Target object point cloud data generation method and device, radar equipment

Abstract

The application relates to a target object point cloud data generation method and device, a radar device, a storage medium and a computer program product. The method comprises the following steps: determining each significant peak point of a target object in a composite range-Doppler map, and determining the point cloud data value of each significant peak point according to the position of each significant peak point in the composite range-Doppler map. For each significant peak point, based on the range-Doppler map corresponding to each target antenna, each directional significant peak point with the same point cloud data value of the significant peak point and different directional angles in the target direction is determined. The target antenna is each receiving antenna corresponding to the target direction. Based on the point cloud data value and the directional angle of each directional significant peak point, the point cloud data of each directional significant peak point is generated. The method can obtain more point cloud data of the target object.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of radar detection, and in particular to a target object point cloud data generation method and device, a radar device, a storage medium and a computer program product. BACKGROUND

[0002] Radar has a wide range of applications, one of which is biological posture detection. By collecting the echo of a living being through a radar, and then analyzing the collected echo signal, the point cloud of the living being can be obtained, so that whether the living being is in a certain posture can be determined according to the position changes of each key detection point of the living being. Taking a human body as an example, by collecting the echo of the human body through a radar, and then analyzing the collected echo signal, the point cloud of the human body can be obtained, so that whether the human body has fallen can be determined according to the height change of the human body.

[0003] In related technologies, the number of biological point cloud data obtained is relatively single, which leads to a low accuracy of the detection result when determining the biological posture. SUMMARY

[0004] Therefore, it is necessary to provide a target object point cloud data generation method and device, a radar device, a computer readable storage medium and a computer program product capable of improving the accuracy of biological posture detection.

[0005] In a first aspect, the present application provides a target object point cloud data generation method. The method comprises:

[0006] determining each significant peak point of a target object in a composite range-Doppler map, and determining the point cloud data value of each significant peak point according to the position of each significant peak point in the composite range-Doppler map; the composite range-Doppler map is obtained by summing the range-Doppler maps corresponding to a plurality of receiving antennas, and the receiving antennas include at least a plurality of receiving antennas in different directions;

[0007] For each significant peak point, based on the range-Doppler maps corresponding to each target antenna, determining each directional significant peak point with the same point cloud data value as the significant peak point and different directional angles in the target direction; the target antenna is each receiving antenna corresponding to the target direction;

[0008] generating the point cloud data of each directional significant peak point based on the point cloud data value and the directional angle of each directional significant peak point.

[0009] In one embodiment, the method further comprises:

[0010] For each of the significant peak points, based on the position index of the significant peak point in the compound range-Doppler map, the power value of the significant peak point in each of the range-Doppler maps corresponding to the target antenna is queried;

[0011] The fast Fourier transform is performed on each of the power values to obtain a power distribution spectrum of the significant peak point in the target direction;

[0012] Among each of the peak points in the power distribution spectrum, a peak point meeting a requirement is taken as a direction significant peak point in the target direction.

[0013] In one of the embodiments, among each of the peak points in the power distribution spectrum, a peak point meeting a preset peak condition is taken as a direction significant peak point, including:

[0014] A maximum peak point is determined among each of the peak points in the power distribution spectrum;

[0015] According to the power value corresponding to the maximum peak point, a threshold power value corresponding to the significant peak point is determined;

[0016] Based on the threshold power value, among each of the peak points in the power distribution spectrum, a peak point meeting a preset peak condition is determined as a direction significant peak point.

[0017] In one of the embodiments, based on the threshold power value, among each of the peak points in the power distribution spectrum, a peak point meeting a preset peak condition is determined as a direction significant peak point, including:

[0018] Among each of the peak points in the power distribution spectrum, a peak point with a power value higher than the threshold power value in the target direction is searched, and the peak point with the power value higher than the threshold power value is taken as a direction significant peak point.

[0019] In one of the embodiments, based on the threshold power value, among each of the peak points in the power distribution spectrum, a peak point meeting a preset peak condition is determined as a direction significant peak point, including:

[0020] In the power distribution spectrum, the power value corresponding to each of the peak points is traversed until all the peak points are traversed or the number of direction significant peak points is higher than a preset number threshold;

[0021] For each of the peak points, in a case where the power value of the peak point is higher than the threshold power value, the peak point is taken as a direction significant peak point, and the number of direction significant peak points is increased by one.

[0022] In one of the embodiments, the receiving antennas include horizontal receiving antennas and vertical receiving antennas; in the case that the target direction is a vertical direction, the target antenna is the vertical receiving antenna; the direction angle is a pitch angle; the method further includes:

[0023] For each of the significant peak points, based on the distance-Doppler diagram corresponding to each of the horizontal receiving antennas, a direction angle corresponding to the significant peak point is determined, and the direction angle is taken as the point cloud data value corresponding to the significant peak point;

[0024] The method of determining, for each of the significant peak points, each direction significant peak point having the same point cloud data value as the significant peak point and different direction angle in the target direction based on the distance-Doppler diagram corresponding to each of the target antennas includes:

[0025] For each of the significant peak points, based on the distance-Doppler diagram corresponding to each of the vertical receiving antennas, each direction significant peak point having the same point cloud data value as the significant peak point and different pitch angle in the vertical direction is determined.

[0026] In one of the embodiments, the receiving antennas include horizontal receiving antennas and vertical receiving antennas; in the case that the target direction is a horizontal direction; the target antenna is the horizontal receiving antenna; the horizontal direction is an azimuth angle; the method further includes:

[0027] For each of the significant peak points, based on the distance-Doppler diagram corresponding to each of the vertical receiving antennas, a pitch angle corresponding to the significant peak point is determined, and the pitch angle is taken as the point cloud data value corresponding to the significant peak point;

[0028] The method of determining, for each of the significant peak points, each direction significant peak point having the same point cloud data value as the significant peak point and different direction angle in the target direction based on the distance-Doppler diagram corresponding to each of the target antennas includes:

[0029] For each of the significant peak points, based on the distance-Doppler diagram corresponding to each of the horizontal receiving antennas, each direction significant peak point having the same point cloud data value as the significant peak point and different azimuth angle in the horizontal direction is determined.

[0030] In a second aspect, the application further provides a target object point cloud data generation device. The device includes:

[0031] The significant peak point determination module is configured to determine each significant peak point of the target object in a composite range-Doppler map, and determine a point cloud data value of each significant peak point according to a position of each significant peak point in the composite range-Doppler map; the composite range-Doppler map is obtained by summing range-Doppler maps corresponding to a plurality of receiving antennas, and the receiving antennas at least include a plurality of receiving antennas in different directions;

[0032] The direction significant peak point determination module is configured to, for each significant peak point, determine each direction significant peak point with the same point cloud data value of the significant peak point and different direction angles in a target direction based on range-Doppler maps corresponding to target antennas; the target antennas are each receiving antenna corresponding to the target direction;

[0033] The generation module is configured to generate point cloud data of each direction significant peak point based on the point cloud data value and the direction angle of each direction significant peak point.

[0034] In a third aspect, the present application further provides a radar device. The radar device comprises a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0035] The significant peak point determination module is configured to determine each significant peak point of the target object in a composite range-Doppler map, and determine a point cloud data value of each significant peak point according to a position of each significant peak point in the composite range-Doppler map; the composite range-Doppler map is obtained by summing range-Doppler maps corresponding to a plurality of receiving antennas, and the receiving antennas at least include a plurality of receiving antennas in different directions;

[0036] The direction significant peak point determination module is configured to, for each significant peak point, determine each direction significant peak point with the same point cloud data value of the significant peak point and different direction angles in a target direction based on range-Doppler maps corresponding to target antennas; the target antennas are each receiving antenna corresponding to the target direction;

[0037] The generation module is configured to generate point cloud data of each direction significant peak point based on the point cloud data value and the direction angle of each direction significant peak point.

[0038] In a fourth aspect, the present application further provides a computer readable storage medium. The computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the following steps:

[0039] determining each significant peak point of the target object in the composite range-Doppler map, and determining point cloud data values of each significant peak point according to positions of each significant peak point in the composite range-Doppler map; the composite range-Doppler map is obtained by summing range-Doppler maps corresponding to multiple receiving antennas, and the receiving antennas at least include multiple receiving antennas in different directions;

[0040] For each significant peak point, determining each directional significant peak point with the same point cloud data value of the significant peak point and different direction angles in the target direction based on range-Doppler maps corresponding to target antennas; the target antennas are each receiving antenna corresponding to the target direction;

[0041] Generating point cloud data of each directional significant peak point based on the point cloud data value and the direction angle of each directional significant peak point.

[0042] In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the following steps:

[0043] determining each significant peak point of the target object in the composite range-Doppler map, and determining point cloud data values of each significant peak point according to positions of each significant peak point in the composite range-Doppler map; the composite range-Doppler map is obtained by summing range-Doppler maps corresponding to multiple receiving antennas, and the receiving antennas at least include multiple receiving antennas in different directions;

[0044] For each significant peak point, determining each directional significant peak point with the same point cloud data value of the significant peak point and different direction angles in the target direction based on range-Doppler maps corresponding to target antennas; the target antennas are each receiving antenna corresponding to the target direction;

[0045] Generating point cloud data of each directional significant peak point based on the point cloud data value and the direction angle of each directional significant peak point.

[0046] The target object point cloud data generation method, device, radar equipment, storage medium and computer program product described above expand the significant peak points, expand the significant peak points in the target direction with significant characteristics of the target object, so that the originally missed significant peak points are detected, and the point cloud data of the target object in the direction with significant characteristics is enriched. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 A flowchart of a target object point cloud data generation method in one embodiment;

[0048] Figure 2This is a schematic diagram showing the distribution of receiving antennas in one embodiment;

[0049] Figure 3 This is a schematic diagram of the power distribution spectrum in the target direction in one embodiment;

[0050] Figure 4 This is a flowchart illustrating the method for generating point cloud data of a target object in another embodiment;

[0051] Figure 5 This is a structural block diagram of the target object point cloud data generation device in another embodiment;

[0052] Figure 6 This is an internal structural diagram of a radar device in one embodiment. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0054] In related technologies, the amount of biological point cloud data acquired is relatively limited, resulting in low accuracy of detection results when determining biological posture.

[0055] Taking the human body as an example, fall detection requires analyzing the echoes from the human body to obtain a point cloud. Since the height of the point cloud is needed to determine whether a fall has occurred, the azimuth and pitch angles of the point cloud are required. The pitch angle is particularly important for height determination; obtaining more information in the pitch dimension will greatly improve the accuracy of fall detection.

[0056] In radar signal processing algorithms, the general approach is to first obtain a significant peak point and then directly determine its azimuth and elevation angles. The azimuth and elevation angles are the maximum peak points on their respective power distribution spectra. This method is simple to calculate and easy to implement. However, in human fall detection applications, due to the characteristics of the human target, the head, chest, legs, etc., constitute multiple radar scattering points. These scattering points are located at the same azimuth angle but different elevation angles relative to the radar. In other words, the point cloud obtained by the above method can only represent the elevation angle of the strongest scattering point, while the point clouds corresponding to other scattering points will be missed or ignored. Selecting the strongest scattering point as the feature point of the human body, which constitutes multiple radar scattering points such as the head, chest, and legs, will result in insufficient information in the elevation dimension of the point cloud, increasing the difficulty of fall detection.

[0057] The same applies to other horizontal creatures or targets; only the strongest scattering point among multiple horizontal scattering points will be detected, and other scattering points will be ignored.

[0058] Based on this, the application provides a target object point cloud data generation method, determines each significant peak point of the target object in a composite range-Doppler map, and determines the point cloud data value of each significant peak point according to the position of each significant peak point in the composite range-Doppler map. Wherein, the composite range-Doppler map is obtained by summing the range-Doppler maps corresponding to multiple receiving antennas, and the receiving antennas at least include multiple receiving antennas in different directions. For each significant peak point, based on the range-Doppler map corresponding to each target antenna, each directional significant peak point with the same point cloud data value as the significant peak point and different directional angles in the target direction is determined. Wherein, the target antenna is each receiving antenna corresponding to the target direction. Based on the point cloud data value and the directional angle of each directional significant peak point, the point cloud data of each directional significant peak point is generated.

[0059] Through the target object point cloud data generation method of the application, the significant peak points are expanded in the target direction where the characteristics of the target object are significant, so that the originally missed significant peak points are detected, and the point cloud data of the target object in the direction where the characteristics are significant is enriched. Based on this, the point cloud data generated by the method of the application is used for posture detection, and since the point cloud data is more abundant, the posture detection is more accurate.

[0060] The application provides a target object point cloud data generation method, and a target object point cloud data generation device, a radar device, a computer readable storage medium, and a computer program product corresponding thereto. First, the target object point cloud data generation method provided by the application is described in detail.

[0061] In one embodiment, as shown in Figure 1 A target object point cloud data generation method is provided, and the embodiment takes the method applied to a radar device as an example for illustration. In the embodiment, the method includes the following steps:

[0062] Step 101, determining each significant peak point of the target object in a composite range-Doppler map, and determining the point cloud data value of each significant peak point according to the position of each significant peak point in the composite range-Doppler map.

[0063] Wherein, the composite range-Doppler map is obtained by summing the range-Doppler maps corresponding to multiple receiving antennas, and the receiving antennas at least include multiple receiving antennas in different directions.

[0064] The target object is different according to different application scenarios. For example, in the application scenario of personnel fall detection, the target object is a person, in the robot motion capture, the target object is a robot, and in other application scenarios, the target object can be a person, an animal, an object, etc.

[0065] As shown in Figure 2 The plurality of receiving antennas are arranged in both horizontal and vertical directions. The horizontal receiving antennas are arranged equidistantly in the horizontal direction, and there is no difference in the vertical direction. The vertical receiving antennas are arranged equidistantly in the vertical direction, and there is no difference in the horizontal direction.

[0066] Specifically, each receiving antenna receives the echo scattered and reflected back by the target object. For the echo received by each receiving antenna, the radar device processes the echo data received by the receiving antenna to obtain the distance-Doppler graph (also referred to as RD graph) corresponding to the receiving antenna. In the distance-Doppler graph, one dimension is velocity and the other dimension is distance. Each point in the graph has a power value. For example, the power value of the echo returned by the object with a distance of A and a velocity of B is C. After the radar device obtains the distance-Doppler graph corresponding to each receiving antenna, the radar device sums the distance-Doppler graphs corresponding to each receiving antenna to obtain a composite distance-Doppler graph. Taking a two-dimensional matrix as an example, each distance-Doppler graph corresponds to a two-dimensional matrix. The horizontal and vertical indices of the two-dimensional matrix represent different distances and velocities, respectively. The elements with the same horizontal index have the same distance / velocity, and the elements with the same vertical index have the same velocity / distance. The value of each element of the matrix represents the power value. Summing the distance-Doppler graphs corresponding to each receiving antenna means summing the two-dimensional matrices of the distance-Doppler graphs. The elements with the same horizontal and vertical indices are added to obtain a two-dimensional matrix, which is the two-dimensional matrix corresponding to the composite distance-Doppler graph.

[0067] After the radar device obtains the composite distance-Doppler graph, the radar device determines each significant peak point of the target object in the composite distance-Doppler graph. For example, the radar device detects the composite distance-Doppler graph using constant false alarm rate (CFAR) to obtain each significant peak point in the composite distance-Doppler graph. As described above, the points at different positions in the composite distance-Doppler graph have different velocities and distances. According to the position of each significant peak point in the composite distance-Doppler graph, the radar device determines the point cloud data value of each significant peak point, including the distance and velocity corresponding to the significant peak point.

[0068] Step 103, for each significant peak point, based on the distance-Doppler graph corresponding to each target antenna, determine each directional significant peak point with the same point cloud data value as the significant peak point and different directional angles in the target direction.

[0069] The target direction is related to the target object, and the target direction is a direction in which the target object is characteristic. For example, the target object is a human body, and the human body has more characteristics in the vertical direction. Therefore, the target direction can be the vertical direction. For another example, the target object is a crocodile, and the crocodile has more characteristics in the horizontal direction. Therefore, the target direction can be the horizontal direction. The receiving antennas are generally distributed in at least two directions, and the target antennas are the receiving antennas corresponding to the target direction. The receiving antennas corresponding to the target direction are generally located on a straight line in the target direction. For example, the receiving antennas corresponding to the horizontal direction are located on a straight line in the horizontal direction, and the receiving antennas corresponding to the vertical direction are located on a straight line in the vertical direction. The positions and numbers of the receiving antennas can be stored in the radar device in advance. The radar device determines the receiving antennas located on the same straight line in the target direction as the target antennas corresponding to the target direction according to the positions and numbers of the receiving antennas. For example, it is assumed that there are receiving antennas 1, 2, 3, 4, 5, 6, and 7. The receiving antennas 1, 2, 3, and 4 are located on the same horizontal line, and the receiving antennas 4, 5, 6, and 7 are located on the same vertical line. If the target direction is the horizontal direction, the target antennas corresponding to the target direction include the receiving antennas 1, 2, 3, and 4.

[0070] Specifically, each significant peak point represents an object including scattering points with the same distance and speed. For example, all scattering points of the central axis of the human body trunk have the same distance and speed, and all scattering points of the central axis of the human body trunk are represented as a significant peak point in the composite range-Doppler diagram. After the radar device determines the significant peak points in the composite range-Doppler diagram, for each significant peak point, the radar device determines, based on the range-Doppler diagram corresponding to each target antenna, each directional significant peak point with the same point cloud data value of the significant peak point and different direction angles in the target direction. That is, on the basis of the significant peak point, the radar device further distinguishes the directional significant peak points corresponding to different direction angles in the target direction.

[0071] It should be noted that the directional significant peak points expanded from the same significant peak point in the target direction have the same point cloud data value but different direction angles. The directional significant peak points expanded from different significant peak points in the target direction have different point cloud data values and may have the same or different direction angles.

[0072] Step 105: generating point cloud data of each directional significant peak point based on the point cloud data value and the direction angle of each directional significant peak point.

[0073] Specifically, after the radar device determines the directional significant peak points, the radar device generates the point cloud data of each directional significant peak point based on the point cloud data value and the direction angle of each directional significant peak point, including the speed, the distance, and the direction angle.

[0074] Wherein, for each direction significant peak point of the same significant peak extension, the speed and distance are the same, but the direction angle is different, for each direction significant peak point of different significant peak extensions, the speed or distance is different.

[0075] In this embodiment, by expanding the significant peak points, the significant peak points in the target direction where the target object is characteristic are expanded, so that the originally missed significant peak points are detected, and the point cloud data of the target object in the direction where the characteristics are significant is enriched. Based on the point cloud data generated by the method of the present application, the pose detection is more accurate because the point cloud data is more abundant.

[0076] In one embodiment, the step 103 specifically includes:

[0077] Step 103A, for each significant peak point, based on the position index of the significant peak point in the composite range-doppler map, the power value of the significant peak point in each range-doppler map is queried in the range-doppler map corresponding to the target antenna.

[0078] Specifically, as described above, each receiving antenna corresponds to a range-doppler map, for each significant peak point, the radar device queries the power value of the significant peak point at the position index in each range-doppler map based on the position index of the significant peak point in the composite range-doppler map, including the distance index and the Doppler index (speed index), in the range-doppler map corresponding to the target antenna.

[0079] Still taking a two-dimensional matrix as an example, after the radar device determines the significant peak point, the position of the significant peak point in the two-dimensional matrix corresponding to the composite range-doppler map can be determined according to the horizontal subscript and the vertical subscript of the significant peak point, and the power value of the horizontal subscript and the vertical subscript of the significant peak point in each range-doppler map is queried in the two-dimensional matrix corresponding to each range-doppler map based on the horizontal subscript and the vertical subscript of the significant peak point.

[0080] Step 103B, performing fast Fourier transform on each power value to obtain the power distribution spectrum of the significant peak point in the target direction.

[0081] Specifically, after the radar device queries the power value of the significant peak point in each range-doppler map corresponding to the target antenna, fast Fourier transform is performed on each power value to obtain the power distribution spectrum of the significant peak point in the target direction, as shown in Figure 3 The longitudinal coordinate is the power value, and the horizontal coordinate is the direction angle in the target direction.

[0082] Step 103C, among the peak points in the power distribution spectrum, the peak point meeting the preset expansion condition is taken as a direction significant peak point in the target direction.

[0083] The direction angle of the direction significant peak point is the direction angle corresponding to the horizontal coordinate value of the peak point in the power distribution spectrum. The peak point refers to the power value of the point being higher than the power values of the left and right points.

[0084] Specifically, after the power distribution spectrum of the significant peak point in the target direction is obtained through fast Fourier transform, there are multiple peak points. The radar device traverses each peak point in the power distribution spectrum to determine whether the power value of the peak point meets the preset expansion condition, such as whether it is higher than the preset threshold peak value, or whether the number of significant peak points in the current direction of the significant peak point expansion reaches the preset number. If the power value of the peak point meets the preset expansion condition, the peak point is taken as a direction significant peak point in the target direction of the significant peak point expansion. If the power value of the peak point does not meet the preset expansion condition, the peak point is taken as a direction significant peak point in the target direction of the significant peak point expansion.

[0085] In this embodiment, the direction significant peak point expanded by the significant peak point in the target direction is found by generating the power distribution spectrum of the significant peak point in the target direction.

[0086] In one embodiment, the above step 103C specifically includes:

[0087] Step C1, among the peak points in the power distribution spectrum, the maximum peak point is determined.

[0088] Specifically, after the power distribution spectrum of the significant peak point in the target direction is obtained through fast Fourier transform, there are multiple peak points. The radar device traverses each peak point in the power distribution spectrum to compare the power values of the peak points, and determines the peak point with the maximum power value as the maximum peak point.

[0089] Step C2, according to the power value corresponding to the maximum peak point and the threshold adjustment factor, the threshold power value corresponding to the significant peak point is determined.

[0090] The threshold adjustment factor is pre-set according to experience and is not greater than 1.

[0091] Specifically, the power values ​​of multiple strong scattering points of a target object in the target direction will not differ significantly in the power distribution spectrum in the target direction. Therefore, after the radar equipment determines the maximum peak point among the peak points of the power distribution spectrum, it can multiply the power value corresponding to the maximum peak point by a threshold factor to obtain the threshold power value, which can be used as one of the conditions for judging significant peak points in the direction. For example, if the power value corresponding to the maximum peak point is reduced by 15%, the threshold power value is 0.85%, and the power value corresponding to the maximum peak point is A, then the threshold power value is A×0.85.

[0092] Step C3: Based on the threshold power value, among the peak points of the power distribution spectrum, determine the peak points that meet the preset peak conditions as directional significant peak points.

[0093] Specifically, the radar equipment determines the threshold power value corresponding to the significant peak point based on the power value corresponding to the maximum peak point and the threshold adjustment factor. Then, it iterates through all peak points in the power distribution spectrum. Based on the threshold power value and preset peak conditions, it determines whether each peak point in the power distribution spectrum is a directional significant peak point extending in the target direction from the significant peak point. Among all peak points in the power distribution spectrum, peak points that meet the preset peak conditions are obtained. For example, if the power value of a peak point is greater than the threshold power value, that peak point is considered a directional significant peak point; or if the power value of a peak point is greater than the threshold power value and the number of current significant peak points corresponding to that significant peak point is not higher than a preset number threshold, then that peak point is considered a directional significant peak point.

[0094] In this embodiment, a threshold power value is determined by a threshold factor to determine whether to extend the significant peak point in the target direction.

[0095] In one embodiment, step C3 specifically includes:

[0096] Among the peak points of the power distribution spectrum, find the peak points in the target direction where the power value is higher than the threshold power value, and take the peak points where the power value is higher than the threshold power value as the significant peak points in the direction.

[0097] Specifically, after determining the threshold power value, the radar equipment traverses each peak point of the power distribution spectrum, compares the threshold power value with the power value corresponding to each peak point, determines the peak point in the target direction where the power value is higher than the threshold power value, and takes the peak point where the power value is higher than the threshold power value as the significant peak point in the direction.

[0098] In this embodiment, all peak points in the target direction that are above the threshold power value are considered as significant peak points in the extended direction.

[0099] In one embodiment, step C3 specifically includes:

[0100] Step C301, in the power distribution spectrum, traverse the power value corresponding to each peak point until all peak points are traversed or the number of direction significant peak points is higher than the preset number threshold.

[0101] Specifically, in the power distribution spectrum, the radar device traverses the power value corresponding to each peak point and performs step C302. After performing step C302 once, it is determined whether the condition for ending the loop is met, that is, whether all peak points have been traversed or whether the number of direction significant peak points is higher than the preset number threshold.

[0102] Step C302, for each peak point, if the power value of the peak point is higher than the threshold power value, the peak point is taken as a direction significant peak point, and the number of direction significant peak points is increased by one.

[0103] Specifically, after the radar device traverses each peak point, it determines the size of the power value of the peak point and the threshold power value. If the power value of the peak point is higher than the threshold power value, the peak point is taken as a direction significant peak point, and the number of direction significant peak points is increased by one. If the power value of the peak point is not higher than the threshold power value, the next peak point is traversed.

[0104] In this embodiment, a certain number of peak points higher than the threshold power value in the target direction are selected as the direction significant peak points for expansion.

[0105] In one embodiment, if the target object is a human, an ape, or another target object with significant characteristics in the vertical direction, the receiving antenna includes a horizontal receiving antenna and a vertical receiving antenna. In the case where the target direction is the vertical direction, the target antenna is the vertical receiving antenna, and the direction angle is the pitch angle. At this time, the above method can further include:

[0106] Step 107, for each significant peak point, based on the distance-Doppler graph corresponding to each horizontal receiving antenna, determine the azimuth angle corresponding to the significant peak point, and take the azimuth angle as the point cloud data value corresponding to the significant peak point.

[0107] Specifically, when it is determined that the target direction is the vertical direction, the significant peak points need to be expanded in the vertical direction, and there is no need to expand the significant peak points in the horizontal direction. At this time, for each significant peak point, the radar device queries the power value of the significant peak point in each distance-Doppler graph based on the position index of the significant peak point in the composite distance-Doppler graph, in each distance-Doppler graph corresponding to each horizontal receiving antenna, and then performs fast Fourier transform on each power value to obtain the power distribution spectrum (also referred to as the azimuth spectrum) of the significant peak point in the horizontal direction. In each peak point in the power distribution spectrum, the azimuth angle corresponding to the peak point with the maximum power value is taken as the azimuth angle of the significant peak point, and the azimuth angle is taken as the point cloud data value corresponding to the significant peak point.

[0108] At this time, the step 103 specifically includes:

[0109] For each significant peak point, based on the distance-Doppler graph corresponding to each vertical receiving antenna, determine each direction significant peak point with the same point cloud data value of the significant peak point and different elevation angles in the vertical direction.

[0110] Specifically, after the radar device determines each significant peak point in the composite distance-Doppler graph, for each significant peak point, based on the distance-Doppler graph corresponding to each vertical receiving antenna, determine each direction significant peak point with the same point cloud data value of the significant peak point and different elevation angles in the vertical direction, that is, on the basis of the significant peak point, continue to distinguish the direction significant peak point corresponding to different elevation angles in the vertical direction.

[0111] In this embodiment, for the target object with significant characteristics in the vertical direction, the significant peak point is expanded in the vertical direction and not expanded in the horizontal direction.

[0112] In one embodiment, if the target object is a crocodile, a shark or the like with significant characteristics in the vertical direction, the receiving antenna includes a horizontal receiving antenna and a vertical receiving antenna, and in the case where the target direction is the horizontal direction, the target antenna is the horizontal receiving antenna and the horizontal direction is the azimuth angle. The above method can further include:

[0113] Step 109, for each significant peak point, based on the distance-Doppler graph corresponding to each vertical receiving antenna, determine the elevation angle corresponding to the significant peak point, and take the elevation angle as the point cloud data value corresponding to the significant peak point.

[0114] Specifically, in the case where the target direction is the horizontal direction, the significant peak point needs to be expanded in the horizontal direction and does not need to be expanded in the vertical direction. At this time, for each significant peak point, the radar device queries the power value of the significant peak point in each distance-Doppler graph based on the position index of the significant peak point in the composite distance-Doppler graph in each distance-Doppler graph corresponding to each vertical receiving antenna, and then performs fast Fourier transform on each power value to obtain the power distribution spectrum (also referred to as the elevation spectrum) of the significant peak point in the vertical direction. In each peak point in the power distribution spectrum, the elevation angle corresponding to the peak point with the maximum power value is taken as the elevation angle corresponding to the significant peak point, and the elevation angle is taken as the point cloud data value corresponding to the significant peak point.

[0115] At this time, the step 103 specifically includes:

[0116] For each significant peak point, based on the distance-Doppler graph corresponding to each horizontal receiving antenna, determine each direction significant peak point with the same point cloud data value of the significant peak point and different azimuth angles in the horizontal direction.

[0117] Specifically, after the radar device determines each significant peak point in the composite distance-Doppler graph, for each significant peak point, based on the distance-Doppler graph corresponding to each horizontal receiving antenna, determine each direction significant peak point with the same point cloud data value of the significant peak point and different azimuth angles in the horizontal direction, that is, on the basis of the significant peak point, continue to distinguish the direction significant peak point corresponding to different elevation angles in the horizontal direction.

[0118] In this embodiment, for the target object with significant characteristics in the horizontal direction, the significant peak point is expanded in the horizontal direction and not expanded in the vertical direction.

[0119] As Figure 4 shown, a specific implementation of the present application is shown, and the specific embodiment will be described in detail.

[0120] In this embodiment, N_azi receiving antennas are placed in the horizontal direction, N_ele receiving antennas are placed in the vertical direction, and a total of N_all=N_azi+N_ele receiving antennas are placed. Among them, the receiving antennas placed in the horizontal direction are arranged at equal intervals in the horizontal direction and have no difference in the vertical direction; the receiving antennas placed in the vertical direction are arranged at equal intervals in the vertical direction and have no difference in the horizontal direction.

[0121] 401, process the radar echo signal to obtain the distance, velocity, and azimuth angle information of the point cloud.

[0122] (1) Perform two-dimensional FFT processing on the echo data of all N_all receiving antennas to obtain a distance-Doppler graph, also known as an RD graph.

[0123] (2) Perform amplitude summation on the RD graphs of all N_all antennas to obtain an RD_sum graph (the above-mentioned composite distance-Doppler graph).

[0124] (3) Perform two-dimensional CFAR detection on the RD_sum graph to obtain N_temp detection points (the above-mentioned significant peak points), and the index (rangInd, dopplerInd) of each detection point in the RD graph, rangInd is the distance index, and dopplerInd is the Doppler index (also known as the velocity index).

[0125] (4) For each detection point, according to its index (rangeInd, dopplerInd), find the position of the detection point in the RD map corresponding to the receiving antenna placed in all horizontal directions, and N_azi power values can be obtained. Perform FFT calculation on the N_azi numbers with N_azi_fft points to obtain the horizontal direction power distribution spectrum P_azi corresponding to the detection point.

[0126] Where N_azi_fft is an integer power of 2 greater than N_azi, and the typical value is 128.

[0127] (5) Find the horizontal direction peak point with the largest amplitude in the horizontal direction power distribution spectrum P_azi, and record it as the azimuth angle index aziInd of the detection point in the horizontal direction.

[0128] 402, analyze the elevation spectrum (power distribution spectrum in the vertical direction) of each detection point, determine whether to output multiple points, and output the elevation angle of the point.

[0129] (1) Set the total number of detection points N_detect to N_temp, and traverse the N_temp detection points.

[0130] (2) For each detection point, according to its index (rangeInd, dopplerInd), find the position of the detection point in the RD map corresponding to the receiving antenna placed in all vertical directions, and N_ele power values can be obtained. Perform FFT calculation on the N_ele numbers with N_ele_fft points to obtain the vertical direction power distribution spectrum P_ele corresponding to the detection point.

[0131] Where N_ele_fft is an integer power of 2 greater than N_ele, and the typical value is 128.

[0132] (3) Determine the maximum peak point with the largest amplitude in the vertical direction power distribution spectrum P_ele, record it as the elevation angle index eleInd of the detection point in the vertical direction. Initialize the counter count to 0.

[0133] (4) Find the next peak point eleIndTemp of P_ele. Wherein, the amplitude (i.e. power value) P_ele(eleIndTemp) of the point is greater than P_ele(eleIndTemp-1), and also greater than P_ele(eleIndTemp+1).

[0134] (5) If P_ele(eleIndTemp) satisfies the condition: P_ele(eleIndTemp) > thre * P_ele(eleInd), then add one more detection point, bringing the total number of detection points to N_detect = N_detect + 1. Here, thre is the set threshold factor, P_ele(eleInd) is the maximum peak value, and thre * P_ele(eleInd) represents the threshold peak value. The distance index of this detection point is rangeInd, the velocity index is dopplerInd, the azimuth index is aziInd, and the pitch index is eleIndTemp. The counter count is then incremented by 1.

[0135] (6) If count reaches the preset number of vertical peaks searched, countThre, then stop searching for vertical peaks and return to (2) to traverse the next detection point. Otherwise, return to (4) to search for the next peak point.

[0136] 403. Output the distance, speed, azimuth, and elevation angle information for each detection point.

[0137] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0138] Based on the same inventive concept, this application also provides a target object point cloud data generation apparatus for implementing the target object point cloud data generation method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method. Therefore, the specific limitations in one or more target object point cloud data generation apparatus embodiments provided below can be found in the limitations of the target object point cloud data generation method described above, and will not be repeated here.

[0139] In one embodiment, such as Figure 5 As shown, a target object point cloud data generation device is provided, comprising:

[0140] The significant peak point determination module 501 is configured to determine each significant peak point of the target object in a composite range-Doppler map, and determine point cloud data values of the significant peak points according to positions of the significant peak points in the composite range-Doppler map; the composite range-Doppler map is obtained by summing range-Doppler maps corresponding to a plurality of receiving antennas, and the receiving antennas at least include a plurality of receiving antennas in different directions;

[0141] The direction significant peak point determination module 503 is configured to, for each significant peak point, determine, based on range-Doppler maps corresponding to target antennas, direction significant peak points having the same point cloud data value as the significant peak point and different direction angles in a target direction; the target antennas are each receiving antenna corresponding to the target direction;

[0142] The generation module 505 is configured to generate point cloud data of each direction significant peak point based on the point cloud data value and the direction angle of each direction significant peak point.

[0143] In one of the embodiments, the direction significant peak point determination module 503 specifically includes:

[0144] The query unit is configured to, for each significant peak point, query, based on a position index of the significant peak point in the composite range-Doppler map, power values of the significant peak point in each range-Doppler map in the range-Doppler maps corresponding to the target antennas;

[0145] The distribution spectrum generation unit is configured to perform fast Fourier transform on each power value to obtain a power distribution spectrum of the significant peak point in the target direction;

[0146] The screening unit is configured to, among each peak point in the power distribution spectrum, take a peak point meeting a preset peak value condition as a direction significant peak point in the target direction.

[0147] In one of the embodiments, the screening unit specifically includes:

[0148] The maximum peak point determination subunit is configured to determine a maximum peak point among each peak point in the power distribution spectrum;

[0149] The threshold power value determination subunit is configured to determine a threshold power value corresponding to the significant peak point according to a power value corresponding to the maximum peak point and a threshold adjustment factor;

[0150] The expansion subunit is configured to, based on the threshold power value, determine, among each peak point in the power distribution spectrum, a peak point meeting a preset peak value condition as a direction significant peak point.

[0151] In one of the embodiments, the extension subunit is specifically used for:

[0152] In each peak point of the power distribution spectrum, a peak point with a power value higher than the threshold power value in the target direction is searched, and the peak point with the power value higher than the threshold power value is taken as a direction significant peak point.

[0153] In one of the embodiments, the extension subunit is specifically used for:

[0154] In the power distribution spectrum, the power values corresponding to each peak point are traversed until all peak points or the number of direction significant peak points is higher than a preset number threshold;

[0155] For each peak point, if the power value of the peak point is higher than the threshold power value, the peak point is taken as a direction significant peak point, and the number of direction significant peak points is increased by one.

[0156] In one of the embodiments, the receiving antenna includes horizontal receiving antennas and vertical receiving antennas; in the case where the target direction is a vertical direction, the target antenna is the vertical receiving antenna; the direction angle is a pitch angle; and the device further includes:

[0157] An azimuth angle determination module is configured to, for each significant peak point, determine an azimuth angle corresponding to the significant peak point based on the distance-Doppler graph corresponding to each horizontal receiving antenna, and take the azimuth angle as the point cloud data value corresponding to the significant peak point.

[0158] At this time, the direction significant peak point determination module 503 is specifically used for:

[0159] For each significant peak point, the direction significant peak points with the same point cloud data value as the significant peak point and different pitch angles in the vertical direction are determined based on the distance-Doppler graph corresponding to each vertical receiving antenna.

[0160] In one of the embodiments, the receiving antenna includes horizontal receiving antennas and vertical receiving antennas; in the case where the target direction is a horizontal direction; the target antenna is the horizontal receiving antenna; the horizontal direction is an azimuth angle; and the device further includes:

[0161] A pitch angle determination module is configured to, for each significant peak point, determine a pitch angle corresponding to the significant peak point based on the distance-Doppler graph corresponding to each vertical receiving antenna, and take the pitch angle as the point cloud data value corresponding to the significant peak point.

[0162] At this time, the direction significant peak point determination module 503 is specifically used for:

[0163] For each of the significant peak points, based on the distance-Doppler diagram corresponding to each of the horizontal receiving antennas, a direction significant peak point with the same point cloud data value of the significant peak point and different azimuth angle in the horizontal direction is determined.

[0164] The modules in the target object point cloud data generation apparatus can be implemented by software, hardware, or a combination thereof. The modules can be embedded in or independent of a processor in a radar device in hardware form, or stored in a memory in the radar device in software form, so as to be invoked and executed by the processor to perform operations corresponding to the modules.

[0165] In an embodiment, a radar device is provided, and an internal structure diagram of the radar device can be as shown in Figure 6 The radar device includes a processor, a memory, and a communication interface connected through a system bus. The processor of the radar device is configured to provide computing and control capabilities. The memory of the radar device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The communication interface of the radar device is configured to perform wired or wireless communication with an external terminal. The wireless communication can be achieved through WIFI, mobile cellular network, NFC (Near Field Communication), or other technologies. The computer program is executed by the processor to implement a target object point cloud data generation method. In addition, the radar device can also have other components of a radar device, such as a signal transmitter and receiving antennas, which are not shown in the figure, and can refer to the description of the structure of the radar device in related technologies.

[0166] Those skilled in the art can understand that Figure 6 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the radar device to which the scheme of the present application is applied. Specifically, the radar device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0167] In an embodiment, a radar device is also provided, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0168] In an embodiment, a computer readable storage medium is provided, which stores a computer program. The computer program is executed by a processor to implement the steps in the above method embodiments.

[0169] In an embodiment, a computer program product is provided, which includes a computer program. The computer program is executed by a processor to implement the steps in the above method embodiments.

[0170] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties.

[0171] It can be understood by those skilled in the art that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. Any reference to memory, database or other medium used in the embodiments provided by the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric memory (Ferroelectric Random Access Memory, FRAM), phase change memory (Phase Change Memory, PCM), graphene memory, etc. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The database involved in the embodiments provided by the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided by the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0172] The technical features of the above embodiments can be combined in any way. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described, but as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0173] The above-described embodiments are merely illustrative of several embodiments of the present application, and the description is relatively specific and detailed, but should not be understood as a limitation on the scope of the patent. It should be noted that for those skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the scope of the present application. Therefore, the scope of protection of the present application should be subject to the appended claims.

Claims

1. A method for generating point cloud data of a target object, characterized in that, The method includes: In the composite range-Doppler map, significant peak points of the target object are identified, and point cloud data values ​​of each significant peak point are determined based on their positions in the composite range-Doppler map. The composite range-Doppler map is obtained by summing the range-Doppler maps corresponding to multiple receiving antennas, wherein the receiving antennas include at least two receiving antennas in different directions. The range-Doppler map corresponding to each receiving antenna includes echo data of the target object received, wherein the echo data includes at least distance, velocity, and power values. The composite range-Doppler map is obtained by summing the power values ​​corresponding to the same distance and / or the same velocity in the range-Doppler maps corresponding to each receiving antenna. For each significant peak point, based on the range-Doppler map corresponding to each target antenna, significant peak points in each direction with the same point cloud data value as the significant peak point but different azimuth angles in the target direction are determined; the target antennas are the receiving antennas corresponding to the target direction; Point cloud data of each significant peak point in each direction is generated based on the point cloud data value and direction angle.

2. The method according to claim 1, characterized in that, For each significant peak point, based on the range-Doppler map corresponding to each target antenna, the determination of significant peak points in various directions that have the same point cloud data value as the significant peak point but different azimuth angles in the target direction includes: For each significant peak point, based on the position index of the significant peak point in the composite range-Doppler map, query the power value of the significant peak point in each range-Doppler map corresponding to the target antenna; Perform a fast Fourier transform on each of the power values ​​to obtain the power distribution spectrum of the significant peak point in the target direction; Among the peak points in the power distribution spectrum, the peak points that meet the preset expansion conditions are designated as directional significant peak points in the target direction.

3. The method according to claim 2, characterized in that, Among the peak points in the power distribution spectrum, the peak points that meet the preset expansion conditions are designated as directionally significant peak points, including: Among the peak points of the power distribution spectrum, determine the maximum peak point; Based on the power value corresponding to the maximum peak point and the threshold adjustment factor, determine the threshold power value corresponding to the significant peak point; Based on the threshold power value, among the peak points of the power distribution spectrum, the peak points that meet the preset peak conditions are determined as directional significant peak points.

4. The method according to claim 3, characterized in that, Based on the threshold power value, determining the peak points that meet the preset peak conditions as directionally significant peak points among the peak points of the power distribution spectrum includes: Among the peak points of the power distribution spectrum, find the peak point in the target direction where the power value is higher than the threshold power value, and take the peak point where the power value is higher than the threshold power value as the significant peak point in the direction.

5. The method according to claim 3, characterized in that, Based on the threshold power value, determining the peak points that meet the preset peak conditions as directionally significant peak points among the peak points of the power distribution spectrum includes: In the power distribution spectrum, the power values ​​corresponding to each peak point are traversed until all peak points are traversed or the number of directionally significant peak points exceeds a preset threshold. For each peak point, if the power value of the peak point is higher than the threshold power value, the peak point is designated as a directionally significant peak point, and the number of directionally significant peak points is incremented by one.

6. The method according to any one of claims 1-5, characterized in that, The receiving antenna includes a horizontal receiving antenna and a vertical receiving antenna; When the target direction is vertical, the target antenna is the vertical receiving antenna; The orientation angle is a pitch angle; the method further includes: For each significant peak point, the azimuth angle corresponding to the significant peak point is determined based on the range-Doppler map corresponding to each horizontal receiving antenna, and the azimuth angle is used as the point cloud data value corresponding to the significant peak point. For each significant peak point, based on the range-Doppler map corresponding to each target antenna, the determination of significant peak points in various directions that have the same point cloud data value as the significant peak point but different azimuth angles in the target direction includes: For each significant peak point, based on the range-Doppler map corresponding to each of the vertical receiving antennas, significant peak points in each direction with the same point cloud data value as the significant peak point but different pitch angles in the vertical direction are determined.

7. The method according to any one of claims 1-5, characterized in that, The receiving antenna includes a horizontal receiving antenna and a vertical receiving antenna; When the target direction is horizontal; The target antenna is the horizontal receiving antenna; The horizontal direction is the azimuth angle; the method further includes: For each significant peak point, the elevation angle corresponding to the significant peak point is determined based on the range-Doppler map corresponding to each vertical receiving antenna, and the elevation angle is used as the point cloud data value corresponding to the significant peak point; For each significant peak point, based on the range-Doppler map corresponding to each target antenna, the determination of significant peak points in various directions that have the same point cloud data value as the significant peak point but different azimuth angles in the target direction includes: For each significant peak point, based on the range-Doppler map corresponding to each horizontal receiving antenna, significant peak points in each direction with the same point cloud data value as the significant peak point but different azimuth angles in the horizontal direction are determined.

8. A device for generating point cloud data of a target object, characterized in that, The device includes: A significant peak point determination module is used to determine each significant peak point of the target object in a composite range-Doppler image, and to determine the point cloud data value of each significant peak point based on its position in the composite range-Doppler image. The composite range-Doppler image is obtained by summing the range-Doppler images corresponding to multiple receiving antennas, wherein the receiving antennas include at least two receiving antennas in different directions. The range-Doppler image corresponding to each receiving antenna includes echo data received from the target object, wherein the echo data includes at least distance, velocity, and power values. The composite range-Doppler image is obtained by summing the power values ​​corresponding to the same distance and / or the same velocity in the range-Doppler images corresponding to each receiving antenna. The directional significant peak point determination module is used to determine, for each significant peak point, significant peak points in different directions that have the same point cloud data value as the significant peak point but different directional angles in the target direction, based on the range-Doppler map corresponding to each target antenna; the target antennas are the receiving antennas corresponding to the target direction. The generation module is used to generate point cloud data for each of the said significant peak points based on the point cloud data values ​​and direction angles of each of the said significant peak points.

9. A radar device comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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