Monitoring device and monitoring method

Abstract

The present invention is provided with: a moving body reflection component extraction unit (1201) for extracting a reflection component due to a moving body from a signal received by a sensor (11); a profile distribution generation unit (1202) for generating, on the basis of the reflection component due to the moving body and extracted by the moving body reflection component extraction unit (1201), a profile distribution that is a waveform indicating a relationship between the reception strength of the reflection component due to the moving body and a propagation distance or propagation delay time; a profile feature extraction unit (1203) for extracting a feature amount relating to the waveform shape of the profile distribution on the basis of the profile distribution generated by the profile distribution generation unit (1202); and a calculation unit (1204) for performing at least one process out of detection of existence of a moving body in at least one of indoor and outdoor areas, or calculation of a reliability of detection of existence of the moving body, on the basis of the feature amount extracted by the profile feature extraction unit (1203) or time-series change of the feature amount.

Description

Monitoring device and monitoring method

[0001] The present disclosure relates to a monitoring device and a monitoring method for monitoring the presence or absence of a moving object at least either indoors or outdoors.

[0002] In recent years, there has been a trend to introduce radio wave sensors such as millimeter-wave radar into indoor spaces such as vehicle interiors to monitor elderly people or detect abandoned infants. Compared to cameras, millimeter-wave radar has the advantage of being superior in terms of privacy and less susceptible to lighting or weather conditions.

[0003] On the other hand, the radio waves used by millimeter-wave radar have properties such as transmission, reflection, and diffraction. Therefore, when sensing a vehicle interior using millimeter-wave radar, the radio waves may pass through windows or walls and be reflected by people outside, resulting in multipath detection that can lead to false detection. This phenomenon can make it difficult to determine whether an object detected by the millimeter-wave radar is inside or outside the vehicle. This can lead to false detection when using millimeter-wave radar for interior sensing. For example, the radar may determine that a child has been left behind in the vehicle even when no one is present, resulting in a false alarm.

[0004] In response to this, a technology is known that uses a simple configuration to determine whether a detected object is located inside or outside the vehicle (see, for example, Patent Document 1). This conventional technology includes two antennas, a narrow-directional antenna and a wide-directional antenna. The conventional technology compares the reception strength of a signal received by outputting radio waves from the narrow-directional antenna with the reception strength of a signal received by outputting radio waves from the wide-directional antenna, and determines whether the detected object is located inside or outside the vehicle based on the comparison result.

[0005] JP 2010-188855 A

[0006] However, in the conventional technology, the accuracy of the determination is low because the detection of whether the detected object is inside or outside the vehicle is determined by comparing the reception strength of the signals received by the narrow directional antenna and the wide directional antenna. Furthermore, the conventional technology requires two antennas, a narrow directional antenna and a wide directional antenna, which complicates the hardware configuration and increases the amount of calculation required to process the signals received by these antennas.

[0007] The present disclosure has been made to solve the above-mentioned problems, and aims to provide a monitoring device that is capable of monitoring the presence or absence of moving objects at least indoors or outdoors with greater accuracy than conventional devices.

[0008] The monitoring device according to the present disclosure is characterized by comprising: a moving object reflection component extraction unit that extracts reflection components from a signal received by a sensor that transmits a signal and receives a signal reflected by the moving object; a profile distribution generation unit that generates a profile distribution, which is a waveform that indicates the relationship between the reception intensity of the reflection component from the moving object and the propagation distance or propagation delay time, based on the reflection components from the moving object extracted by the moving object reflection component extraction unit; a profile feature extraction unit that extracts feature amounts related to the waveform shape of the profile distribution based on the profile distribution generated by the profile distribution generation unit; and a calculation unit that performs at least one of detecting the presence or absence of a moving object at least either indoors or outdoors, or calculating the reliability of the detection of the presence or absence of a moving object, based on the feature amounts extracted by the profile feature extraction unit or changes in the feature amounts over time.

[0009] According to the present disclosure, with the above-described configuration, it is possible to monitor the presence or absence of a moving object at least either indoors or outdoors with higher accuracy than conventional methods.

[0010] FIG. 1 is a block diagram illustrating an example of the configuration of a monitoring system including a monitoring device according to a first embodiment. FIG. 3A and FIG. 3B are flowcharts illustrating an example of the operation of the monitoring device according to the first embodiment. FIG. 3A is a diagram illustrating an example of the transmission and reception of radio waves and a distance profile distribution when a moving object is present indoors, and FIG. 3B is a diagram illustrating an example of the transmission and reception of radio waves and a distance profile distribution when a moving object is present outdoors. FIG. 4A and FIG. 4B are diagrams illustrating an example of the operation of the monitoring device according to the first embodiment. FIG. 4A is a diagram illustrating an example of the distance profile distribution when a moving object is present indoors, and FIG. 4B is a diagram illustrating an example of the distance profile distribution when a moving object is present outdoors. FIG. 5A and FIG. 5B are diagrams illustrating multipath. FIG. 6A and FIG. 6B are diagrams illustrating an example of the operation of the monitoring device according to the first embodiment. FIG. 6A is a diagram illustrating an example of the distance profile distribution when a moving object is present indoors, and FIG. 6B is a diagram illustrating an example of a threshold used when a feature value is at a peak position. 7A and 7B are diagrams for explaining an example of the operation of the monitoring device according to embodiment 1, where FIG. 7A is a diagram showing an example of a distance profile distribution, and FIG. 7B is a diagram showing an example of peak position extraction when a distance profile distribution for each moving object speed is used. A diagram for explaining an example of the operation of a calculation unit according to embodiment 1. A block diagram showing an example of the configuration of a monitoring system including a monitoring device according to embodiment 2. A diagram for explaining an example of the operation when multiple radio waves are input to the monitoring device according to embodiment 2. FIGS. 11A and 11B are diagrams for explaining an example of the operation of the monitoring device according to embodiment 2, where FIG. 11A is a diagram showing an example of a distance profile distribution obtained by the monitoring device according to embodiment 1, and FIG. 11B is a diagram showing an example of a distance profile distribution obtained by the monitoring device according to embodiment 2. A block diagram showing an example of the configuration of a monitoring system including a monitoring device according to embodiment 3. FIGS. 13A and 13B are diagrams showing example hardware configurations of the monitoring devices according to embodiments 1 to 3.

[0011] Hereinafter, embodiments will be described in detail with reference to the drawings. Embodiment 1. Fig. 1 is a diagram showing an example of the configuration of a monitoring system 1 equipped with a monitoring device 12 according to embodiment 1. The monitoring system 1 monitors the presence or absence of moving objects at least either inside or outside the vehicle. As shown in Fig. 1, this monitoring system 1 includes a sensor 11, a monitoring device 12, and a control device 13. This monitoring system 1 can be applied, for example, as a monitoring system that monitors the presence or absence of moving objects at least either inside or outside the vehicle.

[0012] The sensor 11 transmits a signal to a room targeted by the monitoring device 12 and receives the signal reflected by an object present inside or outside the room. Such objects include moving objects such as people. The sensor 11 may be any sensor capable of transmitting a signal and receiving a signal reflected by a moving object, such as a radio wave sensor capable of transmitting and receiving radio waves or an ultrasonic sensor capable of transmitting and receiving ultrasonic waves. In the first embodiment, there is only one sensor 11. The signal received by the sensor 11 is output to the monitoring device 12.

[0013] The monitoring device 12 monitors the presence or absence of a moving object at least either indoors or outdoors based on the signal received by the sensor 11. The monitoring device 12 according to the first embodiment detects the presence or absence of a moving object at least either indoors or outdoors. A signal indicating the monitoring result by the monitoring device 12 is output to the control device 13. An example configuration of the monitoring device 12 will be described later.

[0014] The control device 13 performs various controls based on the monitoring results of the monitoring device 12. For example, when the monitoring device 12 detects the presence of a moving object inside or outside the room, the control device 13 may issue an alert to the outside to indicate this. This enables the monitoring system 1 to implement security measures such as theft detection or suspicious person detection.

[0015] 1, the monitoring device 12 includes a moving object reflection component extraction unit 1201, a profile distribution generation unit 1202, a profile feature extraction unit 1203, and a calculation unit 1204. Note that the monitoring device 12 can also perform part of the processing using a cloud server or another ECU (Electronic Control Unit).

[0016] The moving object reflection component extraction unit 1201 extracts reflection components due to a moving object from the signal received by the sensor 11. That is, the moving object reflection component extraction unit 1201 extracts reflection components due to a moving object by suppressing reflection components due to objects that exist around the sensor 11 and have a velocity of zero from the signal received by the sensor 11. In this case, the moving object reflection component extraction unit 1201 extracts reflection components due to a moving object by using, for example, a known process such as MTI (Moving Target Indicator) processing. A signal indicating the extraction result by the moving object reflection component extraction unit 1201 is output to the profile distribution generation unit 1202.

[0017] The profile distribution generation unit 1202 generates a profile distribution based on the reflection components from the moving object extracted by the moving object reflection component extraction unit 1201. Here, for example, the profile distribution generation unit 1202 generates a distance profile distribution as the profile distribution. The distance profile distribution is a waveform indicating the relationship between the reception intensity of the reflection components from the moving object and the propagation distance. In this case, for example, the profile distribution generation unit 1202 generates the distance profile distribution by applying a Fourier transform process in the fast time direction to the reflection components from the moving object. Note that the distance profile distribution shown below indicates the relationship between the reception intensity of the reflection components from the moving object and half the propagation distance, and the distance indicated by the peak position matches (including the meaning of approximately matches) the distance drawn by a straight line from the sensor 11 to the moving object. The profile distribution generation unit 1202 may also generate a profile distribution for each velocity of the moving object as the profile distribution. A signal indicating the generation result by the profile distribution generation unit 1202 is output to the profile feature extraction unit 1203.

[0018] The profile feature extraction unit 1203 extracts a feature quantity related to the waveform shape of the profile distribution based on the profile distribution generated by the profile distribution generation unit 1202. In this case, for example, the profile feature extraction unit 1203 may perform frequency analysis on the profile distribution generated by the profile distribution generation unit 1202 and extract the frequency analysis result as a feature quantity. For example, the profile feature extraction unit 1203 may extract the gradient of a falling section in the profile distribution generated by the profile distribution generation unit 1202 as a feature quantity. The falling section is a section in the distance profile distribution from the maximum value to a predetermined value or less. For example, the profile feature extraction unit 1203 may extract the peak position in the profile distribution generated by the profile distribution generation unit 1202 as a feature quantity. The profile feature extraction unit 1203 may extract a combination of the frequency analysis result, gradient, or peak position as a feature quantity. A signal indicating the extraction result by the profile feature extraction unit 1203 is output to the calculation unit 1204.

[0019] The calculation unit 1204 detects the presence or absence of a moving object at least either indoors or outdoors based on the feature amounts extracted by the profile feature extraction unit 1203 or time-series changes in the feature amounts. A signal indicating the detection result by this calculation unit 1204 is output to the external control device 13.

[0020] Next, an example of the operation of the monitoring device 12 according to the first embodiment shown in FIG. 1 will be described with reference to FIG. 2 . In the following description, it is assumed that the sensor 11 is a radio wave sensor that transmits and receives radio waves, and the profile distribution generation unit 1202 generates a distance profile distribution as the profile distribution. In the monitoring device 12 according to the first embodiment shown in FIG. 1 , as shown in FIG. 2 , the moving object reflection component extraction unit 1201 first extracts reflection components due to a moving object from the radio waves received by the sensor 11 (step ST101). That is, the moving object reflection component extraction unit 1201 extracts reflection components due to a moving object by suppressing reflection components due to objects present around the sensor 11 with a speed of zero from the radio waves received by the sensor 11. In this case, the moving object reflection component extraction unit 1201 extracts reflection components due to a moving object by using, for example, a known process such as MTI processing. A signal indicating the extraction result by the moving object reflection component extraction unit 1201 is output to the profile distribution generation unit 1202.

[0021] Next, the profile distribution generation unit 1202 generates a distance profile distribution based on the reflection components due to the moving object extracted by the moving object reflection component extraction unit 1201 (step ST102). At this time, for example, the profile distribution generation unit 1202 generates the distance profile distribution by applying a Fourier transform process in the fast time direction to the reflection components due to the moving object. The profile distribution generation unit 1202 may also generate a distance profile distribution for each velocity of the moving object as the profile distribution. A signal indicating the generation result by the profile distribution generation unit 1202 is output to the profile feature extraction unit 1203.

[0022] Next, the profile feature extraction unit 1203 extracts feature quantities related to the waveform shape of the distance profile distribution based on the distance profile distribution generated by the profile distribution generation unit 1202 (step ST103). At this time, for example, the profile feature extraction unit 1203 may perform frequency analysis on the distance profile distribution generated by the profile distribution generation unit 1202 and extract the frequency analysis result as a feature quantity. For example, the profile feature extraction unit 1203 may extract the gradient of a falling edge in the distance profile distribution generated by the profile distribution generation unit 1202 as a feature quantity. For example, the profile feature extraction unit 1203 may extract the peak position in the distance profile distribution generated by the profile distribution generation unit 1202 as a feature quantity. The profile feature extraction unit 1203 may extract a combination of the frequency analysis result, gradient, or peak position as a feature quantity. A signal indicating the extraction result by the profile feature extraction unit 1203 is output to the calculation unit 1204.

[0023] Next, the calculation unit 1204 detects the presence or absence of a moving object at least either indoors or outdoors based on the feature values ​​extracted by the profile feature extraction unit 1203 or time-series changes in the feature values ​​(step ST104). A signal indicating the detection result by the calculation unit 1204 is output to the external control device 13.

[0024] Here, consider a case where, in order to determine differences in waveform shapes of distance profile distributions, the profile feature extraction unit 1203 extracts, as feature quantities, the results of frequency analysis of the distance profile distributions generated by the profile distribution generation unit 1202. In this case, the profile feature extraction unit 1203 can use processing such as Fourier transform-based processing or wavelet transform as the frequency analysis.

[0025] For example, the upper part of FIG. 3A illustrates a case in which radio waves transmitted by the sensor 11 are reflected by a moving object present in the room. In this case, the radio waves transmitted by the sensor 11 are repeatedly reflected by various objects in the room, including the moving object, resulting in multipath waves (see FIG. 5 ), which are more easily received by the sensor 11. As shown in FIG. 5 , the direct wave reflected by the moving object and returning directly to the sensor 11 corresponds to a peak position. As the propagation distance increases, the multipath waves are located further back from the peak position, resulting in lower reception strength. Furthermore, the more times a multipath is reflected, the longer the propagation distance. Thus, when a moving object is present in the room, many multipath waves passing through the moving object are received. Therefore, as shown in the lower part of FIG. 3A and FIG. 4A , the distance profile distribution has a peak at a position corresponding to the linear distance from the sensor 11 to the moving object, followed by a gradual attenuation of reception strength in the subsequent falling edge. The frequency analysis results for the distance profile distribution in this case show a large low-frequency component.

[0026] On the other hand, for example, the upper part of Figure 3B shows a case where radio waves transmitted by sensor 11 are reflected by a moving object outside the room. In this case, the reflected radio waves are less likely to return to sensor 11, resulting in fewer multipath waves passing through the moving object compared to when the moving object is present indoors. Note that reference numeral 301 in the upper part of Figure 3B indicates radio waves that do not return to sensor 11. Therefore, as shown in the lower part of Figure 3B and Figure 4B, the distance profile distribution has a peak at a position corresponding to the linear distance from sensor 11 to the moving object, and the reflection intensity attenuates sharply in the subsequent falling section. The frequency analysis result for the distance profile distribution in this case shows a large high-frequency component.

[0027] Therefore, in this case, the calculation unit 1204 can determine that a moving object is present indoors if the low-frequency components are large, and can determine that a moving object is present outdoors if the high-frequency components are large. For example, the calculation unit 1204 can determine that a moving object is present indoors if the frequency analysis result, which is the feature extracted by the profile feature extraction unit 1203, contains a frequency component of 1 cycle / m, and can determine that a moving object is present outdoors if the frequency component is of 5 cycles / m. Note that the threshold for determining whether the low-frequency components or the high-frequency components are large can be set as appropriate.

[0028] Also, consider a case where the profile feature extracting unit 1203 extracts the gradient in the falling section of the distance profile distribution as a feature amount in order to determine differences in the waveform shapes of the distance profile distribution.

[0029] For example, as shown in the upper part of Fig. 3A, when radio waves transmitted by the sensor 11 are reflected by a moving object present in the room, the distance profile distribution has a peak at a position corresponding to the linear distance from the sensor 11 to the moving object, and the reflection intensity gradually attenuates in the subsequent falling section, as shown in the lower part of Fig. 3A and Fig. 4A. In other words, in this case, the gradient in the falling section becomes smaller.

[0030] On the other hand, for example, in the case where the radio waves transmitted by the sensor 11 are reflected by a moving object outside the room, as shown in the upper part of Fig. 3B, the distance profile distribution has a peak at a position corresponding to the linear distance from the sensor 11 to the moving object, and the reflection intensity attenuates sharply in the subsequent falling section, as shown in the lower part of Fig. 3B and Fig. 4B. In other words, in this case, the gradient in the falling section becomes large.

[0031] Therefore, in this case, the calculation unit 1204 can determine that a moving object is present indoors when the gradient is smaller than a predetermined value, and can determine that a moving object is present outdoors when the gradient is larger than the predetermined value. For example, the calculation unit 1204 can determine that a moving object is present indoors when the gradient, which is the feature extracted by the profile feature extraction unit 1203, is -1 or greater, and can determine that a moving object is present outdoors when the gradient is less than -2. Note that the threshold for determining whether the gradient is small or large can be set as appropriate.

[0032] Also, consider a case where the profile feature extracting unit 1203 extracts the peak position in the distance profile distribution as a feature amount in order to determine differences in the waveform shapes of the distance profile distribution.

[0033] For example, as shown in the upper part of Figure 3A, when the radio waves transmitted by sensor 11 are reflected by a moving object present in the room, the peak in the distance profile distribution will be located in a section close to sensor 11, i.e., within a distance range equivalent to the room, as shown in Figure 6A.

[0034] On the other hand, for example, as shown in the upper part of Figure 3B, when the radio waves transmitted by sensor 11 are reflected by a moving object outside the room, the peak in the distance profile distribution will be located in a section far from sensor 11, that is, within a distance range corresponding to the outside of the room.

[0035] Therefore, the calculation unit 1204 can determine that there is a moving object inside the room when the peak is located within a distance range corresponding to the indoor area, and can determine that there is a moving object outside the room when the peak is located within a distance range corresponding to the outdoor area. For example, as shown in FIG. 6, the calculation unit 1204 can determine that there is a moving object outside the room when the peak is located within a distance range corresponding to the outdoor area. ｉｎ If the peak is within the range of R, it is determined that a moving object exists in the room. ｏｕｔ If the object is located within the above range, it can be determined that a moving object is present outside the room. ｉｎ The range of R is clearly considered to be an indoor space. ｏｕｔThe above range can clearly be considered as an outdoor space, and can be set as appropriate.

[0036] The profile feature extraction unit 1203 may extract a combination of the frequency analysis results, gradients, or peak positions as feature quantities, and the calculation unit 1204 may comprehensively detect the presence or absence of a moving object based on these feature quantities. For example, if the profile feature extraction unit 1203 extracts the frequency analysis results and peak positions as feature quantities, the calculation unit 1204 may determine that a moving object is present indoors as a final determination if the frequency analysis results indicate that a moving object is present indoors and the peak positions indicate that a moving object is present indoors. Alternatively, if the frequency analysis results indicate that a moving object is present outdoors and the peak positions indicate that a moving object is present outdoors, the calculation unit 1204 may determine that a moving object is present outdoors as a final determination. This is believed to improve the detection accuracy of the monitoring device 12 according to embodiment 1.

[0037] Also, consider a case where the profile distribution generation unit 1202 generates a distance profile distribution for each velocity of a moving object as the profile distribution. In this case, for example, the profile feature extraction unit 1203 can extract a feature amount for each velocity of the moving object based on the distance profile distribution for each velocity of the moving object. Here, the feature amount is at least one of a frequency analysis result, a gradient, or a peak position.

[0038] 7B shows a case where the profile feature extraction unit 1203 extracts the peak position of each velocity of a moving object from the distance profile distribution for each velocity of the moving object. The circles in the two-dimensional distribution showing the relationship between the velocity and distance of the moving object in FIG. 7B indicate the peaks for each velocity of the moving object detected by CFAR (Constant False Alarm Rate) processing.

[0039] In this case, the calculation unit 1204 can determine that there is a moving object inside the room if a certain number or more of peaks are located within a distance range corresponding to the indoors, and can determine that there is a moving object outside the room if a certain number or more of peaks are located within a distance range corresponding to the outdoors.

[0040] Furthermore, the calculation unit 1204 may process only the feature amounts included within a predetermined range from the position where the target moving object is assumed to exist, among the feature amounts for each speed of the moving object extracted by the profile feature extraction unit 1203, and may exclude other feature amounts from the processing. ｔ From R ｔ -R ｗｉｄ Only peaks located within the range of R ｔ is the position where the target moving object is assumed to exist. ｗｉｄ is a predetermined range and can be set appropriately.

[0041] Furthermore, the calculation unit 1204 may process only feature amounts that fall within a predetermined range from the speed assumed to be the target speed of the moving object, among the peak positions for each speed of the moving object extracted by the profile feature extraction unit 1203, and exclude other feature amounts from the processing. For example, if the target moving object is a sleeping person, the speed range of the sleeping person can be set based on the expected breathing volume during sleep, etc. Therefore, by processing only feature amounts that fall within the above speed range, the calculation unit 1204 can exclude feature amounts of unexpected movement speeds from the processing target, thereby improving accuracy and reducing the processing load.

[0042] Consider a case where the calculation unit 1204 detects the presence or absence of a moving object at least either indoors or outdoors based on time-series changes in the feature amounts extracted by the profile feature extraction unit 1203. Here, the feature amounts are at least one of the frequency analysis result, the gradient, and the peak position.

[0043] For example, if the feature amount is a gradient, the calculation unit 1204 can determine that a moving object is present indoors if the gradient is -1 or greater for a certain period of time. An example of the certain period is 3 seconds. Furthermore, if the number of times the gradient is less than -2 is greater than the number of times it is -1 or greater during the certain period of time, the calculation unit 1204 can determine that a reaction is due to a moving object outside the room rather than a moving object inside the room, and can determine that a moving object is present outdoors.

[0044] The calculation unit 1204 can also determine, as a detection result, any one of four patterns as shown in FIG. 8 . In FIG. 8 , the first pattern indicates a pattern in which there is no moving object indoors and no moving object outdoors. The second pattern indicates a pattern in which there is a moving object indoors and no moving object outdoors. The third pattern indicates a pattern in which there is no moving object indoors and a moving object outdoors. The fourth pattern indicates a pattern in which there is a moving object indoors and a moving object outdoors. For example, the calculation unit 1204 may detect all of the above four patterns, or may detect only some of the patterns, such as detecting only the second and third patterns.

[0045] As described above, the monitoring device 12 according to the first embodiment extracts reflected components due to a moving object from the wave signal received by the sensor 11 to generate a profile distribution, and detects the presence or absence of a moving object at least either indoors or outdoors based on feature quantities related to the waveform shape of this profile distribution or time-series changes in these feature quantities. This enables the monitoring device 12 according to the first embodiment to accurately detect the presence or absence of a moving object at least either indoors or outdoors. Furthermore, the sensor 11 may be a single sensor, and the monitoring device 12 according to the first embodiment can detect the presence or absence of a moving object at least either indoors or outdoors with a minimum sensor configuration.

[0046] In the above description, the profile distribution generation unit 1202 generates a distance profile distribution as the profile distribution. However, the distance in the distance profile distribution can be replaced with time using the relational expression: time = distance ÷ (2 × speed of light). Therefore, the profile distribution generation unit 1202 may generate a delay profile distribution, which is a waveform indicating the relationship between the reception intensity of the reflection component from a moving object and the propagation delay time, instead of a distance profile distribution.

[0047] In the above description, the monitoring system 1 including the monitoring device 12 is exemplified as a monitoring system that monitors the presence or absence of moving objects inside or outside a vehicle. However, the application of the monitoring system 1 including the monitoring device 12 is not limited to this. For example, the monitoring system 1 may be a monitoring system that monitors the presence or absence of moving objects inside or outside a vehicle other than a vehicle, such as a bus, train, ship, or airplane. Furthermore, the monitoring system 1 may be a monitoring system that monitors the presence or absence of moving objects inside or outside a living room, toilet, bathroom, or elevator car in a house, factory, office, or the like. In other words, the monitoring system 1 may be any monitoring system that monitors the presence or absence of moving objects inside or outside an indoor space separated by a window, wall, or the like.

[0048] As described above, according to the first embodiment, the monitoring device 12 includes a moving object reflection component extraction unit 1201 that extracts reflection components from a signal received by the sensor 11, which transmits a signal and receives a signal reflected by the moving object, a profile distribution generation unit 1202 that generates a profile distribution, which is a waveform indicating the relationship between the reception intensity of the reflection component from the moving object and the propagation distance or propagation delay time, based on the reflection components from the moving object extracted by the moving object reflection component extraction unit 1201, a profile feature extraction unit 1203 that extracts feature amounts related to the waveform shape of the profile distribution based on the profile distribution generated by the profile distribution generation unit 1202, and a calculation unit 1204 that detects the presence or absence of a moving object at least either indoors or outdoors, based on the feature amounts extracted by the profile feature extraction unit 1203 or time-series changes in the feature amounts. As a result, the monitoring device 12 according to the first embodiment is capable of monitoring the presence or absence of a moving object at least either indoors or outdoors with higher accuracy than conventional methods. Furthermore, the monitoring device 12 according to the first embodiment can detect the presence or absence of a moving object using a signal from a single sensor 11, thereby reducing the amount of calculation compared to conventional systems. Furthermore, the monitoring system 1 according to the first embodiment can use only a single sensor 11, thereby simplifying the hardware configuration compared to conventional systems.

[0049] Moreover, according to the first embodiment, the profile feature extraction unit 1203 extracts, as a feature, the result of frequency analysis of the profile distribution generated by the profile distribution generation unit 1202. Moreover, according to the first embodiment, the profile feature extraction unit 1203 extracts, as a feature, the gradient in a falling section of the profile distribution generated by the profile distribution generation unit 1202. Moreover, according to the first embodiment, the calculation unit 1204 determines that a moving object is present indoors when the gradient extracted by the profile feature extraction unit 1203 is smaller than a predetermined value, and determines that a moving object is present outdoors when the gradient is larger than the predetermined value. Moreover, according to the first embodiment, the profile feature extraction unit 1203 extracts, as a feature, the peak position of the profile distribution generated by the profile distribution generation unit 1202. As a result, the monitoring device 12 according to the first embodiment is capable of monitoring the presence or absence of a moving object at least indoors or outdoors with higher accuracy than conventional methods.

[0050] Furthermore, according to the first embodiment, the profile distribution generating unit 1202 generates a profile distribution, which is a waveform indicating the relationship between the reception intensity of the reflected component from the moving object and the propagation distance or propagation delay time, for each speed of the moving object. This makes it easier to exclude from the processing target feature amounts based on the reflected component from moving objects other than the target moving object, thereby further improving accuracy.

[0051] Moreover, according to the first embodiment, the monitoring method includes the steps of: a moving object reflection component extraction unit 1201 extracting reflection components from a moving object from a signal received by the sensor 11, which transmits a signal and receives a signal reflected by the moving object; a profile distribution generation unit 1202 generating a profile distribution, which is a waveform indicating the relationship between the reception intensity of the reflection component from the moving object and the propagation distance or the propagation delay time, based on the reflection components from the moving object extracted by the moving object reflection component extraction unit 1201; a profile feature extraction unit 1203 extracting feature amounts related to the waveform shape of the profile distribution based on the profile distribution generated by the profile distribution generation unit 1202; and a calculation unit 1204 detecting the presence or absence of a moving object at least either indoors or outdoors, based on the feature amounts extracted by the profile feature extraction unit 1203 or time-series changes in the feature amounts. As a result, the monitoring method according to the first embodiment enables monitoring the presence or absence of a moving object at least either indoors or outdoors with higher accuracy than conventional methods.

[0052] Second Embodiment The monitoring system 1 according to the first embodiment has one sensor 11. In contrast, the monitoring system 1 according to the second embodiment has a plurality of sensors 11.

[0053] Fig. 9 is a block diagram showing a configuration example of a monitoring system 1 including a monitoring device 12 according to a second embodiment. In the monitoring system 1 according to the second embodiment shown in Fig. 9, the number of sensors 11 is changed from one to a plurality of sensors, and the moving body reflection component extraction unit 1201 of the monitoring device 12 is changed to a moving body reflection component extraction unit 1201b, compared to the monitoring system 1 according to the first embodiment shown in Fig. 1. Note that Fig. 9 shows a case where two sensors 11 are provided in the monitoring system 1, but this is not limiting, and three or more sensors 11 may be provided. The other configuration example of the monitoring system 1 according to the second embodiment shown in Fig. 9 is similar to the configuration example of the monitoring system 1 according to the first embodiment, and the same reference numerals are used, and only the different parts will be described.

[0054] The sensor 11 in the second embodiment has a plurality of receiving antennas or a plurality of receiving units that are installed so as to be able to receive reflected waves from different directions of arrival.

[0055] The moving object reflection component extraction unit 1201b extracts reflection components due to moving objects from radio waves received by multiple sensors 11 for each arrival angle of the radio waves. That is, the moving object reflection component extraction unit 1201b extracts reflection components due to moving objects for each arrival angle of the radio waves by suppressing reflection components due to objects existing around the sensors 11 with a speed of zero for the radio waves received by the sensors 11. In this case, the moving object reflection component extraction unit 1201b extracts reflection components due to moving objects for each arrival angle of the radio waves by using, for example, a known process such as MTI processing. Note that the arrival angle here refers to a predetermined angle range. A signal indicating the extraction result for each arrival angle of the radio waves by the moving object reflection component extraction unit 1201b is output to the profile distribution generation unit 1202.

[0056] The profile distribution generating unit 1202 in the second embodiment generates a profile distribution for each angle of arrival of the radio wave based on the reflection components from the moving object for each angle of arrival of the radio wave extracted by the moving object reflection component extracting unit 1201b.

[0057] In this way, when there are multiple sensors 11, as shown in Figure 10, for example, the moving object reflection component extraction unit 1201b of the monitoring device 12 of embodiment 2 extracts reflection components from moving objects in each direction of arrival.

[0058] Here, for example, as shown in FIG. 11A , consider a case where there is one sensor 11 and moving objects are present both indoors and outdoors. In this case, the distance profile distribution may be such that the waveform due to the moving object present indoors and the waveform due to the moving object present outdoors are superimposed. That is, if the distance from the sensor 11 to the moving object present indoors is equal to the distance from the sensor 11 to the moving object present outdoors, the waveform due to the moving object present indoors and the waveform due to the moving object present outdoors are superimposed. Note that in FIG. 11A , reference numeral 1101 indicates a waveform when a moving object is present indoors, and reference numeral 1102 indicates a waveform when a moving object is present outdoors. In the example of FIG. 11 , the waveform indicated by reference numeral 1101 is weaker than the waveform indicated by reference numeral 1102 and may be canceled out by the waveform indicated by reference numeral 1102, resulting in the possibility of not being able to detect the moving object present indoors. On the other hand, if there are multiple sensors 11, radio waves can be directed in both indoor and outdoor directions using an existing beam control method, such as digital beam forming. Therefore, in this case, even if there are moving objects both indoors and outdoors, as shown in Fig. 11B, by dividing the distance profile distribution by arrival angle, it is possible to separate the waveform due to the moving object present indoors from the waveform due to the moving object present outdoors. Note that in Fig. 11B, the distance profile distribution on the left side shows the waveform when a moving object is present indoors, and the distance profile distribution on the right side shows the waveform when a moving object is present outdoors. In this case, even if the waveforms on the left and right sides of Fig. 11B are superimposed, it is possible to detect the moving object present indoors and the moving object present outdoors from each waveform.

[0059] 7 , consider a case where the profile distribution generation unit 1202 extracts a profile distribution for each velocity of a moving object as the profile distribution, and there are multiple sensors 11. In this case, for example, the calculation unit 1204 can detect the direction of the peak for each velocity of the moving object. Therefore, the calculation unit 1204 can calculate the three-dimensional position where the moving object is assumed to exist from the peak position for each velocity of the moving object, and can detect the presence or absence of a moving object indoors from the number of three-dimensional positions within a distance range equivalent to indoors, and can detect the presence or absence of a moving object outdoors from the number of three-dimensional positions within a distance range equivalent to outdoors.

[0060] As described above, according to the second embodiment, the moving object reflection component extraction unit 1201b extracts reflection components from a moving object for each angle of arrival of a signal from signals received by a plurality of sensors 11. This enables the monitoring device 12 according to the second embodiment to have improved accuracy compared to the first embodiment.

[0061] Embodiment 3. The monitoring device 12 according to embodiment 1 detects the presence or absence of a moving object at least either indoors or outdoors. In contrast, the monitoring device 12 according to embodiment 3 will be described as determining the reliability of the detection of the presence or absence of a moving object.

[0062] Fig. 12 is a block diagram showing a configuration example of a monitoring system 1 including a monitoring device 12 according to embodiment 3. In the monitoring system 1 according to embodiment 3 shown in Fig. 12, the calculation unit 1204 of the monitoring device 12 is changed to a calculation unit 1204b, compared to the monitoring system 1 according to embodiment 1 shown in Fig. 1. The other configuration example of the monitoring system 1 according to embodiment 3 shown in Fig. 12 is the same as the configuration example of the monitoring system 1 according to embodiment 1, and the same reference numerals are used and only the different parts will be described.

[0063] The calculation unit 1204b has the function of calculating the reliability of the detection of the presence or absence of a moving object in addition to the functions of the calculation unit 1204 in embodiment 1. In this case, for example, the calculation unit 1204b may calculate the reliability of the detection of the presence or absence of a moving object based on the feature quantities extracted by the profile feature extraction unit 1203. That is, the calculation unit 1204b may calculate the reliability of the detection of the presence or absence of a moving object based on one or more of the frequency analysis results, gradients, or peak positions, which are the feature quantities extracted by the profile feature extraction unit 1203. The calculation unit 1204b may also calculate the time average value of the calculated reliability as the final reliability. For example, the calculation unit 1204b may calculate the reliability of the detection of the presence or absence of a moving object based on time-series changes in the feature quantities extracted by the profile feature extraction unit 1203. For example, the calculation unit 1204b may calculate the reliability of the detection of the presence or absence of a moving object based on time-series changes in the detection of the presence or absence of a moving object.

[0064] Here, consider a case where the calculation unit 1204b calculates the reliability of detection of the presence or absence of a moving object based on the feature amount extracted by the profile feature extraction unit 1203. In the following, a case where the feature amount is the gradient in the falling section of the distance profile distribution is shown, but the same applies to the case where the feature amount is the frequency analysis result or the peak position.

[0065] In this case, for example, if the gradient in the falling section of the profile distribution is -1 or greater, the calculation unit 1204b determines that the reliability of the detection of the presence of a moving object in the room is high, for example, the reliability is 80% or greater. Also, for example, if the gradient in the falling section of the profile distribution is -2 or greater and less than -1, the calculation unit 1204b determines that the reliability of the detection of the presence of a moving object in the room is medium, for example, the reliability is 50% or greater. Also, for example, if the gradient in the falling section of the profile distribution is less than -2, the calculation unit 1204b determines that the reliability of the detection of the presence of a moving object in the room is low, for example, the reliability is 20% or greater.

[0066] In this way, the calculation unit 1204b calculates the reliability according to the degree of deviation of the gradient in the profile distribution from the threshold value used for determination by the calculation unit 1204.

[0067] The calculation unit 1204b may determine the reliability using, for example, a method based on predefined rules, a statistical method based on observed data, or machine learning.

[0068] Next, consider a case where the calculation unit 1204b calculates the reliability of the detection of the presence or absence of a moving object based on a time-series change in the detection of the presence or absence of a moving object.

[0069] In this case, for example, if the detection of the presence or absence of a moving object within a predetermined period fluctuates between "moving object inside the room," "moving object inside the room," "moving object outside the room," and "moving object inside the room," the calculation unit 1204b determines that the detection of the presence of a moving object inside the room is highly reliable, for example, 75% or higher, because the number of detections of a moving object inside the room is greater than the number of detections of a moving object outside the room. The calculation unit 1204b determines that the detection result of the presence or absence of a moving object is highly reliable, for example, 25%. The above-mentioned certain period can be, for example, 5 seconds. If the calculation unit 1204b determines that the detection of the presence or absence of a moving object fluctuates significantly and that the detection is unstable, it may temporarily suspend notification of the detection result to the external control device 13 until the detection stabilizes.

[0070] The above description also illustrates a case in which the calculation unit 1204b has both the function of detecting the presence or absence of a moving object and the function of calculating the reliability of the presence or absence of a moving object. However, the calculation unit 1204b may not have the function of detecting the presence or absence of a moving object, but may only have the function of calculating the reliability of the presence or absence of a moving object. That is, the function of detecting the presence or absence of a moving object may be provided in an external component of the monitoring device 12, such as the control device 13. In this case, the control device 13 may detect the presence or absence of a moving object at least indoors or outdoors by, for example, combining the reliability calculated by the monitoring device 12 with information for detecting the presence or absence of a moving object from another sensor and performing processing.

[0071] 12 shows a case where the calculation unit 1204 is changed to the calculation unit 1204b in the monitoring system 1 according to embodiment 1. However, this is not limiting, and the calculation unit 1204 may be changed to the calculation unit 1204b in the monitoring system 1 according to embodiment 2, and the same effect as above can be obtained.

[0072] As described above, according to the third embodiment, the monitoring device 12 includes moving object reflection component extraction units 1201, 1201b that extract reflection components caused by a moving object from signals received by the sensor 11, which transmits signals and receives signals reflected by the moving object; a profile distribution generation unit 1202 that generates a profile distribution, which is a waveform that indicates the relationship between the reception intensity of the reflection components caused by the moving object and the propagation distance or propagation delay time, based on the reflection components caused by the moving object extracted by the moving object reflection component extraction units 1201, 1201b; a profile feature extraction unit 1203 that extracts feature amounts related to the waveform shape of the profile distribution generated by the profile distribution generation unit 1202; and a calculation unit 1204b that calculates the reliability of detection of the presence or absence of a moving object, or detects the presence or absence of a moving object at least either indoors or outdoors and calculates the reliability of detection of the presence or absence of the moving object, based on the feature amounts extracted by the profile feature extraction unit 1203 or time-series changes in the feature amounts. As a result, the monitoring device 12 according to the third embodiment is capable of monitoring the presence or absence of a moving object at least indoors or outdoors with higher accuracy than conventional methods. Furthermore, the monitoring device 12 according to the third embodiment is capable of detecting the presence or absence of a moving object using a signal from a single sensor 11, which makes it possible to reduce the amount of calculation required compared to conventional methods. Furthermore, the monitoring system 1 according to the third embodiment may require only a single sensor 11, which makes it possible to simplify the hardware configuration compared to conventional methods.

[0073] According to the third embodiment, the calculation unit 1204b calculates the reliability of detection of the presence or absence of a moving object based on the feature quantities extracted by the profile feature extraction unit 1203. That is, the calculation unit 1204b calculates the reliability of detection of the presence or absence of a moving object based on one or more of the feature quantities extracted by the profile feature extraction unit 1203: the frequency analysis result for the profile distribution, the gradient of the falling edge in the profile distribution, or the peak position in the profile distribution. According to the third embodiment, the calculation unit 1204b calculates the reliability of detection of the presence or absence of a moving object based on time-series changes in the feature quantities extracted by the profile feature extraction unit 1203. According to the third embodiment, the calculation unit 1204b calculates the reliability of detection of the presence or absence of a moving object based on time-series changes in the detection of the presence or absence of a moving object. As a result, the monitoring device 12 according to the third embodiment can monitor the presence or absence of a moving object at least indoors or outdoors with higher accuracy than conventional methods.

[0074] Furthermore, according to this embodiment 3, the monitoring method includes the steps of: the moving object reflection component extraction units 1201 and 1201b extracting reflection components from a moving object from a signal received by the sensor 11, which transmits a signal and receives a signal reflected by the moving object; the profile distribution generation unit 1202 generating a profile distribution, which is a waveform showing the relationship between the reception intensity of the reflection component from the moving object and the propagation distance or propagation delay time, based on the reflection components from the moving object extracted by the moving object reflection component extraction units 1201 and 1201b; the profile feature extraction unit 1203 extracting feature amounts related to the waveform shape of the profile distribution based on the profile distribution generated by the profile distribution generation unit 1202; and the calculation unit 1204b calculating the reliability of detecting the presence or absence of a moving object, or detecting the presence or absence of a moving object at least either indoors or outdoors and calculating the reliability of the detection of the presence or absence of the moving object, based on the feature amounts extracted by the profile feature extraction unit 1203 or time-series changes in the feature amounts. As a result, the monitoring method according to the third embodiment makes it possible to monitor the presence or absence of a moving object at least either indoors or outdoors with higher accuracy than conventional methods.

[0075] Finally, with reference to FIG. 13 , an example of the hardware configuration of the monitoring device 12 according to the first to third embodiments will be described. Note that while the example of the hardware configuration of the monitoring device 12 according to the first embodiment will be described here, the same applies to the example of the hardware configuration of the monitoring device 12 according to the second and third embodiments. The functions of the moving body reflection component extraction unit 1201, the profile distribution generation unit 1202, the profile feature extraction unit 1203, and the calculation unit 1204 in the monitoring device 12 are realized by a processing circuit 51. The processing circuit 51 may be dedicated hardware as shown in FIG. 13A , or may be a CPU (also referred to as a central processing unit, processing unit, calculation unit, microprocessor, microcomputer, processor, or DSP (Digital Signal Processor)) 52 that executes a program stored in a memory 53 as shown in FIG. 13B .

[0076] When the processing circuitry 51 is dedicated hardware, the processing circuitry 51 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination of these. The functions of each of the moving body reflection component extraction unit 1201, the profile distribution generation unit 1202, the profile feature extraction unit 1203, and the calculation unit 1204 may be realized individually by the processing circuitry 51, or the functions of each unit may be realized collectively by the processing circuitry 51.

[0077] When the processing circuitry 51 is a CPU 52, the functions of the moving body reflection component extraction unit 1201, the profile distribution generation unit 1202, the profile feature extraction unit 1203, and the calculation unit 1204 are realized by software, firmware, or a combination of software and firmware. The software and firmware are written as programs and stored in the memory 53. The processing circuitry 51 realizes the functions of each unit by reading and executing the programs stored in the memory 53. In other words, the monitoring device 12 includes a memory 53 for storing a program that, when executed by the processing circuitry 51, results in the execution of each step shown in FIG. It can also be said that these programs cause a computer to execute the procedures and methods of the moving body reflection component extraction unit 1201, the profile distribution generation unit 1202, the profile feature extraction unit 1203, and the calculation unit 1204. Here, examples of the memory 53 include non-volatile or volatile semiconductor memories such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable ROM), and EEPROM (Electrically EPROM), as well as magnetic disks, flexible disks, optical disks, compact disks, minidisks, and DVDs (Digital Versatile Discs).

[0078] It is also possible to realize some of the functions of the moving body reflection component extraction unit 1201, the profile distribution generation unit 1202, the profile feature extraction unit 1203, and the calculation unit 1204 with dedicated hardware and some with software or firmware. For example, the function of the moving body reflection component extraction unit 1201 can be realized by the processing circuitry 51 as dedicated hardware, and the functions of the profile distribution generation unit 1202, the profile feature extraction unit 1203, and the calculation unit 1204 can be realized by the processing circuitry 51 reading out and executing programs stored in the memory 53.

[0079] In this way, the processing circuitry 51 can realize each of the above-described functions by hardware, software, firmware, or a combination of these.

[0080] It should be noted that the embodiments may be freely combined, or any of the components in each embodiment may be modified, or any of the components in each embodiment may be omitted.

[0081] The monitoring device according to the present disclosure is capable of monitoring the presence or absence of moving objects at least either indoors or outdoors with greater accuracy than conventional devices, and is suitable for use as a monitoring device that monitors the presence or absence of moving objects at least either indoors or outdoors.

[0082] REFERENCE SIGNS LIST 1 monitoring system, 11 sensor, 12 monitoring device, 13 control device, 51 processing circuit, 52 CPU, 53 memory, 1201, 1201b moving object reflection component extraction unit, 1202 profile distribution generation unit, 1203 profile feature extraction unit, 1204, 1204b calculation unit.

Claims

1. A monitoring device comprising: a moving object reflection component extraction unit that extracts reflection components caused by a moving object from a signal received by a sensor that transmits a signal and receives a signal reflected by a moving object; a profile distribution generation unit that generates a profile distribution, which is a waveform indicating the relationship between the reception intensity of the reflection component caused by the moving object and the propagation distance or the propagation delay time, based on the reflection components caused by the moving object extracted by the moving object reflection component extraction unit; a profile feature extraction unit that extracts feature amounts related to the waveform shape of the profile distribution based on the profile distribution generated by the profile distribution generation unit; and a calculation unit that performs at least one of the processes of detecting the presence or absence of a moving object at least either indoors or outdoors, or calculating the reliability of the detection of the presence or absence of a moving object, based on the feature amounts extracted by the profile feature extraction unit or changes in the feature amounts over time.

2. The monitoring device according to claim 1, characterized in that the moving object reflection component extraction unit extracts reflection components caused by moving objects from signals received by a plurality of the sensors for each angle of arrival of the signals.

3. A monitoring device according to claim 1 or 2, characterized in that said profile feature extraction section extracts, as a feature amount, a result of frequency analysis of the profile distribution generated by said profile distribution generation section.

4. A monitoring device as claimed in any one of claims 1 to 3, characterized in that the profile feature extraction unit extracts, as a feature, a gradient in a falling section in the profile distribution generated by the profile distribution generation unit.

5. The monitoring device according to claim 4, characterized in that the calculation unit determines that a moving object is present inside the room when the gradient extracted by the profile feature extraction unit is smaller than a predetermined value, and determines that a moving object is present outside the room when the gradient is larger than the predetermined value.

6. A monitoring device according to any one of claims 1 to 5, characterized in that said profile feature extraction section extracts, as a feature amount, a peak position in the profile distribution generated by said profile distribution generation section.

7. A monitoring device as claimed in any one of claims 1 to 6, characterized in that the profile distribution generating unit generates a profile distribution which is a waveform showing the relationship between the received intensity of the reflected component from the moving object and the propagation distance or the propagation delay time for each speed of the moving object.

8. A monitoring device as claimed in any one of claims 1 to 7, characterized in that the calculation unit calculates the reliability of detection of the presence or absence of a moving object based on the feature amount extracted by the profile feature extraction unit.

9. The monitoring device according to claim 8, characterized in that the calculation unit calculates the reliability of detection of the presence or absence of a moving object based on one or more of the features extracted by the profile feature extraction unit, which are the results of frequency analysis of the profile distribution, the gradient in the falling section of the profile distribution, or the peak position in the profile distribution.

10. A monitoring device as claimed in any one of claims 1 to 7, characterized in that the calculation unit calculates the reliability of detection of the presence or absence of a moving object based on the time series changes in the features extracted by the profile feature extraction unit.

11. A monitoring device as claimed in any one of claims 1 to 7, characterized in that the calculation unit calculates the reliability of the detection of the presence or absence of a moving object based on a time series change in the detection of the presence or absence of a moving object.

12. A monitoring method comprising the steps of: a moving object reflection component extraction unit extracting a reflection component caused by a moving object from a signal received by a sensor which transmits a signal and receives a signal reflected by the moving object; a profile distribution generation unit generating a profile distribution which is a waveform indicating the relationship between the reception intensity of the reflection component caused by the moving object and the propagation distance or the propagation delay time based on the reflection component caused by the moving object extracted by the moving object reflection component extraction unit; a profile feature extraction unit extracting a feature amount relating to the waveform shape of the profile distribution based on the profile distribution generated by the profile distribution generation unit; and a calculation unit performing at least one of the processes of detecting the presence or absence of a moving object at least either indoors or outdoors, or calculating the reliability of the detection of the presence or absence of a moving object, based on the feature amount extracted by the profile feature extraction unit or a time-series change in the feature amount.

Images