Observation target detection device and observation target detection method

Abstract

The present invention achieves an observation object detection device and an observation object detection method that make it possible to appropriately distinguish between an observation object and a non-observation object. The present invention comprises: a radar (11) that emits radio waves (transmitted waves (Tx)) into an observation range and identifies the position of a reflection point within the observation range on the basis of reflected waves (Rx) of the radio waves; a first correlation degree calculation unit (12) that calculates a first correlation degree (Cor1(m)) indicating the level of correlation between a time change of at least one of the amplitude, intensity, and power of a signal at the reflection point and a time change of phase; a first determination unit (13) that selects a reflection point having a first correlation degree (Cor1(m)) equal to or greater than a prescribed value; a second correlation degree calculation unit (14) that calculates a second correlation (Cor2(n1, n2)) indicating the level of correlation between a time change of at least one of the amplitude, intensity, power, and phase between signals at two reflection points if the number of reflection points selected by the first determination unit (13) is three or more; and a second determination unit (15) that determines reflection points having a second correlation degree (Cor2(n1, n2)) equal to or greater than a prescribed value as non-observation object reflection points, and determines reflection points other than the non-observation object reflection points as observation object reflection points.

Description

Technical Field

[0001] The present invention relates to an observation target detection device and an observation target detection method.

Background Art

[0002] The introduction of a system that detects a human body using radar (RADAR: RAdio Detection And Ranging) and acquires biological information based on the body surface displacement of the human body is underway. In a radar system, in order to identify a target by analyzing the reflected wave of the radio wave radiated from an antenna, it is necessary to improve the analysis accuracy of the reflected wave and the identification accuracy of the target.

[0003] In Patent Document 1, a beat signal between transmission and reception signals of an FMCW (Frequency Modulated Continuous Wave) radar is acquired, a plurality of time series data for transmission signals having a plurality of discrete frequencies among the sweep frequencies are extracted, and based on the period of the median value of the intervals between the peaks or bottoms of the time series data having the maximum amplitude among the plurality of time series data, an activity amount measuring device, an activity amount measuring system, an activity amount measuring program, and an activity amount measuring method for measuring the respiration rate of a human or animal are disclosed.

[0004] Further, in Patent Document 2, in a configuration for detecting a target using a Doppler radar, by correcting the Doppler speed based on the reflected wave component (ground clutter) from the ground existing in the received signal, even if the antenna fluctuates due to wind or the like and only the apparent Doppler frequency of the ground clutter and the target changes, an observation target detection device or an observation target detection method capable of detecting a target signal is disclosed.

[0005] Furthermore, Patent Document 3 discloses an interferometric vibration observation device, vibration observation program, recording medium, vibration observation method, and vibration observation system that receive reflected waves from an observation target with a receiving antenna mounted on a platform that vibrates or shakes, such as a helicopter, perform vibration analysis of a fixed point determined from an image generated from observation data representing the vibration of the observation target or a specific part, and remove the vibration of the fixed point from the observation data.

[0006] Furthermore, Non-Patent Document 1 discloses a method for extracting vital signs using the correlation between the amplitude and phase of signals obtained from reflected waves of an FMCW radar.

[0007] Furthermore, Non-Patent Document 2 discloses a method for detecting vital signs that utilizes the autocorrelation of the time evolution of the phase of each reflected wave and the crosscorrelation of the Doppler components (Doppler velocities) between each reflected wave. [Prior art documents] [Patent Documents]

[0008] [Patent Document 1] Japanese Patent Publication No. 2022-040858 [Patent Document 2] Japanese Patent Publication No. 2006-214766 [Patent Document 3] International Publication No. 2016 / 027422 [Non-patent literature]

[0009] [Non-Patent Document 1] H. -I. Choi, H. Song, and H. -C. Shin, “Target Range Selection of FMCW Radar for Accurate Vital Information Extraction,” IEEE Access, vol.9, pp.1261, 2021. [Non-Patent Document 2] E. Cardillo, C. Li, and A. Caddemi, “Vital Sign Detection and Radar Self-Motion Cancellation Through Clutter Identification,” IEEE Transactions on Microwave Theory and Techniques, vol.69, no.3, pp.1932, 2021. [Overview of the project] [Problems that the invention aims to solve]

[0010] In vital signs sensors that acquire body surface displacement of a stationary human body as biological information, if the sensor itself vibrates periodically due to external disturbances, there is a possibility that reflections from stationary objects (hereinafter also referred to as "clutter") in the biological information acquisition environment may be misinterpreted as reflections from the human body. Furthermore, periodic displacements due to sensor vibration may be superimposed, potentially preventing the acquisition of highly accurate biological information.

[0011] The technology described in Patent Document 1 acquires the respiratory rate based on the period of the median interval between the peak or bottom of time-series data with the maximum amplitude. Therefore, if the periodic vibration of the sensor itself is relatively large compared to the displacement of the human body surface, it may be impossible to distinguish between reflections from the human body and clutter. Furthermore, it is difficult to suppress the effects of the periodic vibration of the sensor itself.

[0012] Furthermore, the technology described in Patent Document 2 detects target information in a radar device for detecting ground targets by correcting the Doppler velocity based on ground clutter, which is a reflected wave from the stationary ground surface, in response to changes in the apparent Doppler frequency of the received signal due to antenna shaking, etc. For this reason, it is difficult to apply it to vital sensors that acquire minute surface displacements of a stationary human body as biological information.

[0013] Furthermore, the technology described in Patent Document 3 requires determining a fixed point (a stationary point) from an image generated from observation data representing the vibration of the object being observed or a specific part. For this reason, it cannot be applied to situations where it is unknown whether the vibration is a reflection from the human body or clutter in the environment in which biological information is acquired.

[0014] Furthermore, the technology described in Non-Patent Document 1 selects range bins with a high correlation between amplitude and phase. In Non-Patent Document 1, if each range bin contains the vibration component of the sensor, the correlation between amplitude and phase becomes high even in range bins that do not contain vital signs such as respiration or heart rate, making it impossible to distinguish between reflections from the human body and clutter.

[0015] Furthermore, the technology described in Non-Patent Literature 2 identifies signals with high autocorrelation of phase time variation, i.e., signals with periodically changing phase, as reflections from the human body. When the cross-correlation of Doppler components between relative signals is high, it identifies them as clutter due to high correlation caused by radar self-motion effects (RSMs). Therefore, if RSMs have periodicity, there is a high possibility of misidentifying clutter as a reflection from the human body, or vice versa, making it difficult to distinguish between reflections from the human body and clutter.

[0016] This disclosure is made in view of the above, and aims to realize an observation target detection device and an observation target detection method that can appropriately distinguish between observed targets and non-observed targets. [Means for solving the problem]

[0017] An observation target detection device according to one aspect of the present disclosure includes: a radar that emits radio waves into an observation range and identifies the position of reflection points within the observation range based on the reflected waves of the radio waves; a first correlation calculation unit that calculates a first correlation degree indicating the degree of correlation between the time change of at least one of the amplitude, intensity, and power of the signal at the reflection point and the time change of the phase; a first determination unit that selects reflection points for which the first correlation degree is equal to or greater than a predetermined value; a second correlation calculation unit that, if there are three or more reflection points selected by the first determination unit, calculates a second correlation degree indicating the degree of correlation between the time change of at least one of the amplitude, intensity, power, and phase of the signals at two reflection points; and a second determination unit that determines each reflection point for which the second correlation degree is equal to or greater than a predetermined value as a non-observation target reflection point, and determines the reflection points excluding the non-observation target reflection points as observation target reflection points.

[0018] In this configuration, for each reflection point identified by radar, a first correlation is calculated that indicates the degree of correlation between the time variation of at least one of the amplitude, intensity, or power of the signal at each reflection point and the time variation of the phase. Reflections with a calculated first correlation of at least one value above a predetermined threshold are selected, thereby selecting reflection points that contain periodic fluctuation components that are relatively large compared to random noise components. Then, a second correlation is calculated that indicates the degree of correlation between the time variation of at least one of the amplitude, intensity, power, or phase of the signals at each selected reflection point. Reflections with a second correlation of at least one value above a predetermined threshold are designated as non-observed reflection points, and the reflection points excluding the non-observed reflection points are determined to be observed reflection points. This allows for appropriate distinction between observed reflection points and non-observed reflection points that do not include displacement at the observed reflection points.

[0019] The method for detecting an observation target according to one aspect of the present disclosure includes: a first step of emitting radio waves within the observation range of a radar and identifying the positions of reflection points within the observation range based on the reflected waves of the radio waves; a second step of calculating a first correlation degree indicating the height of the correlation between at least one of the amplitude, intensity, and power of the signal at the reflection point and the temporal change in phase; a third step of selecting reflection points for which the first correlation degree is greater than or equal to a predetermined value; a fourth step of calculating a second correlation degree indicating the height of the correlation between at least one of the amplitude, intensity, power, and phase of the signals at two reflection points when there are three or more reflection points selected in the third step; and a fifth step of determining each reflection point for which the second correlation degree is greater than or equal to a predetermined value as a non-observation target reflection point and determining the reflection points excluding the non-observation target reflection points as observation target reflection points.

[0020] In this configuration, in the position identification process (first step), the positions of the reflection points within the observation range 2 of the radar are identified. For each reflection point identified in the position identification process, the first correlation degree calculation process (second step) is executed to calculate a first correlation degree indicating the height of the correlation between at least one of the amplitude, intensity, and power of the signal at each reflection point and the temporal change in phase. The first determination process (third step) is executed to select reflection points for which the first correlation degree is greater than or equal to a predetermined threshold, thereby selecting reflection points including relatively large periodic variation components compared to random noise components. Then, the second correlation degree calculation process (fourth step) is executed to calculate a second correlation degree indicating the height of the correlation between the temporal changes in amplitude, intensity, power, and phase of the signals at the reflection points selected in the first determination process. The second determination process (fifth step) is executed to determine each reflection point for which the second correlation degree calculated in the second correlation degree calculation process is greater than or equal to a predetermined threshold as a non-observation target reflection point and determine the reflection points excluding the non-observation target reflection points as observation target reflection points. Thereby, it is possible to appropriately discriminate between the observation target reflection points and the non-observation target reflection points that do not include the displacement at the observation target reflection points.

Advantages of the Invention

[0021] According to the present disclosure, it is possible to realize an observation target detection device and an observation target detection method that can appropriately discriminate between an observation target and a non-observation target.

Brief Description of the Drawings

[0022] [Figure 1] FIG. 1 is a block diagram showing a schematic configuration of an observation target detection device according to an embodiment. [Figure 2] FIG. 2 is a conceptual diagram showing the positions of reflection points within the observation range of the observation target detection device according to an embodiment. [Figure 3A] FIG. 3A is a first diagram showing an example of the temporal change in the amplitude of a signal at a reflection point. [Figure 3B] FIG. 3B is a first diagram showing an example of the temporal change in the phase of a signal at a reflection point. [Figure 4A] FIG. 4A is a second diagram showing an example of the temporal change in the amplitude of a signal at a reflection point. [Figure 4B] FIG. 4B is a second diagram showing an example of the temporal change in the phase of a signal at a reflection point. [Figure 5A] FIG. 5A is a first diagram showing an example of the temporal change in the phase of a signal when the reflection point is a human body. [Figure 5B] FIG. 5B is a second diagram showing an example of the temporal change in the phase of a signal when the reflection point is a human body. [Figure 5C] FIG. 5C is a diagram showing an example of the temporal change in the phase of a signal when the reflection point is a stationary object. [Figure 6A] FIG. 6A is a first diagram showing an example of the temporal change in the amplitude of a signal when the reflection point is a human body. [Figure 6B] FIG. 6B is a second diagram showing an example of the temporal change in the amplitude of a signal when the reflection point is a human body. [Figure 6C] FIG. 6C is a first diagram showing an example of the temporal change in the amplitude of a signal when the reflection point is a stationary object. [Figure 6D] FIG. 6D is a second diagram showing an example of the temporal change in the amplitude of a signal when the reflection point is a stationary object. [Figure 7]Figure 7 is a flowchart showing an example of the object detection process by the object detection device according to this embodiment. [Figure 8] Figure 8 is a flowchart showing an example of the first correlation calculation process (second step). [Figure 9] Figure 9 is a flowchart showing an example of the first decision process (third step). [Figure 10] Figure 10 is a flowchart showing an example of the second correlation calculation process (fourth step). [Figure 11] Figure 11 is a flowchart showing an example of the second decision process (fifth step). [Figure 12] Figure 12 is a flowchart showing an example of the displacement calculation process (step 6). [Figure 13] Figure 13 is a subflowchart showing an example of the first step in the displacement calculation process (step 6). [Figure 14] Figure 14 is a subflowchart showing an example of the second step of the displacement calculation process (step 6). [Figure 15] Figure 15 is a flowchart showing an example of the disturbance removal process (step 7). [Modes for carrying out the invention]

[0023] The following describes in detail, with reference to the drawings, an observation target detection device and an observation target detection method according to an embodiment. However, this disclosure is not limited by this embodiment.

[0024] Figure 1 is a block diagram illustrating the schematic configuration of an observation target detection device according to an embodiment. The observation target detection device 1 according to this embodiment includes a radar 11, a first correlation calculation unit 12, a first determination unit 13, a second correlation calculation unit 14, a second determination unit 15, a displacement calculation unit 16, and a disturbance removal unit 17.

[0025] The radar 11 emits, for example, a millimeter-wave or microwave-wave radio wave (transmitted wave Tx) into the observation range where the object to be observed should be detected in the object detection device according to the embodiment, and receives the radio wave (reflected wave Rx) reflected at an unknown reflection point to determine the position of the reflection point within the observation range. Examples of radar 11 include FMCW (Frequency Modulated Continuous Wave) radar, Doppler radar, pulse radar, etc. In this disclosure, the radar 11 only needs to be configured to measure at least the distance and angle (azimuth) to the reflection point.

[0026] Radar 11 performs AD conversion, filtering, and various FFT processing on the received reflected wave Rx to determine the position of the reflection point within the observation range. This disclosure is not limited by the specific processing performed by radar 11.

[0027] Figure 2 is a conceptual diagram showing the location of reflection points within the observation range of the observation target detection device according to the embodiment. In Figure 2, a, b, c, d, and e indicate reflection points identified by the radar 11 within the observation range 2 of the observation target detection device 1.

[0028] In this disclosure, the observation target detection device 1 is exemplified by a vital sensor that acquires body surface displacement of a human body as biological information and detects vital signs such as heart rate, heart rate variability, respiratory rate, and respiratory depth. In this case, the reflection points a, b, c, d, and e identified within the observation range 2 of the observation target detection device 1 include not only the human body that the observation target detection device 1 is observing, but also stationary objects present in the biological information acquisition environment.

[0029] Stationary objects present in the vital signs acquisition environment include, for example, seats and dashboards if the biometric information acquisition environment is a moving object such as a car. Alternatively, if the biometric information acquisition environment is a hospital examination room or patient room, walls and beds may be considered. To improve the accuracy of vital signs detection, it is necessary to appropriately determine whether the reflective point identified by the radar 11 is a human body or not.

[0030] Figure 3A is Figure 1 showing an example of the time variation of the signal amplitude at the reflection point. Figure 3B is Figure 1 showing an example of the time variation of the signal phase at the reflection point. Figures 3A and 3B show examples in which a stationary object within observation range 2 is identified as the reflection point.

[0031] Figure 4A is Figure 2, showing an example of the time variation of the signal amplitude at the reflection point. Figure 4B is Figure 2, showing an example of the time variation of the signal phase at the reflection point. Figures 4A and 4B show examples where a stationary human body is identified as the reflection point.

[0032] Noise components are superimposed on the signal corresponding to each reflection point. Therefore, even if the reflection point is a stationary object, the noise components appear as time changes in the amplitude and phase of the signal, as shown in Figures 3A and 3B. These noise components are so-called random noise, and there is no correlation between the noise components that appear as time changes in amplitude and the noise components that appear as time changes in phase.

[0033] In contrast, when the reflection point is a stationary human body, in addition to random noise components, approximately periodic displacements of the body surface, such as respiration and heartbeat, are superimposed. These body surface displacements are relatively large compared to the random noise components and become dominant in the temporal changes of amplitude and phase. Therefore, when the reflection point is a stationary human body, the correlation between the temporal changes in amplitude and the temporal changes in phase becomes high, as shown in Figures 4A and 4B.

[0034] In this disclosure, among the reflection points identified by the radar 11, reflection points with a high correlation between the time variation of the signal amplitude and the time variation of the phase are selected. This makes it possible to exclude reflection points that do not involve the displacement of the human body surface.

[0035] Specifically, the first correlation calculation unit 12 uses equation (1) below to calculate the first correlation degree Cor1(m), which indicates the degree of correlation between the time change of the signal amplitude A(m) and the time change of the phase φ(m) at each reflection point m (in the example shown in Figure 2, reflection points a, b, c, d, e; in this case, the total number of reflection points M is 5).

[0036]

number

[0037] In equation (1) above, σA(m) represents the standard deviation of the amplitude A(m), and σφ(m) represents the standard deviation of the phase φ(m). This yields the normalized first correlation, Cor1(m).

[0038] Then, the first determination unit 13 selects the reflection point m (in the example shown in Figure 2, any of reflection points a, b, c, d, or e) as reflection point n if the first correlation coefficient Cor1(m) calculated by the first correlation coefficient calculation unit 12 is equal to or greater than a predetermined threshold Cor1th (for example, 0.9) (Cor1(m) ≥ Cor1th). (The total number of selected reflection points n is N.) As a result, reflection points that do not include displacement of the human body surface are excluded from selection. The threshold Cor1th for the first correlation coefficient Cor1(m) is preferably around Cor1th = 0.99, for example, if the ratio of the noise component to the signal is 1 / 100 or less.

[0039] In addition, while equation (1) above shows an example of calculating the first correlation degree Cor1(m) between the time change of the signal amplitude A(m) and the time change of the phase φ(m) at each reflection point m, it is also possible to calculate the first correlation degree using the intensity or power of the signal superimposed by the displacement of the human body surface instead of the amplitude A.

[0040] In this case, if the observation target detection device 1 according to the embodiment is periodically oscillating, the periodic oscillating of the observation target detection device 1 will be superimposed on the signal corresponding to each reflection point.

[0041] Figure 5A is the first figure showing an example of the time evolution of the signal phase when the reflection point is a human body. Figure 5B is the second figure showing an example of the time evolution of the signal phase when the reflection point is a human body. Figure 5C is a figure showing an example of the time evolution of the signal phase when the reflection point is a stationary object.

[0042] Figures 5A, 5B, and 5C show examples of simulations where the oscillation of the observation target detection device 1 is set to a 1 Hz sine wave, and the displacement of the human body surface is set to a 0.2 Hz sine wave. Figures 5A, 5B, and 5C show examples of the time evolution of the signal phase at each reflection point; the same applies to the time evolution of the signal amplitude at each reflection point.

[0043] When the reflection point is a human body and the observation target detection device 1 is not moving, a 0.2 Hz sine wave, which simulates body surface displacement, is superimposed on the time change in the phase (or amplitude) of the signal at the reflection point, as shown in Figure 5A. On the other hand, when the observation target detection device 1 is moving at 1 Hz, in addition to the 0.2 Hz sine wave that simulates body surface displacement, a 1 Hz sine wave, which simulates the movement of the observation target detection device 1, is superimposed on the time change in the phase (or amplitude) of the signal at the reflection point, as shown in Figure 5B.

[0044] Furthermore, if the periodic oscillation of the observation target detection device 1 is relatively large compared to random noise components, even if the reflection point is a stationary object, the periodic oscillation of the observation target detection device 1 will dominate the time change of phase (and amplitude), as shown in Figure 5C. As a result, the correlation between the time change of amplitude and the time change of phase will increase, and the first correlation calculated by the first correlation calculation unit 12 may exceed the threshold, potentially leading to selection by the first determination unit 13.

[0045] Figure 6A is the first figure showing an example of the time evolution of the signal amplitude when the reflection point is a human body. Figure 6B is the second figure showing an example of the time evolution of the signal amplitude when the reflection point is a human body. Figure 6C is the first figure showing an example of the time evolution of the signal amplitude when the reflection point is a stationary object. Figure 6D is the second figure showing an example of the time evolution of the signal amplitude when the reflection point is a stationary object.

[0046] In Figures 6A, 6B, 6C, and 6D, the oscillation of the object detection device 1 is assumed to be a 1 Hz sine wave. Figure 6A also shows an example of simulation where the surface displacement of human body A is assumed to be a 0.2 Hz sine wave, and Figure 6B shows an example where the surface displacement of human body B is assumed to be a 0.25 Hz sine wave. Figure 6C shows an example of simulation of a stationary object C, and Figure 6D shows an example of simulation of a stationary object D. Note that while Figures 6A, 6B, 6C, and 6D show examples of the time evolution of the signal amplitude at each reflection point, the same applies to the time evolution of the signal phase at each reflection point.

[0047] The correlation of the time evolution of amplitude (or phase) between signals is low when comparing a human body (human body A or human body B) with a stationary object (stationary object C or stationary object D), while the correlation of the time evolution of amplitude (or phase) between signals is high when comparing stationary objects (between stationary object C and stationary object D). On the other hand, when comparing human bodies (between human body A and human body B), the correlation of the time evolution of amplitude (or phase) between signals is low because the frequencies of body surface displacement are different (the frequency of body surface displacement for human body A is 0.2 Hz, and the frequency of body surface displacement for human body B is 0.25 Hz).

[0048] Therefore, in this disclosure, among the reflection points selected by the first determination unit 13, reflection points with a high correlation in the time change of amplitude (or phase) between each signal are determined to be stationary objects that are not observed by the observation target detection device 1 according to the embodiment. As a result, the reflection points other than those determined to be stationary objects can be determined to be human bodies that are observed by the observation target detection device 1.

[0049] Specifically, the second correlation calculation unit 14 calculates a second correlation coefficient Cor2(n1,n2) using the following equation (2), which indicates the degree of correlation between the time change of the signal amplitude A(n1) at the reflection point n1 (n1 is an integer from 1 to N) selected by the first determination unit 13 and the time change of the signal amplitude A(n2) at the reflection point n2 (n2 is an integer from 1 to N excluding n1).

[0050]

number

[0051] In equation (2) above, σA(n1) represents the standard deviation of the signal amplitude A(n1) corresponding to reflection point n1, and σA(n2) represents the standard deviation of the signal amplitude A(n2) corresponding to reflection point n2. This yields the normalized second correlation, Cor2(n1,n2).

[0052] Alternatively, the second correlation calculation unit 14 calculates a second correlation coefficient Cor2(n1,n2) using the following equation (3), which indicates the degree of correlation between the time change of the phase φ(n1) of the signal at the first determination unit 13 selected by the first determination unit 13 (n1 is an integer from 1 to N) and the time change of the phase φ(n2) of the signal at the second reflection point n2 (n2 is an integer from 1 to N excluding n1).

[0053]

number

[0054] In equation (3) above, σφ(n1) represents the standard deviation of the phase φ(n1) of the signal corresponding to reflection point n1, and σφ(n2) represents the standard deviation of the phase φ(n2) of the signal corresponding to reflection point n2. This yields the normalized second correlation, Cor2(n1,n2).

[0055] The second determination unit 15 determines that reflection points n1 and n2 are unobserved reflection points q if the second correlation coefficient Cor2(n1,n2) calculated by the second correlation coefficient calculation unit 14 is equal to or greater than a predetermined threshold Cor2th (for example, 0.9) (Cor2(n1,n2)≧Cor2th). After the threshold determination of all second correlation coefficients calculated by the second correlation coefficient calculation unit 14, the reflection points excluding the unobserved reflection points q are determined to be observed reflection points r (if the total number of unobserved reflection points q is Q, the total number of observed reflection points r is R (R=NQ)). The threshold Cor2th for the second correlation coefficient Cor2(n1,n2) is also preferably around 0.99, similar to the threshold Cor1th for the first correlation coefficient Cor1(m).

[0056] In equation (2) above, the second correlation degree Cor2(n1,n2) is calculated between the time change of the amplitude A(n1) of the signal at reflection point n1 and the time change of the amplitude A(n2) of the signal at reflection point n2. In equation (3) above, an example is shown in which the second correlation degree Cor2(n1,n2) is calculated between the time change of the phase φ(n1) of the signal at reflection point n1 and the time change of the phase φ(n2) of the signal at reflection point n2. However, instead of amplitude A and phase φ, the second correlation degree may also be calculated using the intensity or power of the signal superimposed by the displacement of the human body surface and the periodic oscillation of the observation target detection device 1. Alternatively, if the radar 11 is an FMCW radar, it is also possible to calculate the second correlation degree using the complex signal corresponding to each reflection point.

[0057] The displacement calculation unit 16 calculates the displacements of all observed reflection points r and unobserved reflection points q (displacement d1(r) of observed reflection points, displacement d2(q) of unobserved reflection points).

[0058] The displacement d of each reflection point can be calculated from the phase φ of the signal at each reflection point. The phase φ of the signal at each reflection point is given by equation (4) below, where λ is the center frequency of the radio waves used by the radar 11 (transmitted wave Tx, reflected wave Rx).

[0059] φ = 4π × d / λ···(4)

[0060] As described above, if the observation target detection device 1 according to the embodiment is periodically shaken, the periodic shaking of the observation target detection device 1 is superimposed on the phase of the signal corresponding to each reflection point. Therefore, in order to obtain the body surface displacement of the human body that has been determined to be the observation target reflection point r by the second determination unit 15, it is necessary to remove the displacement component caused by the shaking of the observation target detection device 1 from the displacement at the observation target reflection point r.

[0061] Here, if the periodic oscillation of the object detection device 1 is relatively large compared to the random noise component, even if the reflection point is a stationary object, the periodic oscillation of the object detection device 1 will dominate the time change of the phase, as described above (see Figure 5C). For this reason, the displacement calculated from the phase of the stationary object determined to be a non-observed reflection point q by the second determination unit 15 will be dominated by the displacement component caused by the periodic oscillation of the object detection device 1.

[0062] Therefore, in this disclosure, the displacement component of a stationary object is removed from the displacement at the observed reflection point r. This makes it possible to obtain highly accurate biological information (displacement of the human body surface) with the displacement component caused by the periodic oscillation of the observed object detection device 1 suppressed, thereby improving the accuracy of vital sign detection.

[0063] Specifically, the disturbance removal unit 17 extracts the displacement corresponding to the non-observed reflection point where the signal amplitude is maximum among the reflection points determined by the second determination unit 15 as the non-observed reflection point displacement d2max, and calculates the human body surface displacement Dhb(r) by removing the displacement component Δd (∝d2max) that is proportional to the non-observed reflection point displacement d2max from the observed reflection point displacement d1(r) calculated by the displacement calculation unit 16 (Dhb(r)=d1(r)-Δd). In this disclosure, an example is described in which the displacement corresponding to the non-observed reflection point where the signal amplitude is maximum among the reflection points determined by the second determination unit 15 as the non-observed reflection point displacement d2max, but it is also possible to extract the displacement corresponding to the non-observed reflection point where the signal intensity or power is maximum instead of amplitude as the non-observed reflection point displacement d2max.

[0064] The following describes a specific example of the object detection process in the object detection device 1 according to this embodiment. Figure 7 is a flowchart showing an example of the object detection process by the object detection device according to this embodiment.

[0065] The observation target detection device 1 according to this embodiment first performs a process to determine the location of reflection points in the observation range 2 (step S001, first step). Specifically, the radar 11 emits a transmitted wave Tx in the observation range 2, receives a reflected wave Rx reflected at an unknown reflection point, and determines the location of the reflection points within the observation range 2 (for example, each of the reflection points a, b, c, d, e shown in Figure 2).

[0066] Returning to the observation target detection process shown in Figure 7, the observation target detection device 1 then numbers each reflection point identified in the position identification process by the radar 11 (step S001, first step) with a number m from 1 to M (where M is the total number of identified reflection points), and performs a first correlation calculation process (step S002, second step) to calculate a first correlation degree that indicates the degree of correlation between the time change of the signal amplitude and the time change of the phase at each reflection point m. Figure 8 is a flowchart showing an example of the first correlation calculation process (second step).

[0067] In the first correlation calculation process (second step), the first correlation calculation unit 12 first initializes the number m of the reflection point identified by the radar 11. Specifically, the first correlation calculation unit 12 sets the number m to "0" (m=0, step S201). Subsequently, the first correlation calculation unit 12 increments the number m (m=m+1, step S202) and calculates the first correlation Cor1(m) using the above equation (1) (step S203).

[0068] After calculating the first correlation coefficient Cor1(m) (step S203), the first correlation coefficient calculation unit 12 determines whether the number m is M or not (step S204). If the number m is not M (step S204; No), in other words, if there are reflection points for which the first correlation coefficient calculation process has not been performed, the process from step S202 onwards is repeated. If the number m is M (m=M, step S204; Yes), in other words, after performing the first correlation coefficient calculation process at all reflection points identified by the radar 11, the process returns to the observation target detection process shown in Figure 7. The first correlation coefficient calculation process (second step) calculates the first correlation coefficient for all reflection points identified by the radar 11.

[0069] Return to the observation target detection process shown in FIG. 7. Subsequently, the observation target detection device 1 executes a first determination process (step S003, third step) of selecting a reflection point whose first correlation degree calculated by the first correlation degree calculation unit 12 is equal to or greater than a predetermined threshold. FIG. 9 is a flowchart showing an example of the first determination process (third step).

[0070] In the first determination process (third step), the first determination unit 13 first initializes the number m of the reflection point specified by the radar 11 and the number n up to the total number N (unknown) of the reflection points selected in the first determination process (third step). Specifically, the first determination unit 13 sets the number m and the number n to "0" (m = 0, n = 0, step S301). Subsequently, the first determination unit 13 increments the number m (m = m + 1, step S302) and determines whether the first correlation degree Cor1(m) calculated by the first correlation degree calculation unit 12 is equal to or greater than a predetermined threshold Cor1th (Cor1(m) ≧ Cor1th, step S303). If the first correlation degree Cor1(m) is less than the threshold Cor1th (Cor1(m) < Cor1th, step S303; No), the process proceeds to the process of step S306.

[0071] If the first correlation degree Cor1(m) is equal to or greater than the threshold Cor1th (Cor1(m) ≧ Cor1th, step S303; Yes), the first determination unit 13 increments the number n (n = n + 1, step S304), selects the reflection point m as the reflection point n (step S305), and proceeds to the process of step S306.

[0072] Proceed to the process of step S306, and the first determination unit 13 determines whether the number m is M (step S306).

[0073] If the number m is not M (step S306; No), in other words, if there are reflection points for which the threshold determination process for the first correlation has not been performed, the processes from step S302 onwards are repeated. If the number m is M (m=M, step S306; Yes), in other words, if the threshold determination process for the first correlation has been performed for all reflection points identified by the radar 11, the process returns to the observation target detection process shown in Figure 7, with the number n being the total number of reflection points N selected in the first determination process (third step) (N=n, step S307). The first determination process (third step) performs the threshold determination process for the first correlation at all reflection points identified by the radar 11, and reflection points n whose first correlation is greater than or equal to the threshold Cor1th are selected.

[0074] Returning to the observation target detection process shown in Figure 7, the observation target detection device 1 determines whether the total number N of reflection points n selected in the first determination process (third step) is 3 or greater (N≧3, step S031). If N≧3 (step S031; Yes), the observation target detection device 1 then performs a second correlation calculation process (step S004, fourth step) to calculate a second correlation, which indicates the degree of correlation of the time changes in amplitude (or phase) between signals of the reflection points selected by the first determination unit 13. Figure 10 is a flowchart of an example of the second correlation calculation process (fourth step).

[0075] In the second correlation calculation process (fourth step), the second correlation calculation unit 14 first initializes the numbers n1 (n1 is an integer from 1 to N) and n2 (n2 is an integer from 1 to N excluding n1) corresponding to the number n of the reflection point selected in the first determination process (third step), and also initializes the numbers p up to the total number P (=N × (N-1) / 2) of the second correlation calculated in the second correlation calculation process (fourth step). Specifically, the second correlation calculation unit 14 sets the number n1 to "0", the number n2 to "1", and the number p to "0" (n1=0, n2=1, p=0, step S401). Next, the second correlation calculation unit 14 increments the number n1 (n1=n1+1, step S402), and then increments the number n2 (n2=n2+1, step S403), and calculates the second correlation Cor2(n1,n2) using the above formula (2) or (3) (step S404).

[0076] After calculating the second correlation coefficient Cor2(n1,n2) (step S404), the second correlation coefficient calculation unit 14 increments the number p (p=p+1, step S405), determines whether the number n2 is N or not (step S406), and if the number n2 is not N (step S406; No), it repeatedly executes the process from step S403 onwards. If the number n2 is N (step S406; Yes), the second correlation coefficient calculation unit 14 sets the value obtained by incrementing the number n1 as the number n2 (step S407).

[0077] Next, the second correlation calculation unit 14 determines whether or not the number n1 is N-1 (step S408). If the number n1 is not N-1 (step S408; No), the process from step S402 onwards is repeated. If the number n1 is N-1 (step S408; Yes), the number p is set as the total number P of the second correlations calculated in the second correlation calculation process (step 4) (P=p, step S409), and the process returns to the observation target detection process shown in Figure 7. The second correlation calculation process (step 4) calculates the second correlation between each signal of all reflection points selected by the first determination unit 13.

[0078] Return to the observation target detection process shown in FIG. 7. Subsequently, the observation target detection device 1 executes a second determination process (step S005, fifth step) in which each reflection point whose second correlation degree calculated by the second correlation degree calculation unit 14 is equal to or greater than a predetermined threshold is set as a non-observation target reflection point, and the reflection points excluding the non-observation target reflection points are determined as observation target reflection points. FIG. 11 is a flowchart showing an example of the second determination process (fifth step).

[0079] In the second determination process (fifth step), the second determination unit 15 first initializes the number p of the second correlation degree calculated by the second correlation degree calculation unit 14. Specifically, the second determination unit 15 sets the number p to "0" (p = 0, step S501). Subsequently, the second determination unit 15 increments the number p (p = p + 1, step S502), and determines whether the second correlation degree Cor2(n1, n2) calculated by the second correlation degree calculation unit 14 is equal to or greater than a predetermined threshold Cor2th (Cor2(n1, n2) ≧ Cor2th, step S503). If the second correlation degree Cor2(n1, n2) is less than the threshold Cor2th (Cor2(n1, n2) < Cor2th, step S503; No), the process proceeds to the process of step S505.

[0080] If the second correlation degree Cor2(n1, n2) is equal to or greater than the threshold Cor2th (Cor2(n1, n2) ≧ Cor2th, step S503; Yes), the reflection points n1 and n2 are determined as non-observation target reflection points (step S504), and the process proceeds to the process of step S505.

[0081] When the process moves to step S505, the second determination unit 15 determines whether the number p is P or not (p=P, step S505). If the number p is not P (step S505; No), the process from step S502 onwards is repeatedly executed. If the number p is P (step S505; Yes), the second determination unit 15 determines the reflection points that were not determined to be non-observable reflection points in step S504 as observationable reflection points (step S506), and returns to the observation target detection process shown in Figure 7. Through the second determination process (fifth step), all reflection points selected by the first determination unit 13 are determined to be either non-observable reflection points or observationable reflection points.

[0082] Returning to the observation target detection process shown in Figure 7, the observation target detection device 1 assigns a number q from 1 to Q (where Q is the total number of reflection points determined to be non-observation target reflection points) to each reflection point determined to be an observation target reflection point by the second determination unit 15 (step S005, fifth step), and similarly assigns a number r from 1 to R (where R is the total number of reflection points determined to be observation target reflection points) to each reflection point determined to be an observation target reflection point. Then, the observation target detection device 1 determines whether the total number Q of reflection points determined to be non-observation target reflection points is 2 or more (Q≧2, step S051). If Q ≥ 2 (Step S051; Yes), the observation target detection device 1 then performs a displacement calculation process (Step S006, 6th step) in which it calculates the displacement at each reflection point determined by the second determination unit 15 as an observation target reflection point, and the displacement corresponding to the reflection point with the maximum signal amplitude among the reflection points determined by the second determination unit 15 as a non-observation target reflection point displacement. Figure 12 is a flowchart showing an example of the displacement calculation process (6th step).

[0083] In the displacement calculation process (step 6), the displacement calculation unit 16 performs a first process (step S610) to calculate the displacement at each reflection point determined to be an observation target reflection point, and a second process (step S620) to calculate the displacement corresponding to the reflection point with the maximum signal amplitude among the reflection points determined to be non-observation target reflection points. Figure 13 is a subflowchart showing an example of the first process of the displacement calculation process (step 6). Figure 14 is a subflowchart showing an example of the second process of the displacement calculation process (step 6).

[0084] In the first step of the displacement calculation process (6th step) shown in Figure 13, the displacement calculation unit 16 first initializes the number r of the reflection point determined by the second determination unit 15 as the observation target reflection point. Specifically, the displacement calculation unit 16 sets the number r to "0" (r=0, step S611). Next, the displacement calculation unit 16 increments the number r (r=r+1, step S612) and calculates the displacement at the observation target reflection point r (observation target reflection point displacement d1(r)) using the above equation (4) (step S613).

[0085] After calculating the displacement d1(r) of the observed reflection point (step S613), the displacement calculation unit 16 determines whether the number r is R or not (step S614). If the number r is not R (step S614; No), the process from step S612 onwards is repeated. If the number r is R (step S614; Yes), the process proceeds to the second step of the displacement calculation process (6th step) shown in Figure 14. The displacements of all reflection points determined to be observed reflection points by the second determination unit 15 are calculated by the first step of the displacement calculation process (6th step) described above.

[0086] When the process moves to the second step of the displacement calculation process (6th step) shown in Figure 14, the displacement calculation unit 16 first initializes the number q of the reflection point determined by the second determination unit 15 as an unobserved reflection point, and the maximum value A2max of the amplitude A2(q) of the unobserved reflection point q among the unobserved reflection points q numbered 1 to Q. Specifically, the displacement calculation unit 16 sets the number q and the maximum value A2max to "0" (q=0, A2max=0, step S621).

[0087] Next, the displacement calculation unit 16 increments the number q (q=q+1, step S622) and determines whether the amplitude of the signal A2(q) at the unobserved reflection point q exceeds the maximum value A2max (A2(q)>A2max, step S623). If the amplitude of the signal A2(q) at the unobserved reflection point q is less than or equal to the maximum value A2max (A2(q)≦A2max, step S623; No), the process proceeds to step S625. If the amplitude of the signal A2(q) at the unobserved reflection point q exceeds the maximum value A2max (A2(q)>A2max, step S623; Yes), the displacement calculation unit 16 updates the amplitude of the signal A2(q) at the unobserved reflection point q to the maximum value A2max (A2max=A2(q), step S624).

[0088] After updating the signal amplitude A2(q) at the unobserved reflection point q to its maximum value A2max (step S624), the displacement calculation unit 16 determines whether the number q is Q or not (step S625). If the number q is not Q (step S625; No), the processing from step S622 onwards is repeated. If the number q is Q (step S625; Yes), the displacement calculation unit 16 uses equation (4) above to calculate the displacement d2max at the unobserved reflection point q, where the signal amplitude A2(q) was updated to its maximum value A2max in the processing of step S624 (step S626), and returns to the observation target detection processing shown in Figure 7. Through the second processing of the displacement calculation processing (6th step) described above, the displacement corresponding to the unobserved reflection point with the maximum signal amplitude among the reflection points determined to be unobserved reflection points by the second determination unit 15 is extracted as the unobserved reflection point displacement d2max.

[0089] Returning to the observation target detection process shown in Figure 7, the observation target detection device 1 then performs a disturbance removal process (step S007, 7th step) to generate the surface displacement of the human body by removing the displacement component of a stationary object from the displacement at the observation target reflection point calculated by the displacement calculation unit 16. Figure 15 is a flowchart showing an example of the disturbance removal process (7th step).

[0090] In the disturbance removal process (step 7), the disturbance removal unit 17 initializes the number r of the reflection point determined by the second determination unit 15 as the observation target reflection point. Specifically, the disturbance removal unit 17 sets the number r to "0" (r=0, step S701).

[0091] Next, the disturbance removal unit 17 increments the number r (r=r+1, step S702), and removes the displacement component Δd that is proportional to the observed reflection point displacement d2max extracted by the second process of the disturbance removal process (step 7) from the observed reflection point displacement d1(r) to generate the human body surface displacement Dhb(r) (step S703). Specifically, the disturbance removal unit 17 calculates the human body surface displacement Dhb(r) by subtracting the displacement component Δd that is proportional to the observed reflection point displacement d2max from the observed reflection point displacement d1(r).

[0092] After removing the displacement component Δd proportional to the observed reflection point displacement d2max from the observed reflection point displacement d1(r) (step S703), the disturbance removal unit 17 determines whether the number r is R or not (step S704). If the number r is not R (step S704; No), the process from step S702 onwards is repeated. If the number r is R (step S704; Yes), the process returns to the observed object detection process shown in Figure 7 and terminates the observed object detection process. Through the disturbance removal process described above (step 7), it is possible to obtain body surface displacements with the displacement component caused by the periodic oscillation of the observed object detection device 1 suppressed at all reflection points determined by the second determination unit 15 to be the human body, which is the object of observation of the observed object detection device 1.

[0093] Furthermore, if the total number N of reflection points n selected in the first determination process (third step) by the first determination unit 13 is 0 or 1, the second correlation calculation process (step S004, fourth step) by the subsequent second correlation calculation unit 14 cannot be executed. Also, if the total number N of reflection points n selected in the first determination process (third step) by the first determination unit 13 is 2, the second correlation calculation process (step S004, fourth step) by the subsequent second correlation calculation unit 14 calculates a single second correlation, Cor2(n1,n2). At this point, in the second determination process (step S005, fifth step) by the second determination unit 15 in a later stage, if both of the two reflection points n1 and n2 used to calculate the second correlation coefficient Cor2(n1,n2) are determined to be observation target reflection points r, in other words, if the two reflection points n1 and n2 used to calculate the second correlation coefficient Cor2(n1,n2) are not determined to be non-observation target reflection points q, then this can include both cases where both of these reflection points n1 and n2 are human bodies, and cases where one is a human body and the other is a stationary object. For this reason, if the total number N of reflection points n selected by the first determination process (third step) is less than 3 (N<3, step S031; No), in other words, if the total number N of reflection points n selected by the first determination process (third step) is 2 or less (N≦2), then the processes from the second correlation coefficient calculation process (step S004, fourth step) onward are canceled and the observation target detection process is terminated.

[0094] Furthermore, in the second determination process (5th step) by the second determination unit 15, if the total number Q of reflection points determined to be non-observed reflection points q is 0, in other words, if all the reflection points n selected in the first determination process (3rd step) by the first determination unit 13 are determined to be observed reflection points r, this may include the case where one of the R reflection points determined to be observed reflection points r is a stationary object. In this case, the calculation of the non-observed reflection point displacement d2(q) in the displacement calculation process (6th step) by the displacement calculation unit 16, and the extraction of the maximum value d2max of the non-observed reflection point displacement in the disturbance removal process (7th step) by the disturbance removal unit 17 cannot be performed, and the displacement component proportional to the maximum value d2max of the non-observed reflection point displacement cannot be removed from the observed reflection point displacement d1(r). Therefore, if the total number of reflection points Q determined to be non-observable reflection points q is less than 2 (Q<2, step S051; No), in other words, if all reflection points n are determined to be observable reflection points r (R=N), the processes from the displacement calculation process (step S006, 6th step) onward are canceled, and the observation target detection process is terminated.

[0095] According to the observation target detection process in the observation target detection device 1 and observation target detection method of this embodiment, in the position identification process by the radar 11 (step S001, first step), the position of the reflection point within the observation range 2 is identified. For each reflection point identified in the position identification process, the first correlation calculation process (step S002, second step) is performed by the first correlation calculation unit 12 to calculate a first correlation, which indicates the degree of correlation between the time change of at least one of the amplitude, intensity, and power of the signal at each reflection point and the time change of the phase. Then, the first determination process (step S003, third step) is performed by the first determination unit 13 to select reflection points for which the first correlation calculated in the first correlation calculation process (step S002, second step) by the first correlation calculation unit 12 is equal to or greater than a predetermined threshold. As a result, reflection points containing relatively large periodic fluctuation components (approximately periodic displacement of the human body surface such as respiration and heartbeat, or periodic oscillation of the observation target detection device 1) are selected compared to random noise components.

[0096] Furthermore, the second correlation calculation unit 14 performs a second correlation calculation process (step S004, fourth step) to calculate a second correlation, which indicates the degree of correlation of the correlation between at least one of the time changes of amplitude, intensity, power, and phase between the signals of each reflection point selected in the first determination process. Then, the second determination unit 15 performs a second determination process (step S005, fifth step) to determine that each reflection point whose second correlation calculated in the second correlation calculation process is equal to or greater than a predetermined threshold is a non-observed reflection point, and the reflection points excluding the non-observed reflection points are determined to be observed reflection points. As a result, among the reflection points selected in the first determination process, reflection points that do not contain the human body surface displacement component are determined to be non-observed reflection points, and reflection points that contain the human body surface displacement component are determined to be observed reflection points.

[0097] Therefore, the observation target detection process according to the embodiment makes it possible to appropriately distinguish between observation target reflection points that include surface displacement of the human body and non-observation target reflection points that are stationary objects that do not include surface displacement of the human body.

[0098] Furthermore, the displacement calculation unit 16 performs a displacement calculation process (step S006, sixth step) to calculate the displacement at each reflection point determined by the second determination unit 15 as an observation target reflection point, and the displacement corresponding to the reflection point with the maximum signal amplitude, intensity, or power among the reflection points determined by the second determination unit 15 as a non-observation target reflection point. The disturbance removal unit 17 then performs a disturbance removal process (step S007, seventh step) to remove the displacement component of the non-observation target reflection point determined to be a stationary object from the displacement at the observation target reflection point calculated by the displacement calculation unit 16. As a result, the displacement component caused by the periodic oscillation of the observation target detection device 1 (radar 11) is removed from the observation target reflection point displacement, which includes the displacement of the human body surface and the displacement component caused by the periodic oscillation of the observation target detection device 1 (radar 11), and highly accurate human body surface displacement can be obtained as biological information.

[0099] The embodiments described above are provided to facilitate understanding of this disclosure and are not intended to limit the invention. This disclosure may be modified or improved without departing from its spirit, and equivalents thereof are included.

[0100] This disclosure may take the following configuration, as described above, or alternatively.

[0101] (1) An observation target detection device according to one aspect of the present disclosure includes: a radar that emits radio waves into an observation range and identifies the position of reflection points within the observation range based on the reflected waves of the radio waves; a first correlation calculation unit that calculates a first correlation degree indicating the degree of correlation between the time change of at least one of the amplitude, intensity, and power of the signal at the reflection point and the time change of the phase; a first determination unit that selects reflection points for which the first correlation degree is equal to or greater than a predetermined value; a second correlation calculation unit that, if there are three or more reflection points selected by the first determination unit, calculates a second correlation degree indicating the degree of correlation between the time change of at least one of the amplitude, intensity, power, and phase of the signals at two reflection points; and a second determination unit that determines each reflection point for which the second correlation degree is equal to or greater than a predetermined value as a non-observation target reflection point, and determines the reflection points excluding the non-observation target reflection points as observation target reflection points.

[0102] In this configuration, for each reflection point identified by radar, a first correlation is calculated that indicates the degree of correlation between the time variation of at least one of the amplitude, intensity, or power of the signal at each reflection point and the time variation of the phase. Reflections with a calculated first correlation of at least one value above a predetermined threshold are selected, thereby selecting reflection points that contain periodic fluctuation components that are relatively large compared to random noise components. Then, a second correlation is calculated that indicates the degree of correlation between the time variation of at least one of the amplitude, intensity, power, or phase of the signals at each selected reflection point. Reflections with a second correlation of at least one value above a predetermined threshold are designated as non-observed reflection points, and the reflection points excluding the non-observed reflection points are determined to be observed reflection points. This allows for appropriate distinction between observed reflection points and non-observed reflection points that do not include displacement at the observed reflection points.

[0103] (2) The observation target detection device described in (1) above further comprises a displacement calculation unit that calculates the displacement at the observation target reflection point and the non-observation target reflection point, and a disturbance removal unit that removes the displacement component at the non-observation target reflection point from the displacement at the observation target reflection point.

[0104] In this configuration, the displacement at each reflection point determined to be an observed reflection point and an unobserved reflection point is calculated, and the displacement component of the unobserved reflection points is removed from the displacement at the observed reflection points. As a result, the displacement component caused by the periodic oscillation of the observation target detection device is removed from the displacement at the observed reflection points, which includes the displacement at the observed reflection points and the displacement component caused by the periodic oscillation of the observation target detection device, and the displacement at the observed reflection points can be obtained with high accuracy.

[0105] (3) In the observation target detection device described in (2) above, an object determined by the second determination unit to be an observation target reflection point is a human body, and an object determined by the second determination unit to be a non-observation target reflection point is a stationary object other than a human body within the observation range.

[0106] This configuration allows for the proper distinction between observed reflection points that include surface displacement components of the human body and unobserved reflection points that are stationary objects and do not include surface displacement components of the human body.

[0107] (4) In the observation target detection device described in (3) above, the disturbance removal unit removes the displacement component of the stationary object from the displacement at the observation target reflection point to generate the body surface displacement of the human body.

[0108] In this configuration, the displacement component caused by the periodic oscillation of the object detection device is removed from the displacement of the observed object reflection point, which includes the displacement of the human body surface and the displacement component caused by the periodic oscillation of the object detection device, thereby enabling the acquisition of highly accurate human body surface displacement as biological information.

[0109] (5) A method for detecting an object to be observed according to one aspect of the present disclosure includes: a first step of emitting radio waves into the observation range of a radar and identifying the location of a reflection point within the observation range based on the reflected waves of the radio waves; a second step of calculating a first correlation degree that indicates the degree of correlation between the time change of at least one of the amplitude, intensity, and power of the signal at the reflection point and the time change of the phase; a third step of selecting a reflection point for which the first correlation degree is equal to or greater than a predetermined value; a fourth step of calculating a second correlation degree that indicates the degree of correlation between the time change of at least one of the amplitude, intensity, power, and phase of the signals at two of the reflection points if there are three or more reflection points selected in the third step; and a fifth step of determining each reflection point for which the second correlation degree is equal to or greater than a predetermined value as an object to be observed, and determining the reflection points excluding the object to be observed as object to be observed.

[0110] In this configuration, the positioning process (1st step) identifies the location of the reflection points within the radar's observation range 2. For each reflection point identified in the positioning process, the first correlation calculation process (2nd step) is performed to calculate a first correlation, which indicates the degree of correlation between the time change of at least one of the amplitude, intensity, or power of the signal at each reflection point and the time change of the phase. The first determination process (3rd step) is performed to select reflection points whose first correlation is greater than or equal to a predetermined threshold, thereby selecting reflection points that contain periodic fluctuation components that are relatively large compared to random noise components. Then, the second correlation calculation process (4th step) is performed to calculate a second correlation, which indicates the degree of correlation between the time changes of amplitude, intensity, power, and phase between each signal at the reflection points selected in the first determination process. The second determination process (5th step) is performed to determine that each reflection point whose second correlation calculated in the second correlation calculation process is greater than or equal to a predetermined threshold is a non-observation target reflection point, and the reflection points excluding the non-observation target reflection points are observed target reflection points. This allows for the proper distinction between observed reflection points and unobserved reflection points that do not include displacement at the observed reflection points.

[0111] (6) In the observation target detection method described in (5) above, if there are two or fewer reflection points selected in the third step, the fourth step and the fifth step are canceled.

[0112] (7) The method for detecting an object to be observed according to (5) above further comprises a sixth step of calculating the displacement at the observed object reflection point and the non-observed object reflection point, and a seventh step of removing the displacement component at the non-observed object reflection point from the displacement at the observed object reflection point.

[0113] In this configuration, a displacement calculation process (step 6) is performed to calculate the displacement at each reflection point determined to be both an unobserved reflection point and an observed reflection point. Then, a disturbance removal process (step 7) is performed to remove the displacement component of the unobserved reflection points from the displacement at the observed reflection points. As a result, the displacement component caused by the periodic oscillation of the radar is removed from the displacement at the observed reflection points, which includes the displacement at the observed reflection points and the displacement component caused by the periodic oscillation of the radar, allowing for high-precision acquisition of the displacement at the observed reflection points.

[0114] (8) In the observation target detection method described in (7) above, if all reflection points are determined to be the observation target reflection points in step 5, steps 6 and 7 are canceled.

[0115] (9) In the observation target detection method described in (7) above, the object determined to be the observation target reflection point in step 5 is a human body, and the object determined to be the non-observation target reflection point in step 5 is a stationary object other than a human body within the observation range.

[0116] This configuration allows for the proper distinction between observed reflection points that include surface displacement components of the human body and unobserved reflection points that are stationary objects and do not include surface displacement components of the human body.

[0117] (10) In the observation target detection method described in (9) above, in step 7, the displacement component of the stationary object is removed from the displacement at the observation target reflection point to generate the body surface displacement of the human body.

[0118] In this configuration, the displacement component caused by the periodic oscillation of the object detection device is removed from the displacement of the observed object reflection point, which includes the displacement of the human body surface and the displacement component caused by the periodic oscillation of the object detection device, thereby enabling the acquisition of highly accurate human body surface displacement as biological information.

[0119] This disclosure makes it possible to realize an observation target detection device and an observation target detection method that can appropriately distinguish between observed targets and non-observed targets. [Explanation of symbols]

[0120] 1. Observation target detection device 2. Observation range 11 Radar 12. First Correlation Calculation Unit 13 1st Judgment Section 14. Second Correlation Calculation Unit 15 Second Judgment Section 16 Displacement Calculation Unit 17 Disturbance Removal Unit

Claims

1. A radar that emits radio waves within an observation range and identifies the position of reflection points for different objects within the observation range based on the reflected waves of said radio waves, A first correlation calculation unit calculates a first correlation that indicates the degree of correlation between the time change of at least one of the amplitude, intensity, and power of the signal at a reflection point whose position has been identified by the radar and the time change of its phase. A first determination unit selects a reflection point from among the reflection points whose position has been identified by the radar, the first correlation score being equal to or greater than a predetermined value. If there are three or more reflection points selected by the first determination unit, a second correlation calculation unit calculates a second correlation that indicates the degree of correlation between at least one of the time changes of amplitude, intensity, power, and phase between each signal at two reflection points, A second determination unit determines each reflection point whose second correlation is equal to or greater than a predetermined value as a non-observation target reflection point, and determines the reflection points excluding the non-observation target reflection points as observation target reflection points. Equipped with, A device for detecting the object being observed.

2. An observation target detection device according to claim 1, A displacement calculation unit that calculates the displacement at the observed reflection point and the non-observed reflection point, A disturbance removal unit that removes the displacement component at the non-observed reflection point from the displacement at the observed reflection point, Furthermore, A device for detecting the object being observed.

3. The observation target detection device according to claim 2, The object determined by the second determination unit to be the observed reflection point is a human body. The object determined by the second determination unit to be the non-observed reflection point is a stationary object other than a human body within the observation range. A device for detecting the object being observed.

4. The observation target detection device according to claim 3, The aforementioned disturbance removal unit is The displacement component of the stationary object is removed from the displacement at the observed reflection point to generate the surface displacement of the human body. A device for detecting the object being observed.

5. The first step involves emitting radio waves within the radar's observation range and identifying the positions of reflection points for different objects within the observation range based on the reflected waves of the radio waves. A second step is to calculate a first correlation degree that indicates the degree of correlation between the time variation of at least one of the amplitude, intensity, and power of the signal at a reflection point whose position has been identified by the radar, and the time variation of its phase. A third step of selecting a reflection point from among the reflection points whose position has been identified by the radar, the first correlation degree being equal to or greater than a predetermined value, If there are three or more reflection points selected in the third step, the fourth step is to calculate a second correlation degree that indicates the degree of correlation between at least one of the time changes of amplitude, intensity, power, and phase between each signal at two reflection points, A fifth step in which each reflection point whose second correlation is equal to or greater than a predetermined value is determined to be a non-observed reflection point, and the reflection points excluding the non-observed reflection points are determined to be observed reflection points, Having, Method for detecting the object of observation.

6. A method for detecting an object to be observed according to claim 5, If there are two or fewer reflection points selected in the third step, the fourth and fifth steps are canceled. Method for detecting the object of observation.

7. A method for detecting an object to be observed according to claim 5, A sixth step of calculating the displacement at the observed reflection point and the non-observed reflection point, A seventh step of removing the displacement component at the non-observed reflection point from the displacement at the observed reflection point, It further possesses, Method for detecting the object of observation.

8. A method for detecting an object to be observed according to claim 7, If all reflection points are determined to be the observed reflection points in the fifth step, the sixth and seventh steps are canceled. Method for detecting the object of observation.

9. A method for detecting an object to be observed according to claim 7, In the fifth step described above, the object determined to be the observed reflection point is a human body. In the fifth step described above, the object determined to be the non-observed reflection point is a stationary object other than a human body within the observation range. Method for detecting the object of observation.

10. A method for detecting an object to be observed according to claim 9, In the seventh step, the displacement component of the stationary object is removed from the displacement at the observed reflection point to generate the surface displacement of the human body. Method for detecting the object of observation.

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