Obstacle detection device and obstacle detection method

Abstract

To improve the detection accuracy of obstacles with various moving speeds.SOLUTION: An obstacle detection device 1 detects obstacles within a detection target range, including on a track. Specifically, the obstacle detection device performs frequency analysis on a received signal of a reflected wave obtained by transmitting toward the detection target range. This frequency analysis obtains a received signal strength distribution, which indicates the distribution of signal strength of the reflected wave in a speed-distance coordinate system, and a predetermined reference signal strength distribution for background masking. Based on these two signal strength distributions, suspected reflectors are detected and obstacles are identified from among the suspected reflectors. In detecting the suspected reflectors, detection by a first detection method based on a signal strength ratio of each signal strength distribution is first performed. If no suspected reflectors are detected, detection by a second detection method based on a signal strength ratio after an addition process is performed on each reference signal strength distribution to add signal strength of predetermined low signal strength points is performed.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to an obstacle detection device and the like.

Background Art

[0002] As a technology for detecting obstacles on a track, a device that uses a reflected wave obtained by transmitting a radio signal is known. For example, a radar device is also an example of such a device. Forms of such devices include a device installed on the ground (see, for example, Patent Document 1) and a device mounted on a vehicle (see, for example, Patent Document 2).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the case of an obstacle detection device installed on the ground, a predetermined detection target range such as on or near the track is continuously monitored, and an object that enters the detection target range, that is, a moving object, is detected as an obstacle. The moving speeds of obstacles to be detected are various, and it is desired to accurately detect obstacles with any moving speed.

[0005] In addition, since the detection target range is set on the track, in a situation where there are no obstacles, reflected waves from the so-called background such as the ground surface and structures along the line are received. For this reason, a method of detecting an obstacle by comparing the result of signal processing of the received signal of the reflected wave obtained by transmitting a radio signal toward the detection target range with the result of signal processing (which can be said to be background information) in a situation where there are no obstacles is the mainstream. By signal processing of the received signal, the distance and speed of the reflector that generated the reflected wave can be obtained. However, when detecting an obstacle on the track, since the distance between the obstacle and the background is almost equal, there has been a problem that it is particularly difficult to detect an obstacle with a low (slow) moving speed.

[0006] The problem to be solved by the present invention is to improve the detection accuracy of obstacles with various moving speeds.

Means for Solving the Problem

[0007] A first invention for solving the above problem is An obstacle detection device that detects an obstacle moving within the detection target range based on a received signal of a reflected wave obtained by transmitting a radio signal from a predetermined transmission / reception position toward the detection target range, Calculating means (for example, calculation unit 22 in FIG. 21) that performs frequency analysis on the received signal and calculates a received signal intensity distribution indicating the distribution of the signal intensity of the reflected wave in the speed-distance coordinate system; Detection means (for example, detection unit 24 in FIG. 21) that executes a process of detecting a suspected reflector based on the received signal intensity distribution and a predetermined reference signal intensity distribution for the background mask; Determination means (for example, determination unit 36 in FIG. 21) that determines the obstacle from among the suspected reflectors; Comprising The detection means First detection means (for example, first detection unit 26 in FIG. 21) that detects, as the suspected reflector, a set of coordinates at which the signal intensity ratio (for example, "SB ratio" in the embodiment) at corresponding coordinates between the received signal intensity distribution and the reference signal intensity distribution satisfies a first peak condition; A second detection means (for example, the second detection unit 28 in FIG. 21) that detects, as the suspected reflector, an aggregate of coordinates at which a signal intensity ratio (for example, the "corrected SB ratio" in the embodiment) at each corresponding coordinate after an amplification process of amplifying the signal intensity at a predetermined low signal intensity location for the received signal intensity distribution and the reference signal intensity distribution satisfies a second peak condition; having, and performing detection by the second detection means when the detection result by the first detection means satisfies a predetermined malfunction condition, It is an obstacle detection device.

[0008] As another method, An obstacle detection method for detecting an obstacle moving within a detection target range based on a received signal of a reflected wave obtained by transmitting a radio signal from a predetermined transmission / reception position toward the detection target range, comprising: A calculation step (for example, step S1 in FIG. 2) of performing frequency analysis on the received signal to calculate a received signal intensity distribution indicating a distribution of signal intensities of the reflected wave in a velocity-distance coordinate system; A detection step (for example, steps S3 to S9 in FIG. 2) of executing a process of detecting a suspected reflector based on the received signal intensity distribution and a predetermined reference signal intensity distribution for a background mask; A determination step (for example, step S19 in FIG. 2) of determining the obstacle from among the suspected reflectors; including, The detection step includes: A first detection method (for example, step S3 in FIG. 2) of detecting, as the suspected reflector, an aggregate of coordinates at which a signal intensity ratio at each corresponding coordinate between the received signal intensity distribution and the reference signal intensity distribution satisfies a first peak condition; A second detection method (for example, step S7 in FIG. 2) of detecting, as the suspected reflector, an aggregate of coordinates at which a signal intensity ratio at each corresponding coordinate after an amplification process of amplifying the signal intensity at a predetermined low signal intensity location for the received signal intensity distribution and the reference signal intensity distribution satisfies a second peak condition; Among the two detection methods, a step of first performing detection by the first detection method and performing detection by the second detection method when the detection result satisfies a predetermined malfunction condition. A method for detecting an obstacle may be configured.

[0009] According to the first invention or the like, it is possible to improve the detection accuracy of obstacles having various moving speeds. That is, a suspected reflector that is a candidate for an obstacle is detected by two detection methods, a first detection method and a second detection method, based on a received signal intensity distribution indicating a distribution of signal intensities of reflected waves calculated from the received signal and a reference signal intensity distribution for a background mask.

[0010] When the reference signal intensity distribution is the signal intensity distribution of a so-called background where no obstacle exists, the speed of an obstacle with a high (fast) moving speed can be significantly different from the speed of a reflector related to a background mainly composed of stationary objects. Therefore, among the signal intensity ratios at the corresponding coordinates of the received signal intensity distribution and the reference signal intensity distribution, the signal intensity ratio related to the position coordinates of the obstacle may appear large. For this reason, it can be said that the first detection method is suitable.

[0011] On the other hand, since the speed of an obstacle with a low (slow) moving speed is not significantly different from the speed of a reflector related to a background mainly composed of stationary objects, there may be a case where it is difficult for a clear difference to occur between the received signal intensity distribution and the reference signal intensity distribution. For this reason, for each signal intensity distribution, the signal intensity at a location where the signal intensity of the reflected wave is low is increased, for example, to a predetermined intensity. Then, the signal intensity ratio at the corresponding coordinates of the received signal intensity distribution and the reference signal intensity distribution is obtained. By the increasing process of increasing the signal intensity at a predetermined low signal intensity location, it is possible to emphasize the signal intensity ratio related to the position coordinates of an obstacle that is moving while having a low moving speed. This method is the second detection method.

[0012] From these facts, first, detection is performed by the first detection method suitable for detecting an obstacle with a high (fast) moving speed. When a suspected reflector is not detected, detection is performed by the second detection method suitable for detecting an obstacle with a low (slow) moving speed. Thus, a moving obstacle can be accurately detected regardless of its moving speed, and the detection accuracy of the obstacle can be improved.

[0013] The second invention is in the above-mentioned invention, Displacement information calculation means (for example, the displacement information calculation unit 30 in FIG. 21) that calculates the relative position of the suspected reflector with respect to the transmission / reception position based on the coordinates of the suspected reflector in the speed-distance coordinate system and the signal processing result obtained by performing predetermined signal processing on the received signal. It is an obstacle detection device further including the above.

[0014] According to the second invention, since the relative position with respect to the transmission / reception position can be calculated as the position of the suspected reflector, it can be made into an obstacle detection device suitable for practical use.

[0015] The third invention is the above-described invention, The detection means variably sets the first peak condition and / or the second peak condition according to the relative position of the suspected reflector determined as the obstacle by the determination means. It is an obstacle detection device.

[0016] The signal intensity of the received signal of the reflected wave from the suspected reflector tends to increase (become stronger) as the relative position with respect to the transmission / reception position is closer because the attenuation is smaller. Therefore, as in the third invention, by variably setting the first peak condition and the second peak condition, such as variably setting the threshold value for determining the peak of the signal intensity ratio, according to the relative position of the suspected reflector determined as the obstacle, it becomes possible to appropriately detect the suspected reflector. Thereby, it becomes possible to improve the detection accuracy of a moving obstacle.

[0017] The fourth invention is the above-described invention, The transmission / reception position is a fixed position, Each time the detection means detects the suspected reflector, the displacement information calculation means calculates the relative position related to the suspected reflector as the moving position within the detection target range, and calculates the moving speed of the suspected reflector. The determination means, Certainty calculation means for calculating the certainty that the suspected reflector can be determined as the obstacle, based on the moving position and moving speed of the suspected reflector, when a predetermined matching condition indicating that the previous suspected reflector, which was the suspected reflector detected last time by the detection means, and the current suspected reflector, which is the suspected reflector detected this time, are the same is satisfied, the certainty calculation means for improving the certainty. having, and performing control for determining the suspected reflector as the obstacle based on the certainty. It is an obstacle detection device.

[0018] According to the fourth invention, since the transmission / reception position is a fixed position, the relative position and relative moving speed of the suspected reflector with respect to the transmission / reception position become absolute moving position and moving speed. And from the moving position and moving speed, it is possible to determine whether the previously detected suspected reflector (previous suspected reflector) and the currently detected suspected reflector (current suspected reflector) are the same, that is, to track the suspected reflector. Since the obstacle is an object entering the detection target range, the suspected reflector that may be an obstacle should also be moving. Therefore, when a predetermined matching condition indicating that the previous suspected reflector and the current suspected reflector are the same is satisfied, by improving the certainty that the suspected reflector can be determined as the obstacle and determining the obstacle, false detection of the suspected reflector can be avoided, and it is possible to improve the detection accuracy of the moving obstacle.

[0019] The fifth invention is in the above-mentioned invention, prediction means (for example, prediction unit 32 in FIG. 21) for predicting a predicted moving position at which the previous suspected reflector moves based on the moving position and moving speed related to the previous suspected reflector, further comprising, the certainty calculation means determines whether or not the matching condition is satisfied based on the predicted moving position and the moving position related to the current suspected reflector. It is an obstacle detection device.

[0020] According to the fifth invention, it is possible to determine whether or not the coincidence condition is satisfied based on the predicted movement position predicted from the previous movement position and movement speed of the suspected reflector and the current movement position of the suspected reflector. Thereby, it becomes possible to track the suspected reflector, and it becomes possible to improve the detection accuracy of the moving obstacle.

[0021] The sixth invention is the above-mentioned invention, in which a current position prediction update means (for example, the current position prediction update unit 34 in FIG. 21) that changes the movement position related to the current suspected reflector to the predicted movement position predicted by the prediction means, is an obstacle detection device further comprising.

[0022] For example, for a suspected reflector with a small signal intensity ratio with respect to the reference signal intensity distribution, the detection accuracy may not be sufficient. In such a case, as in the sixth invention, by changing the movement position of the current suspected reflector to the predicted movement position, it becomes possible to ensure the accuracy of the position of the suspected reflector.

[0023] The seventh invention is the above-mentioned invention, in which the determination means controls whether or not to determine the suspected reflector as the obstacle based on at least one of the movement speed related to the suspected reflector and the signal intensity ratio related to the suspected reflector. is an obstacle detection device.

[0024] According to the seventh invention, for a suspected reflector with a high movement speed or a large signal intensity ratio with respect to the reference signal intensity distribution, compared with a suspected reflector with a low movement speed or a small signal intensity ratio with respect to the reference signal intensity distribution, it is possible to determine as an obstacle with high accuracy. Thereby, it is possible to improve the detection accuracy of the moving obstacle.

[0025] The eighth invention is the above-mentioned invention, in which The obstacle detection device according to any one of claims 1 to 7, which is installed along a railway line and has a predetermined range on the track as the detection target range.

[0026] According to the eighth invention, it is possible to realize a device installed on the ground to detect obstacles on the track.

Brief Description of the Drawings

[0027]

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Embodiments for Carrying Out the Invention

[0028] Hereinafter, an example of a preferred embodiment of the present invention will be described with reference to the drawings. Note that the applicable forms of the present invention are not limited to the following embodiments. Also, in the description of the drawings, the same reference numerals are given to the same elements.

[0029] FIG. 1 is an application example of the obstacle detection device 1 in the present embodiment. As shown in FIG. 1, the obstacle detection device 1 is installed along the railway and detects obstacles 9 such as people and vehicles moving within a detection target range, which is a predetermined range on the track. Then, the obstacle detection device 1 transmits the detection result of the obstacle to other ground devices such as on-vehicle devices and central devices of trains running in the vicinity by wireless communication or wired communication. As the detection target range, for example, a range including a level crossing can be set as the target range, a range including the track beside the platform can be set as the target range, or a range including the track in a mountainous area where rockfalls and avalanches may occur can be set as the target range.

[0030] The obstacle detection device 1 uses a millimeter-wave radar of the FMCW (Frequency Modulation Continuous Wave) method. It irradiates by transmitting a radio signal, which is an irradiation wave, toward the detection target range via the antenna device 3, and detects an obstacle moving within the detection target range based on the received signal obtained by receiving the reflected wave.

[0031] The obstacle detection device 1 includes, as main functional units, an antenna device 3, a transmission / reception unit 10, and a signal processing unit 20. The transmission / reception unit 10 is an RF (Radio Frequency) unit that transmits a signal obtained by frequency-modulating a continuous wave of a predetermined frequency toward a detection target range via the antenna device 3, and converts the signal of the reflected wave received by the antenna device 3 into an IF (Intermediate Frequency) signal by mixing with the transmission signal, and then performs AD (Analog Digital) conversion to generate reception signal data. In the present embodiment, the obstacle detection device 1 is described as including the antenna device 3, but the antenna device 3 may be configured as a separate device.

[0032] The antenna device 3 is a MIMO (Multi Input Multi Output) array antenna having a plurality of transmission antennas and reception antennas.

[0033] The signal processing unit 20 performs signal processing such as frequency analysis on the reception data generated by the transmission / reception unit 10 to detect the presence or absence of an obstacle.

[0034] The antenna device 3 is installed with its antenna surface facing the detection target range. In the present embodiment, for simplicity of explanation, the antenna surface is a vertical plane perpendicular to the ground surface, a reference point of the antenna surface is the origin O(0,0), a vertical direction with respect to the antenna surface is the Y-axis, and a horizontal direction along the antenna surface is the X-axis, and a rectangular coordinate system (X,Y) parallel to the horizontal plane is defined. The obstacle detection device 1 calculates the position (two-dimensional position) of an object or an obstacle in this rectangular coordinate system (X,Y).

[0035] Although not shown, a plurality of obstacle detection devices 1 are installed at predetermined intervals considering the detection distance along the railway line. To prevent radio wave interference between adjacent obstacle detection devices 1, they are designed such that the polarization of the transmitted waves is different from each other, for example, one transmits vertically polarized waves and the other transmits horizontally polarized waves.

[0036] FIG. 2 is a flowchart for explaining the flow of obstacle detection processing performed by the obstacle detection device 1. This processing is performed by the signal processing unit 20 based on the received data generated by the transmission / reception unit 10. The received data includes data for a continuous number of frames n2 (for example, n2 = 64). The data for one frame includes data for the number of samples n1 (for example, n1 = 256) for each communication channel. The obstacle detection device 1 repeatedly performs this obstacle detection processing to detect the obstacle 9 and track its movement.

[0037] In the obstacle detection processing, first, the received data for one time is subjected to frequency analysis to generate a velocity - distance heat map (step S1). The velocity - distance heat map is a received signal intensity distribution showing the distribution of the signal intensity of the received signal of the reflected wave in the velocity - distance coordinate system. Specifically, as the frequency analysis, the FFT (Fast Fourier Transformation) is performed twice on the received data. That is, the distance FFT (Fast Fourier Transform) is performed on each sample column of the received data to calculate the distribution of the signal intensity with respect to distance. Then, the velocity FFT is performed on each frame column of the received data after the distance FFT to calculate the velocity - distance heat map, which is the signal intensity distribution of velocity - distance.

[0038] FIGS. 3 and 8 are examples of the velocity - distance heat map. As shown in FIGS. 3 and 8, the velocity - distance heat map is a distribution diagram showing the signal intensity at each coordinate of the received signal, which is a reflected wave, in a velocity - distance coordinate system with the horizontal axis (one axis) being velocity and the vertical axis (the other axis) being distance, represented by the shades of black and white. Note that the velocity is the relative velocity with respect to the obstacle detection device 1 when the obstacle detection device 1 moves, but since the obstacle detection device 1 is fixedly installed on the ground, it is the absolute moving speed. Also, the signal intensity of the received signal is the SNR (signal - to - noise ratio).

[0039] Next, the obstacle detection device 1 uses the velocity-distance heatmap, which is the received signal strength distribution, and the background heatmap, which is a predetermined reference signal strength distribution for the background mask, to detect a suspected reflector that may be a reflector as a candidate obstacle that is a candidate for an obstacle (steps S3 to S9).

[0040] The background heatmap is a velocity-distance heatmap in a situation where there are no obstacles in the detection target range and its vicinity. This background heatmap is created, for example, based on the velocity-distance heatmap for a period when no obstacles are detected continuously for a predetermined period (for example, about several minutes). For example, the background heatmap is created based on the average value of the signal strengths at each coordinate. Also, the background heatmap may be updated at a predetermined timing.

[0041] As for the detection of candidate obstacles, first, the detection of candidate obstacles by the first detection method is performed (step S3). When the detection result by the first detection method satisfies a predetermined abnormal condition that no candidate obstacles are detected (step S5: NO), subsequently, the detection of candidate obstacles by the second detection method is performed (step S7).

[0042] Both the first detection method and the second detection method for detecting candidate obstacles perform background removal that removes the signal strength (background signal strength) of the received signal of the reflected wave related to the background from the velocity-distance heatmap using the background heatmap, and extracts the signal strength of the received signal of the reflected wave related to the candidate obstacle, but the background removal methods are different.

[0043] Specifically, the first detection method detects, as candidate obstacles, an aggregate of coordinates where the SB (Signal to background) ratio, which is the ratio of the signal strengths at the corresponding coordinates (distance and velocity) of the velocity-distance heatmap, which is the received signal strength distribution, and the background heatmap, which is the reference signal strength distribution, satisfies the first peak condition. The first peak condition is that it is a peak (maximum point) of the SB ratio and the peak value is equal to or greater than the first threshold value.

[0044] The second detection method performs a predetermined amplification process of increasing the signal intensity at a predetermined low signal intensity location at each corresponding coordinate (distance and moving speed) between the speed-distance heat map which is the received signal intensity distribution and the background heat map which is the reference signal intensity distribution. Then, an SB ratio which is the signal intensity ratio of each coordinate after the amplification process is calculated as a corrected SB ratio, and a set of coordinates for which the corrected SB ratio satisfies the second peak condition is detected as candidate obstacles. The second peak condition is that it is a peak (maximum point) of the corrected SB ratio and the peak value is equal to or greater than the second threshold value.

[0045] The first detection method is suitable for detecting obstacles with a high (fast) moving speed, and the second detection method is suitable for detecting obstacles with a low (slow) moving speed.

[0046] Figs. 3 to 12 are diagrams showing specific detection examples of the first detection method and the second detection method. Figs. 3 to 7 are detection examples for obstacles with a high (fast) moving speed, and Figs. 8 to 12 are detection examples for obstacles with a low (slow) moving speed. Figs. 3 and 8 show the speed-distance heat map which is the received signal intensity distribution, and Figs. 4 and 9 show the background heat map which is the reference signal intensity distribution. In each case, the horizontal axis represents speed, the vertical axis represents distance, and the signal intensity is shown as the SN ratio. Figs. 5 and 10 are graphs of the signal intensity (SN ratio) with respect to speed at a certain distance (22.375488 [m]) in the speed-distance heat maps of Figs. 3 and 8, and Figs. 6 and 11 are graphs of the signal intensity (SN ratio) with respect to speed at a certain distance (the same as Figs. 3 and 8, 22.375488 [m]) in the background heat maps of Figs. 4 and 9. In Figs. 5, 6, 10, and 11, the dotted line indicates the signal intensity (SN ratio) in the heat maps of Figs. 3 and 8. And the dashed line is the signal intensity (SN ratio) after the amplification process by the second detection method with respect to the signal intensity indicated by this dotted line.

[0047] Figures 7 and 12 are graphs of the signal strength ratio (SB ratio) with respect to speed at a certain distance (22.375488 [m]), obtained from the graphs of signal strength (SN ratio) with respect to speed shown in Figures 5, 6, 10, and 11. In the second detection method, it is the corrected SB ratio. The same applies hereinafter. In Figures 7 and 12, the solid line represents the graph of the SB ratio by the first detection method, and the dashed line represents the graph of the corrected SB ratio by the second detection method.

[0048] Looking at the heatmaps shown in Figures 3, 4, 8, and 9, in each case, regardless of the distance, the signal strength (SN ratio) is high near a speed of about 0 [m / s]. This indicates that since the detection target range is on the track, there are some reflectors at any distance, and reflected waves are being received evenly from these.

[0049] Furthermore, looking at the speed - distance heatmap for obstacles with a high (fast) moving speed shown in Figure 3, compared to the background heatmap shown in Figure 4, the signal strength is stronger in the vicinity of a distance of about 20 - 30 [m] and a speed of about 0 - 8 [m / s]. On the other hand, looking at the heatmaps for obstacles with a low (slow) moving speed shown in Figures 8 and 9, the distribution of the signal strength is almost the same.

[0050] In the second detection method, for each of the speed - distance heatmap and the background heatmap, an amplification process is performed to increase the signal strength at predetermined low - signal - strength locations. The low - signal - strength locations can be determined, for example, based on the maximum signal strength of the background heatmap. Specifically, for example, a signal strength that is a predetermined signal strength lower than the maximum signal strength of the background heatmap is set as the low - signal - strength. In the examples of Figures 5, 6, 10, and 11, the signal strength of - 71.42 [dB], which is 25 [dB] lower than the maximum signal strength of - 46.42 [dB] of the background heatmap, is set as the low - signal - strength. Then, the locations below the low - signal - strength are regarded as low - signal - strength locations, and for these low - signal - strength locations, they are uniformly amplified to the low - signal - strength of - 71.42 [dB]. This is the amplification process.

[0051] Since the signal strength in the speed·distance heat map and the background heat map is defined as the signal-to-noise ratio (SN ratio), by calculating the difference between the received signal strength graph shown in FIGS. 5 and 10 and the background signal strength graph shown in FIGS. 6 and 11, the SB ratio graphs shown in FIGS. 7 and 12 can be obtained. That is, in the first detection method, the background signal strength (SN ratio) is subtracted from the received signal strength (SN ratio) indicated by the dotted line to obtain the SB ratio. Similarly, in the second detection method, the background signal strength (SN ratio) after the boosting process indicated by the dashed line is subtracted from the received signal strength (SN ratio) after the boosting process indicated by the dashed line to obtain the corrected SB ratio.

[0052] Then, in the SB ratio graphs shown in FIGS. 7 and 12, a peak whose peak value is equal to or greater than a predetermined threshold is considered to satisfy the peak condition and is detected as a peak corresponding to a candidate obstacle. The speed and distance corresponding to the detected peak become the speed (moving speed) and distance of the corresponding candidate obstacle. The threshold will be described later.

[0053] Looking at the SB ratio graph for the obstacle with a high (fast) moving speed shown in FIG. 7, according to the first detection method, two peaks appear around a speed of approximately 1 - 2 [m / s]. On the other hand, according to the second detection method, two peaks appear around a speed of approximately 0 - 2 [m / s], but the peak values are very small compared to the peaks obtained by the first detection method. In the example of FIG. 7, both of the two peaks obtained by the first detection method have peak values that are equal to or greater than the first threshold, satisfy the first peak condition, and are detected as corresponding to candidate obstacles. That is, two candidate obstacles with distances both being 22.375488 [m] and speeds of approximately 1 [m / s] and 2 [m / s] respectively are detected. The two peaks obtained by the second detection method both have peak values less than the second threshold and do not satisfy the second peak condition. That is, no candidate obstacles are detected by the second detection method.

[0054] Also, looking at the graph of the SB ratio for obstacles with a low (slow) moving speed shown in Fig. 12, according to the first detection method, there is no peak. On the other hand, according to the second detection method, there is one peak near a speed of about 0 [m / s]. In the example of Fig. 12, the peak by the second detection method is detected as corresponding to one candidate obstacle because the peak is equal to or greater than the second threshold and satisfies the second peak condition. That is, a candidate obstacle with a distance of 22.375488 [m] and a speed of about 0 [m / s] is detected. In the first detection method, since no peak satisfying the first peak condition is detected, no candidate obstacle is detected.

[0055] The obstacle detection device 1 is installed along the railway line and mainly uses the area on the track as the detection target range. Therefore, as shown in Figs. 4 and 9, in the background heat map obtained from the received signal for the so-called background where there is no obstacle, the signal intensity (SN ratio) near a speed of 0 [m / s] becomes large over almost all distances, and the signal intensity (SN ratio) at other speeds is very small. For this reason, for obstacles with a high (fast) moving speed, since the signal intensity (SN ratio) at a high speed is large in the speed-distance heat map, the first detection method that takes the difference between the received signal intensity and the background signal intensity is more suitable for detecting obstacles with a high (fast) moving speed.

[0056] On the other hand, for obstacles with a low (slow) moving speed, the signal intensity (SN ratio) at a low speed becomes large. However, it is close to the vicinity of a speed of 0 [m / s] where the signal intensity (SN ratio) becomes large in the background heat map, and its magnitude itself is small compared to the intensity of the received signal of the background, which is a reflector across the entire detection target range (background signal intensity). Therefore, the difference between the received signal intensity and the background signal intensity is small and it is difficult to be detected as a peak of the signal intensity ratio. For this reason, the second detection method that focuses on the vicinity of a speed of 0 [m / s] where the signal intensity becomes large for both and takes the ratio (signal intensity ratio) of only the signal intensity in that vicinity is more suitable for detecting obstacles with a low (slow) moving speed.

[0057] In the background heat map, the signal intensity (signal-to-noise ratio) near a speed of 0 [m / s] is the highest. Therefore, in the second detection method, as an amplification process, a signal intensity that is lower than the maximum signal intensity (signal-to-noise ratio) by a predetermined signal intensity is set as the low signal intensity, and the signal intensity at the low signal intensity location, which is the location below the low signal intensity, is amplified to the low signal intensity.

[0058] In the above Figures 7 and 12, for the sake of simplicity of explanation, graphs of the SB ratio at a certain distance (22.375488 [m]) are shown. However, the SB ratio is obtained for all distances and speeds, and its peak is detected. Figures 13 to 16 are examples of obtaining the SB ratio for all distances and speeds. Figure 13 is a speed-distance heat map for an obstacle with a high (fast) moving speed, and Figure 14 is a background heat map. Figure 15 is the result obtained by the first detection method based on the heat maps of Figures 13 and 14, and Figure 16 is the result obtained by the second detection method based on the heat maps of Figures 13 and 14.

[0059] In Figures 15 and 16, in both cases, in the speed-distance coordinate system with the horizontal axis (one axis) being the speed and the vertical axis (the other axis) being the distance, a distribution diagram showing the SB ratio at each coordinate with black and white shades is presented. The lighter (whiter) the color, the higher the SB ratio. Comparing Figures 15 and 16, the SB ratio is high at approximately the same distance (near about 5 [m]) and speed (near about 1 to 3 [m / s]). However, the result by the first detection method has a much higher SB ratio compared to the result by the second detection method. From this, it can be seen that for an obstacle with a high (fast) moving speed, the first detection method is more suitable.

[0060] Fig. 17 shows an example of a threshold table that defines a first threshold used in the first detection method and a second threshold used in the second detection method. As shown in Fig. 17, both the first threshold and the second threshold are determined to be changed from a predetermined reference threshold BT according to the position (specifically, the Y coordinate value) of the obstacle determined in the previous repetition of the obstacle detection process. The threshold is determined to be small when the position of the previous obstacle is far and large when it is close. This is because the attenuation of the signal tends to be smaller as the distance from the obstacle detection device 1 is closer. Also, the first threshold is larger than the second threshold. This is because, as shown in Figs. 15 and 16, an obstacle with a higher (faster) moving speed tends to have a larger SB ratio than an obstacle with a lower (slower) moving speed.

[0061] Figs. 18 and 19 are examples in which only SB ratios equal to or higher than a threshold (since Fig. 15 is the result of the first detection method, the first threshold) are extracted for the SB ratio shown in Fig. 15. The SB ratio is shown by the black-and-white shading, and the whiter (lighter) it is, the larger the SB ratio. For the sake of explanation, the threshold below the threshold is set to 0 [dB] (the minimum value). That is, the white part represents the part where the SB ratio is equal to or higher than the threshold. Fig. 18 is an example where the threshold is not changed from the reference threshold BT, and Fig. 19 is an example where the threshold is changed to a value 5 [dB] or higher from the reference threshold BT according to the threshold table shown in Fig. 17 according to the position of the obstacle determined in the previous repetition of the obstacle detection process (assuming a position close to around 5 [m] from the position of the current candidate obstacle).

[0062] Comparing Figs. 18 and 19, the case where the threshold is changed (Fig. 19) extracts more parts with a larger SB ratio than the case where it is not changed (Fig. 18). Peaks with larger peak values and corresponding to reflectors that are likely to be obstacles can be detected as candidate obstacles.

[0063] After detecting a candidate obstacle, the obstacle detection device 1 continues to perform a process of determining whether the candidate obstacle is an obstacle. Returning to the flowchart of the obstacle detection process in FIG. 2, if a candidate obstacle is detected (step S5: YES, S9: YES), the obstacle detection device 1 calculates the position of the detected candidate obstacle (step S11). That is, for the received data after distance FFT, angle FFT is performed on the data of each communication channel corresponding to the position and speed of the candidate obstacle to calculate the angle (azimuth angle) of the candidate obstacle. Then, the position (X, Y) of the candidate obstacle is obtained from the calculated distance and angle.

[0064] If the position (X, Y) of the candidate obstacle can be specified, clustering and tracking of the candidate obstacle are performed to update the tracking list (steps S13 to S17). Specifically, first, when two or more (a plurality of) candidate obstacles are detected, since a plurality of candidate obstacles with approximate positions are considered to be the same object, these are clustered (aggregated) into one candidate obstacle. Then, based on their positions and speeds, for example, the average position and average speed are set as the position and speed of the candidate obstacle after clustering (step S13).

[0065] FIG. 20 is a diagram for explaining the update of the tracking list. In FIG. 20, the list (list) of candidate obstacles detected in the current iteration process of the obstacle detection process is shown on the upper side. In FIG. 20, four candidate obstacles (numbers "11" to "14") are detected. All of them have approximate positions (X, Y) and are clustered into one candidate obstacle (number "11").

[0066] Subsequently, tracking is performed to determine whether the detected candidate obstacle is the same as the candidate obstacle detected up to the previous iteration of the obstacle detection process (step S15). The candidate obstacles up to the previous time are stored as a tracking list. For each of the candidate obstacles up to the previous time in the tracking list, the current position (current predicted position) is predicted from its position (previous position) and speed (previous speed). Then, it is determined whether the position of the candidate obstacle detected this time satisfies a matching condition indicating that it is approximated to any of the current predicted positions of the candidate obstacles up to the previous time. If the matching condition is satisfied, it is assumed that the candidate obstacle this time is the same as the candidate obstacle previous time and can be tracked.

[0067] In FIG. 20, the tracking list up to the previous time is shown in the center. In the example of FIG. 20, four candidate obstacles (numbers "1" to "4") are stored in the tracking list up to the previous time. Among these previous candidate obstacles, the position (X = 1.0, Y = 4.6) of the candidate obstacle numbered "2" is predicted. The current predicted position (X = 1.0, Y = 4.6) of this candidate obstacle numbered "2" is approximated to the position (X = 1.0, Y = 4.6) of the candidate obstacle detected this time (one candidate obstacle (number "11") after clustering into one), and satisfies the matching condition. That is, it is being tracked as the same candidate obstacle.

[0068] Subsequently, based on the result of tracking and the like, addition and scoring of candidate obstacles are performed to update the tracking list (step S17). That is, first, for each of the candidate obstacles in the tracking list up to the previous time that have been tracked as the same as the candidate obstacle detected this time, their position, speed, and SB ratio are updated to the position, speed, and SB ratio of the candidate obstacle detected this time. Here, the SB ratio is the SB ratio of the peak detected as corresponding at the time of detection of the candidate obstacle (the corresponding peak value in FIGS. 7 and 12).

[0069] For candidate obstacles with a small SB ratio (equal to or less than a predetermined value), their positions may be updated to the predicted position (X, Y) this time. This is because the difference from the signal strength related to the background is small, and it is considered highly likely that they are part of the background.

[0070] Next, scoring is performed for the candidate obstacles in the tracking list up to the previous time. Specifically, among the candidate obstacles in the tracking list up to the previous time, for those that are tracked as the same as the candidate obstacles detected this time, scores are added (for example, +1), and for those that are not tracked, scores are subtracted (for example, -1). Then, among the candidate obstacles detected this time, those that are not considered the same as (not tracked as) the candidate obstacles in the tracking list up to the previous time are regarded as new candidate obstacles, and scores are set to the initial value "0" and added to the tracking list. Further, for the candidate obstacles in the tracking list, for those with a high speed (fast: equal to or higher than a predetermined speed), bonus scores are added (for example, +3). Also, for those with a high SB ratio (equal to or higher than a predetermined value), bonus scores are added (for example, +3). The score represents the probability of being able to determine an obstacle. As a result, it is updated as the current tracking list.

[0071] In the example of FIG. 20, the candidate obstacle numbered "2" in the tracking list up to the previous time is tracked as the same candidate obstacle as the candidate obstacle detected this time (after clustering), and its position (X = 1.0, Y = 4.3), speed (= 1.0), and SB ratio (= 40) are updated to the position (X = 1.0221, Y = 5.1773), speed (= 1.1945), and SB ratio (= 50.03147) of the candidate obstacle detected this time. Also, because it is being tracked, the score is increased by "1", and because the SB ratio is high, a bonus score of "3" is added, resulting in a total score increase of "4". Also, for the other three candidate obstacles (numbered "1", "3", "4") in the tracking list up to the previous time, since the same candidate obstacles are not detected in this detection, the scores are each decreased by "1".

[0072] When the tracking list is updated, one candidate obstacle with the highest score among the candidate obstacles in the updated tracking list is determined as the obstacle detected this time (step S19). In the example of FIG. 20, since the score of the candidate obstacle numbered "2" in the current tracking list is the highest value "34", this is determined as the obstacle detected this time. When the above processing is performed, the obstacle detection processing for one set of received data is completed.

[0073] Next, the functional configuration of the obstacle detection device 1 will be described. FIG. 21 is a diagram for explaining an example of the functional configuration of the obstacle detection device 1. The obstacle detection device 1 includes an antenna device 3, a transmission / reception unit 10, a signal processing unit 20, an operation unit 60, a display unit 70, and an output unit 80. The signal processing unit 20 includes a calculation unit 22, a detection unit 24, a displacement information calculation unit 30, a prediction unit 32, a current position prediction update unit 34, and a determination unit 36.

[0074] The calculation unit 22 performs frequency analysis on the received signal of the reflected wave obtained by transmitting a radio signal from a predetermined transmission / reception position toward the detection target range, and calculates a received signal intensity distribution indicating the distribution of the signal intensity of the reflected wave in the velocity-distance coordinate system.

[0075] Specifically, for one set of received data generated by the transmission / reception unit 10, as frequency analysis, FFT (Fast Fourier Transform) (distance FFT) is performed on each sample sequence to calculate the distribution of the signal intensity with respect to distance. Next, FFT (velocity FFT) is performed on each frame sequence of the received data after the distance FFT to calculate a velocity-distance heat map that is the signal intensity distribution of velocity and distance (see FIGS. 3 and 8).

[0076] The detection unit 24 executes a process of detecting a suspected reflector based on the received signal strength distribution and a predetermined reference signal strength distribution for the background mask. The detection unit 24 also includes a first detection unit 26 and a second detection unit 28, and performs detection by the second detection unit 28 when the detection result by the first detection unit 26 satisfies a predetermined abnormal condition. The first detection unit 26 detects, as a suspected reflector, an aggregate of coordinates where the signal strength ratio at each corresponding coordinate between the received signal strength distribution and the reference signal strength distribution satisfies a first peak condition. The second detection unit 28 detects, as a suspected reflector, an aggregate of coordinates where the signal strength ratio at each corresponding coordinate after an amplification process of increasing the signal strength at a predetermined low signal strength portion for the received signal strength distribution and the reference signal strength distribution satisfies a second peak condition. The detection unit 24 variably sets the first peak condition and / or the second peak condition according to the relative position of the suspected reflector determined to be an obstacle by the determination unit 36.

[0077] Specifically, using the velocity-distance heatmap which is the received signal strength distribution and the background heatmap which is the reference signal strength distribution, a suspected reflector which might be a reflector is detected as a candidate obstacle which is a candidate for an obstacle. As for the detection of the candidate obstacle, first, detection of the candidate obstacle by the first detection method is performed, and when the detection result by the first detection method satisfies a predetermined abnormal condition such as no candidate obstacle being detected, subsequently, detection of the candidate obstacle by the second detection method is performed (FIGS. 3 to 12). Also, the first threshold value used in the first detection method and the second threshold value used in the second detection method are set according to the position (specifically, the Y coordinate value) of the obstacle determined in the previous iteration of the obstacle detection process executed repeatedly according to a threshold value table (see FIG. 17).

[0078] The displacement information calculation unit 30 calculates the relative position of the suspected reflector with respect to the transmission / reception position based on the coordinates of the suspected reflector in the velocity-distance coordinate system and the signal processing result obtained by performing predetermined signal processing on the received signal. Also, since the transmission / reception position of the wireless signal is a fixed position, each time the detection unit 24 detects a suspected reflector, the displacement information calculation unit 30 calculates the relative position related to the suspected reflector as a moving position within the detection target range and calculates the moving speed of the suspected reflector.

[0079] Specifically, as signal processing, for the received data after distance FFT by the calculation unit 22, an FFT (angle FFT) is performed on the data of each communication channel corresponding to the position and velocity of the candidate obstacle to calculate the angle (azimuth angle) of the candidate obstacle. Then, the position (X, Y) of the candidate obstacle is obtained from the calculated distance and angle (see FIG. 1).

[0080] The prediction unit 32 predicts the predicted movement position where the previous suspected reflector moves based on the movement position and movement velocity related to the previous suspected reflector.

[0081] Specifically, the candidate obstacles up to the previous one, which are the previous suspected reflectors, are stored as a tracking list. For each candidate obstacle up to the previous one in this tracking list, the current position (current predicted position) is predicted from its position (previous position) and velocity (previous velocity) (see FIG. 20).

[0082] The current position prediction update unit 34 changes the movement position related to the current suspected reflector to the predicted movement position predicted by the prediction unit 32.

[0083] Specifically, for example, for candidate obstacles with a small SB ratio (equal to or less than a predetermined value), their positions can be updated to the current predicted position (X, Y) (see FIG. 20).

[0084] The determination unit 36 determines an obstacle from among the suspected reflectors. For example, control is performed to determine whether or not the suspected reflector is an obstacle based on at least one of the movement velocity related to the suspected reflector and the signal intensity ratio related to the suspected reflector.

[0085] Further, the determination unit 36 includes a probability calculation unit 38, and performs control to determine a suspected reflector as an obstacle based on probability. The probability calculation unit 38 calculates the probability that the suspected reflector can be determined as an obstacle. Also, based on the moving position and moving speed of the suspected reflector, when a predetermined matching condition indicating that the previous suspected reflector, which was the suspected reflector detected last time by the detection unit 24, and the current suspected reflector, which is the suspected reflector detected this time, are the same is satisfied, the probability is improved. Also, it is determined whether or not the matching condition is satisfied based on the predicted moving position and the moving position related to the current suspected reflector.

[0086] Specifically, a plurality of candidate obstacles with approximate positions are clustered (aggregated) into one candidate obstacle, and the positions and speeds of the candidate obstacles after clustering are used based on their positions and speeds. Next, it is determined whether or not tracking can be performed based on whether or not a matching condition indicating that the position of the candidate obstacle detected this time is approximated to any of the previous candidate obstacle predicted positions predicted by the prediction unit 32 is satisfied. Then, for the candidate obstacles in the previous tracking list that are tracked with the candidate obstacle detected this time, their positions, speeds, and SB ratios are updated to the positions, speeds, and SB ratios of the candidate obstacle detected this time.

[0087] Subsequently, scoring is performed to set a score representing the probability that a candidate obstacle can be determined as an obstacle. That is, for the candidate obstacles in the previous tracking list, the score is added (for example, +1) or subtracted (for example, -1) according to whether or not they are tracked with the candidate obstacle detected this time. Also, among the candidate obstacles detected this time, those that are not tracked with the candidate obstacles in the previous tracking list are regarded as new candidate obstacles, and the score is set to the initial value 0 and added to the tracking list. Further, for the candidate obstacles in the tracking list, a bonus score is added (for example, +3) to those with high speeds (fast: equal to or higher than a predetermined speed) or high SB ratios (equal to or higher than a predetermined value) (see FIG. 20). Then, one candidate obstacle with the highest score among the candidate obstacles in the tracking list is determined as the obstacle detected this time.

[0088] The operation unit 60 is a functional unit for performing operation inputs to the obstacle detection device 1, and can be configured by a button switch, a keyboard, a touch panel, or the like. The display unit 70 is a display for displaying various types of information. The output unit 80 is configured by a communication unit or the like that transmits and outputs the detection result of the obstacle to other ground devices such as on-vehicle devices and central devices of trains traveling in the vicinity by wireless communication or wired communication.

[0089] [Operational Effects] According to the present embodiment, it is possible to improve the detection accuracy of obstacles with various moving speeds. That is, candidates for candidate obstacles are detected by two types of detection methods, a first detection method and a second detection method, based on a speed-distance heat map that is a received signal intensity distribution showing the distribution of the signal intensity of the reflected wave calculated from the received signal and a background heat map that is a reference signal intensity distribution for the background mask.

[0090] The background heat map is a speed-distance heat map of a so-called background where there are no obstacles. The speed of an obstacle moving at a high (fast) speed can be significantly different from the speed of a reflector related to a background mainly composed of stationary objects. Therefore, if there is a location where an object is moving at a high (fast) speed in the speed-distance heat map, the signal intensity ratio between the speed-distance heat map and the background heat map appears large at that location. For this reason, it can be said that the first detection method is suitable.

[0091] On the other hand, since the speed of an obstacle moving at a low (slow) speed is not significantly different from the speed of a reflector related to a background mainly composed of stationary objects, it is difficult for a clear difference to occur between the speed-distance heat map and the background heat map. For this reason, for each heat map, the signal intensity at a location where the signal intensity of the reflected wave is low is increased to a predetermined intensity, for example. Then, the signal intensity ratio at each corresponding coordinate between the speed-distance heat map and the background heat map is obtained. By increasing the signal intensity, it is possible to emphasize the signal intensity ratio related to the position coordinates of an obstacle that is moving while having a low moving speed. This method is the second detection method.

[0092] From these, first, detection is performed by a first detection method suitable for detecting obstacles with a high (fast) moving speed. When a suspected reflector is not detected, detection is performed by a second detection method suitable for detecting obstacles with a low (slow) moving speed. In this way, moving obstacles can be accurately detected regardless of their moving speed, and the detection accuracy of the obstacles can be improved.

[0093] Note that the applicable embodiments of the present invention are not limited to the above-described embodiments, and it goes without saying that they can be appropriately changed without departing from the gist of the present invention.

Explanation of Reference Numerals

[0094] 1... Obstacle detection device 10... Transmission / reception unit 20... Signal processing unit 22... Calculation unit 24... Detection unit 26... First detection unit 28... Second detection unit 30... Displacement information calculation unit 32... Prediction unit 34... Current position prediction update unit 36... Determination unit 38... Accuracy calculation unit 3... Antenna device 9... Obstacle

Claims

1. An obstacle detection device that detects an obstacle moving within the detection target range based on a received signal of a reflected wave obtained by transmitting a radio signal from a predetermined transmission / reception position toward the detection target range, a calculation means that performs frequency analysis on the received signal and calculates a received signal intensity distribution indicating the distribution of the signal intensity of the reflected wave in the velocity-distance coordinate system; a detection means that executes a process of detecting a suspected reflector based on the received signal intensity distribution and a predetermined reference signal intensity distribution for a background mask; a determination means that determines the obstacle from among the suspected reflectors; comprising: the detection means: a first detection means that detects, as the suspected reflector, an aggregate of coordinates at which the signal intensity ratio at corresponding coordinates between the received signal intensity distribution and the reference signal intensity distribution satisfies a first peak condition; a second detection means that detects, as the suspected reflector, an aggregate of coordinates at which the signal intensity ratio at corresponding coordinates after an amplification process of increasing the signal intensity at a predetermined low signal intensity portion of the received signal intensity distribution and the reference signal intensity distribution satisfies a second peak condition; having, and performing detection by the second detection means when the detection result by the first detection means satisfies a predetermined abnormal condition; an obstacle detection device.

2. a displacement information calculation means that calculates a relative position of the suspected reflector with respect to the transmission / reception position based on the coordinates of the suspected reflector in the velocity-distance coordinate system and a signal processing result obtained by performing predetermined signal processing on the received signal; The obstacle detection device according to claim 1, further comprising:

3. The detection means variably sets the first peak condition and / or the second peak condition according to the relative position of the suspected reflector determined to be the obstacle by the determination means. The obstacle detection device according to claim 2.

4. The transmission / reception position is a fixed position, the displacement information calculation means calculates, each time the suspected reflector is detected by the detection means, the relative position related to the suspected reflector as a moving position within the detection target range and calculates the moving speed of the suspected reflector, the determination means: Certainty calculation means for calculating the certainty that the suspected reflector can be determined as the obstacle, based on the moving position and moving speed of the suspected reflector, when a predetermined matching condition indicating that the previous suspected reflector, which was the suspected reflector detected last time by the detection means, and the current suspected reflector, which is the suspected reflector detected this time, are the same is satisfied, the certainty calculation means for improving the certainty; having, and performing control to determine the suspected reflector as the obstacle based on the certainty; The obstacle detection device according to claim 2.

5. Prediction means for predicting a predicted movement position at which the previous suspected reflector moves based on the moving position and moving speed related to the previous suspected reflector; further comprising; The certainty calculation means determines whether or not the matching condition is satisfied based on the predicted movement position and the moving position related to the current suspected reflector. The obstacle detection device according to claim 4.

6. Current position prediction update means for changing the moving position related to the current suspected reflector to the predicted movement position predicted by the prediction means; The obstacle detection device according to claim 5, further comprising.

7. The determination means performs control to determine whether or not to determine the suspected reflector as the obstacle based on at least one of the moving speed related to the suspected reflector and the signal intensity ratio related to the suspected reflector. The obstacle detection device according to claim 4.

8. The obstacle detection device according to any one of claims 1 to 7, which is installed along a railway line and has a predetermined range on the track as the detection target range.

9. An obstacle detection method for detecting an obstacle moving within a detection target range based on a received signal of a reflected wave obtained by transmitting a radio signal from a predetermined transmission / reception position toward the detection target range, comprising: a calculation step of performing frequency analysis on the received signal to calculate a received signal intensity distribution indicating the distribution of the signal intensity of the reflected wave in a speed-distance coordinate system; a detection step of executing a process of detecting a suspected reflector based on the received signal intensity distribution and a predetermined reference signal intensity distribution for a background mask; a determination step of determining the obstacle from among the suspected reflectors; including; The detection step includes: a first detection method of detecting, as the suspected reflector, an aggregate of coordinates at which the signal intensity ratio at each corresponding coordinate between the received signal intensity distribution and the reference signal intensity distribution satisfies a first peak condition; A second detection method for detecting, as the suspected reflector, an aggregate of coordinates at which a signal intensity ratio at each corresponding coordinate after an amplification process of amplifying the signal intensity at a predetermined low signal intensity location for the received signal intensity distribution and the reference signal intensity distribution satisfies a second peak condition; Among the two detection methods, a step of first performing detection by the first detection method and, when the detection result satisfies a predetermined malfunction condition, performing detection by the second detection method; An obstacle detection method.

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