG. 8, in step s31, the moving object determination unit 111 determines U (xz) and V () at each of 21 target distances xz from 0 m to 5 m based on the determination function P (x). xz) is obtained every predetermined time Δt. Furthermore, the moving object determination unit 111 obtains U (xdoor) and V (xdoor) when the distance xdoor is 6 m for each predetermined time Δt based on the determination function P (x).

  Next, in step s32, the moving object determination unit 111 performs ΔU (xz, t) and ΔV (xz, t), ΔU (xdoor, t), and ΔV (21 at each of the 21 target distances xz from 0 m to 5 m. xdoor, t).

  Next, the moving body determination unit 111 executes step s11 described above to determine whether the door 501 is moving.

  If the moving body determination unit 111 determines in step s11 that the door 501 is moving, in step s33, 21 sets of RATIO_U (xz, t) and RATIO_V (RATIO_V () corresponding to 21 target distances xz of 0 m to 5 m, respectively. xz, t) is updated. Specifically, the moving object determination unit 111 calculates ΔU (xz, t), ΔV (xz, t), ΔU (xdoor, t), and ΔV (xdoor, t) obtained in step s32, Expression (38), Using (39), 21 sets of RATIO_U (xz, t) and RATIO_V (xz, t) respectively corresponding to the 21 target distances xz are newly obtained. Then, the moving object determination unit 111 calculates 21 sets of RATIO_U (xz, t) and RATIO_V (xz, t) stored in the control unit 11 as 21 sets of RATIO_U (xz, t) and RATIO_V ( xz, t). Thereby, 21 sets of RATIO_U (xz, t) and RATIO_V (xz, t) respectively corresponding to 21 target distances xz of 0 m to 5 m are updated.

  When step s33 is executed, the moving object determination unit 111, in step s34, 21 sets of RATIO_U (xz, t) and RATIO_V (xz, t) in the control unit 11, and ΔU (xdoor, t) and ΔV (xdoor, t) are used to obtain ΔX (xz, t) and ΔY (xz, t) at each of 21 object distances xz from 0 m to 5 m. Here, 21 sets of RATIO_U (xz, t) and RATIO_V (xz, t) updated in step s33 are used.

  Next, in step s35, the moving object determination unit 111 determines ΔU (xz, t) and ΔV (xz, t) obtained in step s32, and ΔX (xz, t) and ΔY (xz, t) obtained in step s34. Are used to obtain ΔUc (xz, t) and ΔVc (xz, t) at 21 target distances xz of 0 to 5 m. Thereby, 21 sets of ΔUc (xz, t) and ΔVc (xz, t) respectively corresponding to the 21 object distances xz are obtained.

  Next, in step s36, the moving object determination unit 111 calculates a determination value R for each of the 21 sets of ΔUc (xz, t) and ΔVc (xz, t) obtained in step s35. Thus, 21 determination values R respectively corresponding to 21 target distances xz of 0 m to 5 m are obtained.

  Next, in step s37, the moving body determination unit 111, when the maximum value among the 21 determination values R obtained in step s36 is larger than the threshold value, is within the range of 0m to 5m from the moving body detection device 1. That is, it is determined that there is a person in the garage 500. On the other hand, when the maximum value is equal to or less than the threshold value, the moving object determination unit 111 determines that there is no person within the range of 0 to 5 m from the moving object detection device 1, that is, the garage 500.

  If the moving object determination unit 111 determines in step s11 that the door 501 is not moving, the moving object determination unit 111 executes steps s34 to s37 without executing step s33, and determines whether or not there is a person within the determination range.

  In the third and fourth operation examples, RATIO_U (xz, t) and RATIO_V (xz, t) are updated, but may not be updated as in the first operation example.

  Further, in the third and fourth operation examples, the presence / absence of a person is determined based on the comparison result between the maximum value of the plurality of determination values R and the threshold value, but the total value of the plurality of determination values R The presence or absence of a person may be determined based on the comparison result between the threshold value and the threshold value.

  As described above, in the present embodiment, the complex plane vector ΔZ (xz, t) representing the time change of the complex plane vector Z (xz) representing the function value P (xz), and the non-included in the time change. Since the presence / absence of a moving object is determined based on the difference vector J from the complex plane vector ΔW (xz, t) representing the influence of the movement of the detection target object, appropriate moving object detection can be performed. Therefore, the determination accuracy of the presence or absence of a moving object can be improved as compared with the case where the moving object is detected based on the time change of the amplitude of the function value P (xz) or the time change of the phase of the function value P (xz).

  In addition, as in Patent Document 1, in the moving object detection using the Doppler sensor, when the detection object and the non-detection object exist in the same direction as viewed from the Doppler sensor, the detection object and the non-detection object It is difficult to distinguish things. On the other hand, in the moving object detection according to the present embodiment, the determination function P (x) that changes according to the difference distance between the variable x and the distance d to the reflector 300 is used. Even if the detection target object and the non-detection target object exist in the same direction as viewed from the moving object detection device 1, if the distance d to the detection target object and the non-detection target object is different, the detection target object and the non-detection target object are detected. Objects can be distinguished. Therefore, in the moving object detection according to the present embodiment, the determination accuracy of the presence or absence of the moving object is improved as compared with the moving object detection using the Doppler sensor.

<First Modification>
In this modification, another example of how to obtain the complex plane vector ΔW (xz, t) indicating the influence of the motion of the non-detection target will be described.

  In the present modification, the moving object determination unit 111 uses the ratios RATIO_U1 (xz, t) and RATIO_V1 (xz, t) represented by the following expressions (45) and (46) to influence the movement of the door 501. A complex plane vector ΔW (xz, t) indicating

  However, α1 is an update rate (0 ≦ α1 ≦ 1) set as appropriate. Β1 is expressed by the following equation (47) using a threshold value VELth that is set as appropriate.

  Here, ΔUn (xz, t) and ΔVn (xz, t) are expressed by the following equations (48) and (49).

  A complex plane vector ΔZn (xz, t) having ΔUn (xz, t) as a real axis coordinate and ΔVn (xz, t) as an imaginary axis coordinate is an amplitude, and the amplitude of the complex plane vector ΔZ (xz, t) is the amplitude. It has a value obtained by normalizing with the amplitude of the complex plane vector ΔZ (xdoor, t), and subtracts the phase of the complex plane vector ΔZ (xdoor, t) from the phase of the complex plane vector ΔZ (xz, t) as the phase. A vector with the resulting values.

  FIG. 9 is a diagram illustrating an example of the relationship between ΔZ (xz, t) and ΔZ (xdoor, t). FIG. 10 is a diagram showing ΔZn (xz, t) when the relationship between ΔZ (xz, t) and ΔZ (xdoor, t) is the relationship shown in FIG. ΔZn (xz, t) shown in FIG. 10 is made such that the direction of ΔZ (xdoor, t) shown in FIG. 9 coincides with the positive direction of the x-axis, and the amplitude of ΔZ (xdoor, t) is normalized to 1. It can be said that ΔZ (xz, t) is obtained.

  As described above, the vector ΔZ (xz, t) indicated by ΔU (xz, t) and ΔV (xz, t) is the vector ΔZ (xdoor) indicated by ΔU (xdoor, t) and ΔV (xdoor, t). , T), it can be said that the movement of the door 501 shows the influence on the complex plane vector Z (xz) when the door 501 is moving. Accordingly, the vector ΔZn (xz, t) indicated by ΔUn (xz, t) and ΔVn (xz, t) is the unit vector UNT = [1, 0], and the door 501 is moved when the door 501 is moving. It can be said that the influence of the movement on the complex plane vector Z (xz, t) is shown. That is, it can be said that ΔZn (xz, t) indicates the influence of the movement of the door 501 included in ΔZ (xz) when the door 501 moves with the unit vector UNT.

  However, as described above, when a person is present at the distance xz, the influence of the movement of the person also appears in ΔU (xz, t) and ΔV (xz, t). Therefore, when a person exists at the position of the distance xz, the influence of the person's movement also appears in ΔUn (xz, t) and ΔVn (xz, t).

  Therefore, in the present modification, the ratios RATIO_U1 (xz, t) and RATIO_V1 (xz, t) are updated using the above equations (46) and (47), so that A weighted time average of ΔU (xz, t) and ΔV (xz, t) is obtained. This reduces the influence of human movement at the ratios RATIO_U1 (xz, t) and RATIO_V1 (xz, t). Therefore, the ratios RATIO_U1 (xz, t) and RATIO_V1 (xz, t) are the cases where the movement of the door 501 is represented by complex plane vectors whose real axis coordinates and imaginary axis coordinates are “1” and “0”, respectively. The effect of the movement of the door 501 on the complex plane vector Z (xz, t) is shown. That is, the ratios RATIO_U1 (xz, t) and RATIO_V1 (xz, t) are the cases where the movement of the door 501 is represented by complex plane vectors whose real axis coordinates and imaginary axis coordinates are “1” and “0”, respectively. The influence of the movement of the door 501 included in the plurality of plane vectors ΔZ (xz, t) is shown.

In the expressions (45) and (46), β1α1 is the update rate of ΔUn (xz, t) and ΔVn (xz, t). The update rate β1α1 indicates how much ΔUn (xz, t) and ΔVn (xz, t) are reflected when RATIO_U1 (xz, t) and RATIO_V1 (xz, t) are updated. As shown in Equation (47), β1 increases as (ΔU (xdoor, t) ² + ΔV (xdoor, t) ² ) increases (however, the upper limit is 1). Therefore, it can be said that β1 increases as the door 501 existing at the position of x = xdoor moves greatly. Therefore, when RATIO_U1 (xz, t) and RATIO_V1 (xz, t) are updated, ΔUn (xz, t) and ΔVn (xz, t) become RATIO_U1 (xz, t) as the door 501 moves more greatly. ) And RATIO_V1 (xz, t).

  Thus, in this modification, when RATIO_U1 (xz, t) and RATIO_V1 (xz, t) are updated, ΔUn (xz, t) and ΔVn (xz) according to the movement of the door 501 at that time. , T) is reflected to RATIO_U1 (xz, t) and RATIO_V1 (xz, t). Therefore, RATIO_U1 (xz, t) and RATIO_V1 (xz, t) can be updated appropriately.

  Based on the complex plane vectors ΔU (xdoor, t) and ΔV (xdoor, t) and the ratios RATIO_U1 (xz) and RATIO_V1 (xz) at the time t, the moving object determination unit 111 sets the door 501 at the time t. A complex plane vector ΔW (xz, t) indicating the influence of motion is obtained. Specifically, the moving body determination unit 111 obtains the real axis coordinate ΔX (xz, t) of the complex plane vector ΔW (xz, t) indicating the influence of the movement of the door 501 using the following equation (50). The imaginary axis coordinate ΔY (xz, t) of the complex plane vector ΔW (xz, t) indicating the influence of the movement of the door 501 is obtained using the following equation (51).

  The above equations (34) and (35) can be rewritten as follows using equations (50) and (51).

  FIG. 11 is a diagram illustrating an example of a relationship between a unit plane UNT and a complex plane vector L (xz, t) having RATIO_U1 (xz, t) as real axis coordinates and RATIO_V1 (xz, t) as imaginary axis coordinates. It is. FIG. 12 shows an example of a complex plane vector ΔW (xz, t) indicating the influence of the movement of the door 501 when the relationship between L (xz, t) and the unit vector UNT is the relationship shown in FIG. FIG. ΔW (xz) indicating the influence of the movement of the door 501 included in ΔZ (xz, t) when the movement of the door 501 is represented by ΔZ (xdoor, t) by the expressions (50) and (51). , T) can be determined.

  When the moving body determination unit 111 obtains the complex plane vector ΔW (xz, t) at the time t indicating the influence of the movement of the door 501, Expressions (34) and (35) (Expressions (50) and (51)) are obtained. The real axis coordinate ΔUc (xz, t) and the imaginary axis coordinate ΔVc (xz.t) of the difference vector J are obtained. And the moving body determination part 111 determines the presence or absence of the person in the garage 500 based on real axis coordinate (DELTA) Uc (xz, t) and imaginary time coordinate (DELTA) Vc (xz.t) as mentioned above.

  When the complex plane vector ΔW (xz, t) indicating the influence of the motion of the non-detection target is obtained as in this modification, in the operation examples shown in FIGS. 5 to 8 described above, RATIO_U (xz , T) and RATIO_V1 (xz, t) are used instead of RATIO_U1 (xz, t) and RATIO_V1 (xz, t).

  Further, as in the operation examples of FIGS. 6 to 8, when RATIO_U1 (xz, t) and RATIO_V1 (xz, t) are updated in the moving object detection process, step s11 is not executed. FIG. 13 is a flowchart of the present modification corresponding to FIG. As shown in FIG. 13, in this modification, step s33 is executed immediately after step s32. In step s33, RATIO_U1 (xz, t) and RATIO_V1 (xz, t) are updated using equations (45) and (46). RATIO_U1 (xz, t−Δt) and RATIO_V1 (xz, t−Δt) in Expressions (45) and (46) are stored in the control unit 11 and are calculated as RATIO_U1 (xz) and RATIO_V1 ( xz) is used.

  The same applies to the operation example of FIG. 6. Even if step s11 is not executed, step s12 is executed immediately after step s2, and RATIO_U1 (xz, t) and RATIO_V1 (xz, t) are updated. good. Similarly, in the operation example of FIG. 7, step s11 may be performed immediately after step s22 without performing step s11, and RATIO_U1 (xz, t) and RATIO_V1 (xz, t) may be performed.

<Second Modification>
In the garage 500, there is a possibility that there is a moving reflector 300 other than the door 501 although it is sufficiently smaller than the movement of the door 501. For example, when a doll or amulet is suspended in the room of the car 600 in the garage 500, the doll or the amulet becomes a moving reflector 300. In such a case, ΔUc (xz, t) and ΔV (xz, t) may include the influence of the moving reflector 300 other than the door 501, and the determination accuracy of the presence or absence of a person in the garage 500 May be reduced.

  Therefore, in the present modification, the moving body determination unit 111 responds to frequency components corresponding to the movement of the person from each of ΔUc (xz, t) and ΔVc (xz, t), specifically, the vibration of the person due to breathing. Frequency components extracted. And the moving body determination part 111 determines the presence or absence of the person in the garage 500 based on the extracted frequency component. Thereby, the determination precision of the presence or absence of the person in the garage 500 improves.

  Since the frequency of human vibration due to breathing is approximately 0.2 to 0.5 Hz, the moving object determination unit 111 determines 0.2 to 0.5 Hz from each of ΔUc (xz, t) and ΔVc (xz, t). The frequency components up to are extracted. When the magnitude of the frequency component extracted from ΔUc (xz, t) is ΔUcc (xz, t) and the magnitude of the frequency component extracted from ΔVc (xz, t) is ΔVcc (xz, t), the moving object determination unit 111 represents the determination value R using ΔUcc (xz, t) and ΔVcc (xz, t) instead of ΔUc (xz, t) and ΔVc (xz, t) in the above equation (37), respectively. . ΔUcc (xz, t) and ΔVcc (xz, t) can be obtained using FFT (Fast Fourier Transform) or a filter.

<Third Modification>
In the second modification, frequency components from 0.2 to 0.5 Hz are extracted from ΔUc (xz, t) and ΔVc (xz, t). Instead, U (x) and V (x ), Only frequency components from 0.2 to 0.5 Hz in each of U (x) and V (x) may be used. In this case, in the above description, instead of U (x), the magnitude of the frequency component from 0.2 to 0.5 Hz included therein is 0. 0 included in V (x). Frequency component magnitudes from 2 to 0.5 Hz are used to determine ΔU (xz, t), ΔV (xz, t), ΔU (xdoor, t), ΔV (xdoor, t). In the present modification, as in the second modification, the accuracy of determining the presence or absence of a person in the garage 500 is improved.

  As mentioned above, although the moving body detection apparatus 1 was demonstrated in detail, above-described description is an illustration in all the phases, Comprising: This invention is not limited to it. The various modifications described above can be applied in combination as long as they do not contradict each other. And it is understood that the countless modification which is not illustrated can be assumed without deviating from the scope of the present invention.

DESCRIPTION OF SYMBOLS 1 Moving body detection apparatus 10 Antenna 17 Generation | occurrence | production part 111 Moving body determination part VT Transmission wave VR Reflected wave

Claims (6)

A moving object detection device for determining the presence or absence of a moving object to be detected,
A signal generator for generating a transmission wave;
An antenna for transmitting the transmission wave;
Based on a composite wave of the transmission wave and a reflected wave received by the antenna and reflected by a plurality of reflectors including the moving object, the distance from the moving object detection device is a variable, and the value of the variable A generating unit that generates a determination function that is a complex signal having a variable amplitude and phase;
A determination unit that determines the presence or absence of the moving object based on a time change of a first complex plane vector that represents a value of the determination function when the variable is a target distance;
The determination function is a composite signal of a plurality of individual complex signals corresponding to the plurality of reflectors, respectively.
Each of the plurality of individual complex signals changes according to a difference distance between the variable and a distance to the reflector according to the individual complex signal,
The determination unit calculates a difference vector between a second complex plane vector that represents a time change of the first complex plane vector and a third complex plane vector that represents the influence of the motion of the non-detection target included in the time change. A moving object detection device that determines and determines the presence or absence of the moving object based on the difference vector. The moving object detection device according to claim 1,
If the distance to the reflector according to the individual complex signal is constant, the amplitude of the individual complex signal tends to decrease as the absolute value of the difference distance between the variable and the distance increases.
The determination unit obtains a time change of the first complex plane vector representing a value of the determination function when the variable is the target distance for each of a plurality of target distances within a determination range,
The determination unit obtains the difference vector corresponding to each of the plurality of target distances based on a time change of the first complex plane vector obtained for each of the plurality of target distances, and determines the obtained difference vector. A moving object detection device that determines the presence or absence of the moving object within the determination range based on The moving object detection device according to any one of claims 1 and 2,
The determination unit obtains a time change of a fourth complex plane vector representing a value of the determination function when the variable is a distance to the non-detection target, and a time change of the first complex plane vector. Then, the moving body detection device that obtains the third complex plane vector based on the obtained temporal change of the first and fourth complex plane vectors. It is a moving body detection apparatus as described in any one of Claim 1 thru | or 3, Comprising:
The determination unit obtains a time change of the first complex plane vector by obtaining a time change of the real axis coordinate of the first complex plane vector and a time change of the imaginary axis coordinate of the first complex plane vector. ,
The determination unit sets a time change of a real axis coordinate of the first complex plane vector as a real axis coordinate of the second complex plane vector, and a time change of an imaginary axis coordinate of the first complex plane vector as the second complex plane. As an imaginary axis coordinate of the vector, a difference between a real axis coordinate of the second complex plane vector and a real axis coordinate of the third complex plane vector, an imaginary axis coordinate of the second complex plane vector, and the third complex plane vector The moving object detection apparatus which calculates | requires the said difference vector by calculating | requiring the difference with an imaginary axis coordinate. It is a moving body detection apparatus of Claim 4, Comprising:
The determination unit extracts a frequency component corresponding to the motion of the moving object from each of a real axis coordinate and an imaginary axis coordinate of the difference vector, and determines the presence or absence of the moving object based on the extracted frequency component Detection device. It is a moving body detection apparatus of Claim 4, Comprising:
The determination unit uses only the frequency component corresponding to the motion of the moving object in each of the real axis coordinate and the imaginary axis coordinate of the first complex plane vector when determining the presence or absence of the moving object. apparatus.

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