A method, apparatus, and equipment for determining the yaw rate of a vehicle.

Abstract

This application provides a method, apparatus, and device for determining the yaw rate of a vehicle, comprising: determining multiple reference point clouds of a reference frame; for any point cloud, i.e., a first point cloud, establishing an equation relationship between the energy of the first point cloud and each reference point cloud based on a first distance between the first point cloud and each reference point cloud, and the weight corresponding to each reference point cloud, and determining multiple weights corresponding to the multiple reference point clouds; determining the energy of the second point cloud after rotation based on any point cloud, i.e., a second point cloud, among multiple target point clouds in the current frame, a preset rotation angle, and the weights of the multiple reference point clouds; determining relevant parameters corresponding to the preset rotation angle based on the energies of the multiple second point clouds and the energies of the multiple target point clouds; determining the yaw angle among the multiple preset rotation angles based on the multiple relevant parameters corresponding to the multiple preset rotation angles; and determining the yaw rate of the vehicle based on the yaw angle and the time interval between the current frame and the reference frame.

Description

Technical Field

[0001] This application relates to the field of point cloud processing technology, specifically to a method, apparatus, and equipment for determining the yaw rate of a vehicle. Background Technology

[0002] With the rapid development of intelligent connected vehicles and Advanced Driver Assistance Systems (ADAS), the vehicle's ability to perceive its own motion state is increasingly becoming a core foundation for realizing autonomous driving functions. Among these, yaw rate, as a key parameter describing how fast a vehicle rotates around its vertical axis, is crucial. Errors in estimating the yaw rate can lead to incorrect radar calculations of target position and speed estimations when the vehicle is turning, resulting in target tracking failure.

[0003] Currently, vehicles primarily rely on microelectromechanical systems (MEMS) gyroscopes to directly measure yaw rate. However, MEMS gyroscopes are susceptible to factors such as temperature, mechanical vibration, and electromagnetic interference, leading to errors in the measured yaw rate. Summary of the Invention

[0004] In view of this, this application aims to provide a method, apparatus, and device for determining the yaw rate of a vehicle, so as to improve the accuracy of determining the yaw rate of a vehicle.

[0005] In a first aspect, this application provides a method for determining the yaw rate of a vehicle, the method comprising:

[0006] Multiple reference point clouds are determined for a reference frame, wherein the reference point clouds include: reference point cloud distance, reference azimuth angle, and reference point cloud energy;

[0007] For the first point cloud, based on the first distance between the first point cloud and each of the reference point clouds, and the weight corresponding to each of the reference point clouds, an equation relationship is established with the energy of the first point cloud corresponding to the first point cloud, and the weights corresponding to the multiple reference point clouds are determined respectively. The first point cloud represents any point cloud among the multiple reference point clouds.

[0008] Based on the second point cloud of the current frame, the preset rotation angle, and multiple weights, the energy of the second point cloud corresponding to the rotated second point cloud is determined. The second point cloud represents any point cloud among multiple target point clouds of the current frame. The target point cloud includes: target point cloud energy.

[0009] Based on the energy of multiple second point clouds corresponding to multiple second point clouds and the energy of multiple target point clouds, relevant parameters corresponding to the preset rotation angle are determined. The relevant parameters are used to represent the degree of correlation between the energy of the second point cloud and the energy of the target point cloud.

[0010] Based on the multiple related parameters corresponding to the multiple preset rotation angles, the yaw angle of the vehicle is determined among the multiple preset rotation angles;

[0011] The yaw rate of the vehicle is determined based on the yaw angle and the time interval between the current frame and the reference frame.

[0012] In one possible implementation, establishing an equation relating the energy of the first point cloud to the energy of the first point cloud based on the first distance between the first point cloud and each of the reference point clouds, and the weight corresponding to each of the reference point clouds, and determining the multiple weights corresponding to the multiple reference point clouds respectively, includes:

[0013] Calculate the first distance between the first point cloud and the reference point cloud;

[0014] Determine the first radial basis function for the first distance;

[0015] Calculate the first product of the weights corresponding to the first radial basis function and the reference point cloud;

[0016] Calculate the first sum of the first products of the first point cloud and the multiple reference point clouds, and establish an equation relationship between the first sum and the energy of the first point cloud;

[0017] Based on the multiple equation relationships corresponding to the multiple first point clouds, multiple weights are determined.

[0018] In one possible implementation, calculating the first distance between the first point cloud and the reference point cloud includes:

[0019] Based on the first point cloud distance and the first azimuth angle corresponding to the first point cloud, determine the first rectangular coordinates of the first point cloud;

[0020] Based on the reference point cloud distance and the reference azimuth angle, the reference rectangular coordinates of the reference point cloud are determined;

[0021] The first distance is calculated based on the first rectangular coordinates and the reference rectangular coordinates.

[0022] In one possible implementation, determining the multiple reference point clouds of the reference frame includes:

[0023] Obtain multiple original point clouds of the reference frame;

[0024] Based on the point cloud velocity and the azimuth angle of the original point cloud, the first candidate vehicle speed is determined.

[0025] Based on the median of multiple first candidate vehicle speeds, multiple first candidate vehicle speeds are filtered to obtain multiple second candidate vehicle speeds;

[0026] The target speed of the vehicle is determined based on the median of multiple second candidate vehicle speeds;

[0027] Based on the target vehicle speed and the azimuth angle, determine the static point cloud reference speed;

[0028] When the difference between the point cloud velocity and the static point cloud reference velocity is less than a velocity threshold, the original point cloud is determined to be the reference point cloud.

[0029] In one possible implementation, determining the energy of the second point cloud corresponding to the rotated second point cloud based on the second point cloud of the current frame, a preset rotation angle, and multiple weights includes:

[0030] Obtain the second point cloud distance and the second azimuth angle corresponding to the second point cloud;

[0031] The preset angle is determined based on the second azimuth angle and the preset rotation angle;

[0032] Based on the distance to the second point cloud and the preset angle, determine the second rectangular coordinates corresponding to the rotated second point cloud;

[0033] Based on the second rectangular coordinates, multiple third point clouds are determined within a preset distance range of the rotated second point cloud from among the multiple reference point clouds;

[0034] The energy of the second point cloud is determined based on the second rectangular coordinates, the multiple third rectangular coordinates corresponding to the multiple third point clouds, and the multiple target weights corresponding to the multiple third point clouds.

[0035] In one possible implementation, obtaining the second point cloud distance and the second azimuth angle corresponding to the second point cloud includes:

[0036] Obtain the target point cloud distance and target azimuth angle corresponding to multiple target point clouds in the current frame;

[0037] Based on the target point cloud distance and the target azimuth angle, determine the target's rectangular coordinates;

[0038] The distance traveled is determined based on the target vehicle speed and the time interval.

[0039] Based on the target rectangular coordinates and the moving distance, determine the compensation rectangular coordinates;

[0040] Based on the compensated rectangular coordinates, the distance to the second point cloud and the second azimuth angle are calculated.

[0041] In one possible implementation, determining the energy of the second point cloud based on the second rectangular coordinates, multiple third rectangular coordinates corresponding to multiple third point clouds, and multiple target weights corresponding to multiple third point clouds includes:

[0042] Calculate the second distance between the second rectangular coordinate and the third rectangular coordinate;

[0043] Calculate the second radial basis function for the second distance;

[0044] Calculate the second product of the second radial basis function and the target weight corresponding to the third rectangular coordinate;

[0045] The energy of the second point cloud is obtained by calculating the second sum of the multiple second products corresponding to the multiple third point clouds.

[0046] In one possible implementation, determining the relevant parameters corresponding to the preset rotation angle based on the energy of multiple second point clouds corresponding to multiple second point clouds and the energy of multiple target point clouds includes:

[0047] Calculate the third product between the energy of the second point cloud and the energy of the target point cloud corresponding to the second point cloud;

[0048] The sum of multiple third products is calculated to obtain the relevant parameters.

[0049] Secondly, this application provides an apparatus for determining the yaw rate of a vehicle, the apparatus comprising:

[0050] A point cloud determination unit is used to determine multiple reference point clouds of a reference frame, wherein the reference point clouds include: reference point cloud distance, reference azimuth angle, and reference point cloud energy.

[0051] The weight determination unit is used to establish an equation relationship between the energy of the first point cloud corresponding to the first point cloud and the first distance between the first point cloud and each of the reference point clouds, and the weight corresponding to each of the reference point clouds, for the first point cloud, and to determine the multiple weights corresponding to the multiple reference point clouds respectively, wherein the first point cloud represents any point cloud among the multiple reference point clouds.

[0052] A point cloud energy determination unit is used to determine the energy of the second point cloud corresponding to the rotated second point cloud based on the second point cloud of the current frame, a preset rotation angle, and multiple weights. The second point cloud represents any point cloud among multiple target point clouds of the current frame, and the target point cloud includes: target point cloud energy.

[0053] The relevant parameter determination unit is used to determine the relevant parameters corresponding to the preset rotation angle based on the energy of the second point cloud corresponding to the multiple second point clouds and the energy of the multiple target point clouds. The relevant parameters are used to represent the degree of correlation between the energy of the second point cloud and the energy of the target point cloud.

[0054] An angle determination unit is used to determine the yaw angle of the vehicle among the multiple preset rotation angles based on the multiple related parameters corresponding to the multiple preset rotation angles respectively.

[0055] A yaw rate determination unit is used to determine the yaw rate of the vehicle based on the yaw angle and the time interval between the current frame and the reference frame.

[0056] Thirdly, this application provides an electronic device, the device comprising: a memory and a processor;

[0057] The memory is used to store the relevant program code;

[0058] The processor is used to call the program code to execute the method for determining the yaw rate of a vehicle as described in any of the implementations of the first aspect above.

[0059] Fourthly, this application provides a computer-readable storage medium for storing a computer program for executing the method for determining the yaw rate of a vehicle as described in any implementation of the first aspect above.

[0060] Fifthly, this application provides a computer program product comprising a computer program / instruction, which, when executed by a processor, implements the method for determining the yaw rate of a vehicle as described in any of the implementations of the first aspect.

[0061] In the above implementation of this application, the yaw rate of the vehicle is determined based on point clouds from different frames collected by the radar on the vehicle. Specifically, multiple reference point clouds of a reference frame are first determined. Each reference point cloud includes: reference point cloud distance, reference azimuth angle, and reference point cloud energy, where the energy represents the echo intensity corresponding to the reference point cloud. For any point cloud among the multiple reference point clouds, i.e., the first point cloud, an equation is established with respect to the first point cloud energy based on the first distance between the first point cloud and each reference point cloud, and the weight corresponding to each reference point cloud. Based on this equation, multiple weights corresponding to the multiple reference point clouds are determined. Based on any point cloud among the multiple target point clouds of the current frame, i.e., the second point cloud, and a preset rotation angle and the weights of the multiple reference point clouds, the energy of the second point cloud after rotation is determined. Multiple preset rotation angles can be pre-set to determine the yaw rate of the vehicle. Based on the energy of multiple second point clouds corresponding to multiple second point clouds, and the energy of multiple target point clouds corresponding to multiple target point clouds, relevant parameters corresponding to preset rotation angles are determined. These relevant parameters represent the correlation between the energy of the second point clouds and the energy of the target point clouds. Based on the relevant parameters corresponding to the multiple preset rotation angles, a yaw angle is determined among the multiple preset rotation angles. Then, based on the yaw angle and the time interval between the current frame and the reference frame, the yaw rate of the vehicle is determined. The method provided in this application can calculate the yaw rate of the vehicle using point clouds from different frames acquired by radar, without relying on measurements from MEMS sensors, thus improving the accuracy of determining the yaw rate. Attached Figure Description

[0062] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments provided in this application. For those skilled in the art, other drawings can be obtained based on these drawings.

[0063] Figure 1 A flowchart illustrating a method for determining the yaw rate of a vehicle, provided in an embodiment of this application.

[0064] Figure 2 This is a schematic diagram of a radar coordinate system provided in an embodiment of this application.

[0065] Figure 3 This is a schematic diagram of a device for determining the yaw rate of a vehicle, provided as an embodiment of this application.

[0066] Figure 4 This is a schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0067] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. The described embodiments are merely exemplary implementations of this application and not all implementation methods. Those skilled in the art can obtain other embodiments in conjunction with the embodiments of this application without creative effort, and these embodiments are also within the protection scope of this application.

[0068] With the rapid development of intelligent connected vehicles and Advanced Driver Assistance Systems (ADAS), the vehicle's ability to perceive its own motion state is increasingly becoming a core foundation for realizing autonomous driving functions. Among these, yaw rate, as a key parameter describing how fast a vehicle rotates around its vertical axis, can lead to problems such as incorrect radar position calculation, speed estimation errors, and tracking failures when the vehicle is turning if there are errors in its estimation.

[0069] Currently, vehicles primarily rely on microelectromechanical systems (MEMS) gyroscopes to directly measure yaw rate. However, MEMS gyroscopes are susceptible to factors such as temperature, mechanical vibration, and electromagnetic interference, leading to errors in the measured yaw rate.

[0070] Existing Iterative Closest Point (ICP) algorithms estimate pose (including position and yaw rate) by registering point clouds from different frames acquired by millimeter-wave radar. However, the ICP algorithm requires finding the nearest neighbor of all point clouds in each iteration, resulting in a large computational load during the iteration process. Moreover, the "point-to-point" nearest neighbor matching on which the ICP algorithm relies is prone to errors, affecting the accuracy of the estimated yaw rate.

[0071] Based on this, embodiments of this application provide a method for determining the yaw rate of a vehicle, improving the accuracy of yaw rate determination. Specifically, firstly, multiple reference point clouds of a reference frame are determined. Each reference point cloud includes: reference point cloud distance, reference azimuth angle, and reference point cloud energy, where the reference point cloud energy represents the echo intensity corresponding to the reference point cloud. For any point cloud among the multiple reference point clouds, i.e., the first point cloud, an equation relationship is established with respect to the first point cloud energy based on the first distance between the first point cloud and each reference point cloud, and the weight corresponding to each reference point cloud. Based on this equation relationship, multiple weights corresponding to the multiple reference point clouds are determined. Based on any point cloud among the multiple target point clouds of the current frame, i.e., the second point cloud, and a preset rotation angle and the weights of the multiple reference point clouds, the second point cloud energy corresponding to the rotated second point cloud is determined. Multiple preset rotation angles can be preset to determine the vehicle's yaw rate. Based on the energy of multiple second point clouds corresponding to multiple second point clouds, and the energy of multiple target point clouds corresponding to multiple target point clouds, relevant parameters corresponding to preset rotation angles are determined. These relevant parameters represent the correlation between the energy of the second point clouds and the energy of the target point clouds. Based on the relevant parameters corresponding to the multiple preset rotation angles, a yaw angle is determined among the multiple preset rotation angles. Then, based on the yaw angle and the time interval between the current frame and the reference frame, the yaw rate of the vehicle is determined. The method provided in this application embodiment can utilize point clouds from different frames acquired by radar to calculate the yaw rate of the vehicle, without relying on MEMS sensor measurements, thus improving the accuracy of determining the yaw rate. Compared to the repetitive iterative process of the ICP algorithm, it reduces the computational load. It avoids nearest neighbor matching between "point-to-point" pairs, further improving the accuracy of determining the yaw rate.

[0072] To facilitate understanding of the technical solutions provided in the embodiments of this application, a detailed description will be given below in conjunction with the accompanying drawings.

[0073] See Figure 1 The diagram shown is a flowchart of a method for determining the yaw rate of a vehicle according to an embodiment of this application.

[0074] Alternatively, this method can be executed by a data processing device. This data processing device can be a terminal device or a server.

[0075] The method may include the following steps:

[0076] S101: Determine multiple reference point clouds for the reference frame.

[0077] The reference point cloud is obtained by the radar installed on the vehicle, which collects data on targets in the surrounding environment. The reference frame represents the previous frame of the current frame. The time interval between two adjacent frames is short, and the difference between the point cloud data corresponding to the two frames is small, making subsequent calculations more accurate. Each reference point cloud includes: reference point cloud distance (distance between the reference point cloud and the radar), reference azimuth angle, and reference point cloud energy. The reference point cloud energy can be used to reflect the echo intensity of the target scanned by the radar.

[0078] Before a vehicle leaves the factory, the radar originally installed on the vehicle can acquire data such as yaw rate measured by the vehicle's MEMS gyroscope. In this embodiment, the radar may be installed on the vehicle after it leaves the factory to meet the needs of intelligent driving and other applications. Radar installed after this step may not be able to acquire the vehicle's speed or the data collected by the MEMS gyroscope. Based on the method provided in this embodiment, the vehicle's speed can be estimated solely based on the point cloud data acquired by the radar, and the vehicle's yaw rate can be calculated based on the point cloud data.

[0079] To simplify data processing, this embodiment of the application can filter point clouds belonging to static targets (such as roadblocks, signs, etc.) from the point clouds acquired by radar, ensuring that only the yaw rate generated by vehicle movement is present. Specifically, multiple raw point clouds acquired by the radar in a reference frame can be obtained, and the radar can acquire the point cloud velocity and azimuth of the raw point clouds. These raw point clouds are initially estimated to belong to static targets. Optionally, point clouds belonging to static targets can be initially determined as follows: Among the multiple point clouds acquired by the radar, the point cloud velocities corresponding to the multiple point clouds can be sorted to obtain a point cloud velocity sequence. In the point cloud velocity sequence, the point cloud velocities of dynamic targets are located at both ends of the sequence, and the point cloud velocities of static targets are located in the middle part of the sequence. Therefore, point clouds belonging to static targets, i.e., raw point clouds, can be initially determined.

[0080] If the original point cloud is static, in the radar coordinate system, the original point cloud has a velocity in the opposite direction to the vehicle. The point cloud velocity measured by the radar represents the radial velocity in the radar measurement direction, i.e., the projection of the vehicle's velocity in the radar measurement direction. Therefore, a first candidate vehicle speed can be determined based on the point cloud velocity and the azimuth angle. Specifically, the first candidate vehicle speed is equal to the ratio of the point cloud velocity to the cosine of the azimuth angle.

[0081] See Figure 2 The diagram shown is a schematic representation of a radar coordinate system provided in an embodiment of this application. The point cloud velocity of the original point cloud is represented as v0, and the azimuth angle is represented as... Let the first candidate vehicle speed be represented as v1, then It should be noted that the above calculation process only considers the magnitude of the velocity, not its direction.

[0082] Among multiple first candidate vehicle speeds, there may be values ​​with significant deviations. Therefore, the median of multiple first candidate vehicle speeds can be used to filter them, resulting in multiple more effective second candidate vehicle speeds. That is, a first threshold can be preset; when the difference between a first candidate vehicle speed and the median is less than the first threshold, that first candidate vehicle speed is retained as a second candidate vehicle speed, and multiple second candidate vehicle speeds are obtained in this way. To reduce the impact of deviations, the target vehicle speed can be determined based on the median of the multiple second candidate vehicle speeds. After obtaining the target vehicle speed, the static point cloud reference speed corresponding to the static target's point cloud can be calculated in reverse. That is, the static point cloud reference speed is determined based on the target vehicle speed and azimuth angle. When the difference between the point cloud speed of the original point cloud and the static point cloud reference speed is less than the speed threshold, it indicates that the initially determined original point cloud is the point cloud of the static target, thus determining the original point cloud as the reference point cloud. In this embodiment, the specific value of the speed threshold is not limited and can be determined based on the actual application scenario. For example, the speed threshold can be set to 0.5.

[0083] S102: For the first point cloud, based on the first distance between the first point cloud and each reference point cloud, and the weight corresponding to each reference point cloud, establish an equation relationship with the energy of the first point cloud corresponding to the first point cloud, and determine the multiple weights corresponding to the multiple reference point clouds respectively.

[0084] Here, the first point cloud refers to any one of multiple reference point clouds, and includes the first point cloud distance, the first azimuth angle, and the first point cloud energy. It should be noted that the first point cloud is also a reference point cloud, and the different names are used for the convenience of describing the same object. Therefore, the first point cloud distance is the same as the reference point cloud distance, the first azimuth angle is the same as the reference azimuth angle, and the first point cloud energy is the same as the reference point cloud energy.

[0085] In this embodiment, the weights are used to distinguish different reference point cloud energies corresponding to different reference point clouds, so that reference point clouds with higher confidence have higher weights. The weight of each reference point cloud can be determined based on the first point cloud energies of multiple first point clouds.

[0086] In practice, the main steps include:

[0087] A1: Calculate the first distance between the first point cloud and the reference point cloud.

[0088] The distance can be calculated based on the rectangular coordinates corresponding to different point clouds. The radar can collect the first point cloud distance and first azimuth angle of the first point cloud, representing the distance and azimuth angle in a polar coordinate system. Therefore, the first rectangular coordinate of the first point cloud can be determined based on the transformation relationship between polar and rectangular coordinate systems. That is, the product of the first point cloud distance and the cosine of the first azimuth angle represents the x-coordinate in the first rectangular coordinate system, and the product of the first point cloud distance and the sine of the first azimuth angle represents the y-coordinate. Similarly, based on the reference point cloud distance and reference azimuth angle corresponding to each reference point cloud, the reference rectangular coordinates of the reference point cloud are determined. Then, based on the first rectangular coordinates and the reference rectangular coordinates, the first distance is calculated. For example, the first distance can be the Euclidean distance.

[0089] A2: The first radial basis function that determines the first distance.

[0090] The radial basis function depends only on the radial distance from the point to a center point. In this embodiment, the first radial basis function of the first distance can be expressed as: Where d represents the first distance, It is a constant parameter.

[0091] A3: Calculate the first product of the weights corresponding to the first radial basis function and the reference point cloud.

[0092] Each reference point cloud corresponds to a weight. After obtaining the first radial basis function of the first point cloud and the reference point clouds, the first product of the first radial basis function and the weight corresponding to the reference point cloud is calculated. Since the reference frame includes multiple reference point clouds, a first product can be calculated for the first point cloud and each reference point cloud. Therefore, multiple first products corresponding to multiple reference point clouds can be obtained.

[0093] A4: Calculate the first sum of the first products of the first point cloud and multiple reference point clouds, and establish an equation relationship between the first sum and the energy of the first point cloud.

[0094] Then calculate the first sum of multiple first products, and establish an equation relationship between the first sum and the energy of the first point cloud corresponding to the first point cloud.

[0095] A5: Determine multiple weights based on multiple equation relationships corresponding to multiple first point clouds.

[0096] The first point cloud represents any one of the multiple reference point clouds. In other words, multiple equations can be determined for the multiple first point clouds, and thus multiple weights corresponding to the multiple reference point clouds can be determined based on the multiple equations.

[0097] In practical implementation, it can be done as follows: The reference Cartesian coordinates of the reference point cloud are represented by i = 1, 2, ..., n, indicating that there are n reference point clouds in the reference frame. Let j represent the first rectangular coordinates of the first point cloud. The first point cloud represents any point cloud among multiple reference point clouds, then j = 1, 2, ..., n. Indicating the energy of the first cloud point, then ,in, Indicates the first point cloud With reference point cloud The distance between them, and the multiple equations, can be represented in the following matrix form:

[0098]

[0099] After obtaining multiple weights corresponding to multiple reference point clouds, a radar energy map is essentially obtained. By interpolating any point cloud into the radar energy map, the point cloud energy corresponding to that point cloud can be calculated based on the distance between that point cloud and multiple reference point clouds.

[0100] S103: Based on the second point cloud of the current frame, the preset rotation angle, and multiple weights, determine the energy of the second point cloud corresponding to the rotated second point cloud.

[0101] First, multiple target point clouds acquired by the radar in the current frame can be determined. Each target point cloud includes: target point cloud range, target azimuth angle, and target point cloud energy. The second point cloud represents any one of the multiple target point clouds. Optionally, the multiple target point clouds can be point clouds of static targets. The selection of static target point clouds in the current frame can be described in the above embodiment for determining the static target point clouds of the reference frame, and will not be elaborated here.

[0102] To determine the vehicle's yaw rate, the yaw angle of the vehicle in the reference frame and the current frame can be determined first. Specifically, multiple preset rotation angles can be pre-set to represent the possible yaw angles of the vehicle (radar) between the reference frame and the current frame. After determining the vehicle's yaw angle, the yaw rate is determined based on the time interval between the reference frame and the current frame. Multiple preset rotation angles can be obtained by dividing the preset rotation angle range into preset step sizes.

[0103] Since point cloud energy can be calculated based on multiple reference point clouds of a reference frame, the second point cloud is restored to the corresponding position of the reference frame by a preset rotation angle, and the point cloud energy is calculated using the radar energy map. When the preset rotation angle is exactly the yaw angle, the correlation between the calculated point cloud energy and the second point cloud energy acquired by the radar is the highest.

[0104] In one possible implementation, since the vehicle moves between the reference frame and the current frame, the radar position also moves. Therefore, in order to more accurately restore the position of the second point cloud corresponding to the reference frame, the position of the second point cloud can be compensated based on the vehicle's target speed.

[0105] In practice, after obtaining the target point cloud distance and target azimuth angle corresponding to the target point cloud in the current frame, the target rectangular coordinates are determined based on the target point cloud distance and target azimuth angle. The vehicle (radar) travel distance is determined based on the target vehicle speed and the time interval between the reference frame and the current frame. Compensated rectangular coordinates are determined based on the target rectangular coordinates and the travel distance. The radar's travel distance is assumed to be the vertical axis distance; therefore, only the horizontal coordinate in the target rectangular coordinates needs to be compensated using the travel distance to obtain the horizontal coordinate in the compensated rectangular coordinates. The vertical coordinate in the compensated rectangular coordinates is the same as the vertical coordinate in the target rectangular coordinates. For example, when the vehicle is moving forward, the horizontal coordinate in the compensated rectangular coordinates is equal to the sum of the horizontal coordinate in the target rectangular coordinates and the travel distance. When the vehicle is moving backward, the horizontal coordinate in the compensated rectangular coordinates is equal to the difference between the horizontal coordinate in the target rectangular coordinates and the travel distance. After obtaining the compensated rectangular coordinates, they are converted into a second point cloud distance. Based on the ratio of the vertical to horizontal coordinates of the compensated rectangular coordinates, the tangent function of the second azimuth angle is obtained, thus calculating the second azimuth angle.

[0106] Since multiple preset rotation angles are pre-set, for each preset rotation angle, the preset angle can be determined based on the sum of the second azimuth angle and the preset rotation angle. This preset angle is the azimuth angle of the rotated second point cloud in the reference frame after rotating the second point cloud by the preset rotation angle. Therefore, the second rectangular coordinates corresponding to the rotated second point cloud can be calculated based on the distance to the second point cloud and the preset angle. According to the formula for calculating point cloud energy in the above embodiment, the energy of the second point cloud in the radar energy map can be calculated based on the distance between the second point cloud and multiple reference point clouds, and the weight corresponding to each reference point cloud.

[0107] In one possible implementation, to reduce computational complexity, and because the radial basis function is easily affected by distant points—that is, when the reference point cloud is far from the second point cloud, the calculation of the radial basis function is inaccurate, resulting in inaccurate energy of the second point cloud—multiple third point clouds can be identified from among multiple reference point clouds, within a preset distance range of the rotated second point cloud. For example, this preset distance range can be represented by a distance threshold. For any reference point cloud, if the distance between the reference point cloud and the rotated second point cloud is less than the distance threshold, then the reference point cloud can be identified as a third point cloud, thus allowing for the identification of multiple third point clouds.

[0108] Since the third point cloud belongs to multiple reference point clouds, the target weight corresponding to the third point cloud has already been calculated through the above process. Therefore, the energy of the second point cloud can be determined based on the second rectangular coordinates of the rotated second point cloud, the multiple third rectangular coordinates corresponding to the multiple third point clouds, and the multiple target weights corresponding to the multiple third point clouds.

[0109] In practice, for any third point cloud, firstly, the second distance between the second rectangular coordinates and the third rectangular coordinates of the third point cloud is calculated, and the second radial basis function corresponding to the second distance is determined. Then, the second product of the second radial basis function and the target weight corresponding to the third rectangular coordinates is calculated. Since there are multiple third point clouds, multiple second products can be obtained. The second sum of the multiple second products is calculated as the energy of the second point cloud.

[0110] For example, with Represents the Cartesian coordinates of the target point cloud, where I = 1, 2, ..., m, and there are m target point clouds in the current frame. This represents the second rectangular coordinate of the second point cloud, where the second point cloud represents any point cloud among m target point clouds. Let J represent the energy of the target point cloud corresponding to the second point cloud, where J = 1, 2, ..., m. Indicates the distance to the second cloud point. Indicates the second azimuth angle. Let L represent the third rectangular coordinates of the third point cloud, where L = 1, 2, ..., N, indicating that there are N third point clouds in total. Let T represent the preset rotation angles, where T = 1, 2, ..., M, indicating that there are M preset rotation angles. Then the energy of the second point cloud can be expressed as: .

[0111] S104: Based on the energy of multiple second point clouds corresponding to multiple second point clouds and the energy of multiple target point clouds, determine the relevant parameters corresponding to the preset rotation angle.

[0112] The target point cloud energy is obtained from radar acquisition. The correlation parameter represents the degree of correlation between the second point cloud energy and the target point cloud energy. A larger correlation parameter indicates a higher correlation between the second point cloud energy and the target point cloud energy, and a greater likelihood that the preset rotation angle is the vehicle's yaw angle. Optionally, a third product can be calculated between the second point cloud energy corresponding to the rotated second point cloud and the target point cloud energy corresponding to the second point cloud. The above process describes the calculation of the second point cloud energy. Since the second point cloud represents any one of multiple target point clouds, the second point cloud energy corresponding to multiple second point clouds can be calculated. This yields a third product between the multiple second point cloud energies and their corresponding target point cloud energies. The sum of these multiple third products is then calculated as the correlation parameter.

[0113] As can be seen from the above embodiments, the energy of the second point cloud can be expressed as: , The energy of the target point cloud corresponding to the second point cloud is represented by C( () indicates the preset rotation angle The corresponding relevant parameters, C( )= .

[0114] S105: Based on multiple related parameters corresponding to multiple preset rotation angles, determine the yaw angle of the vehicle among multiple preset rotation angles.

[0115] By presetting multiple rotation angles, multiple related parameters corresponding to each preset rotation angle can be obtained. The maximum value among these parameters can be determined, and the preset rotation angle corresponding to this maximum value is the vehicle's yaw angle.

[0116] S106: Determine the vehicle's yaw rate based on the yaw angle and the time interval between the current frame and the reference frame.

[0117] The yaw rate is obtained by dividing the yaw angle by the time interval between the current frame and the reference frame.

[0118] Based on the method provided in the above embodiments, the yaw rate of a vehicle can be calculated using point clouds from different frames acquired by radar, without relying on measurements from MEMS sensors, thus improving the accuracy of determining the yaw rate. Compared to the repetitive iterative process of existing ICP algorithms, the computational load can be reduced. It also avoids nearest neighbor matching between "point-to-point" data, further improving the accuracy of determining the yaw rate.

[0119] Based on the above method embodiments, this application also provides a device for determining the yaw rate of a vehicle. See also... Figure 3 The diagram shown is a schematic of a device for determining the yaw rate of a vehicle according to an embodiment of this application.

[0120] The device 300 includes:

[0121] Point cloud determination unit 301 is used to determine multiple reference point clouds of a reference frame, wherein the reference point clouds include: reference point cloud distance, reference azimuth angle and reference point cloud energy;

[0122] The weight determination unit 302 is used to establish an equation relationship between the energy of the first point cloud corresponding to the first point cloud and the first distance between the first point cloud and each of the reference point clouds, and the weight corresponding to each of the reference point clouds, for the first point cloud, and determine the multiple weights corresponding to the multiple reference point clouds respectively, wherein the first point cloud represents any point cloud among the multiple reference point clouds.

[0123] Point cloud energy determination unit 303 is used to determine the energy of the second point cloud corresponding to the rotated second point cloud based on the second point cloud of the current frame, a preset rotation angle and multiple weights. The second point cloud represents any point cloud among multiple target point clouds of the current frame. The target point cloud includes: target point cloud energy.

[0124] The relevant parameter determination unit 304 is used to determine the relevant parameters corresponding to the preset rotation angle based on the energy of the second point cloud corresponding to the multiple second point clouds and the energy of the multiple target point clouds. The relevant parameters are used to represent the degree of correlation between the energy of the second point cloud and the energy of the target point cloud.

[0125] Angle determination unit 305 is used to determine the yaw angle of the vehicle among the multiple preset rotation angles based on the multiple related parameters corresponding to the multiple preset rotation angles respectively.

[0126] Yaw rate determination unit 306 is used to determine the yaw rate of the vehicle based on the yaw angle and the time interval between the current frame and the reference frame.

[0127] In one possible implementation, the weight determination unit 302 is configured to: calculate the first distance between the first point cloud and the reference point cloud; determine a first radial basis function for the first distance; calculate a first product of the first radial basis function and the weights corresponding to the reference point cloud; calculate a first sum of a plurality of the first products corresponding to the first point cloud and a plurality of the reference point clouds, and establish an equation relationship between the first sum and the energy of the first point cloud; and determine a plurality of the weights based on the plurality of equation relationships corresponding to the plurality of the first point clouds.

[0128] In one possible implementation, the weight determination unit 302 is used to determine the first rectangular coordinates of the first point cloud based on the first point cloud distance and the first azimuth angle corresponding to the first point cloud; determine the reference rectangular coordinates of the reference point cloud based on the reference point cloud distance and the reference azimuth angle; and calculate the first distance based on the first rectangular coordinates and the reference rectangular coordinates.

[0129] In one possible implementation, the point cloud determination unit 301 is configured to acquire multiple original point clouds of the reference frame; determine a first candidate vehicle speed based on the point cloud velocity and the azimuth angle of the original point clouds; filter the multiple first candidate vehicle speeds based on the median of the multiple first candidate vehicle speeds to obtain multiple second candidate vehicle speeds; determine the target vehicle speed based on the median of the multiple second candidate vehicle speeds; determine a static point cloud reference speed based on the target vehicle speed and the azimuth angle; and determine the original point cloud as the reference point cloud when the difference between the point cloud velocity and the static point cloud reference speed is less than a speed threshold.

[0130] In one possible implementation, the point cloud energy determination unit 303 is used to obtain the second point cloud distance and the second azimuth angle corresponding to the second point cloud; determine a preset angle based on the second azimuth angle and the preset rotation angle; determine the second rectangular coordinates corresponding to the rotated second point cloud based on the second point cloud distance and the preset angle; determine multiple third point clouds within the preset distance range of the rotated second point cloud among multiple reference point clouds based on the second rectangular coordinates; and determine the energy of the second point cloud based on the second rectangular coordinates, the multiple third rectangular coordinates corresponding to the multiple third point clouds, and the multiple target weights corresponding to the multiple third point clouds.

[0131] In one possible implementation, the point cloud energy determination unit 303 is used to acquire the target point cloud distance and target azimuth angle corresponding to multiple target point clouds in the current frame; determine the target rectangular coordinates based on the target point cloud distance and the target azimuth angle; determine the moving distance based on the target vehicle speed and the time interval; determine the compensated rectangular coordinates based on the target rectangular coordinates and the moving distance; and calculate the second point cloud distance and the second azimuth angle based on the compensated rectangular coordinates.

[0132] In one possible implementation, the point cloud energy determination unit 303 is used to calculate a second distance between the second rectangular coordinate and the third rectangular coordinate; calculate a second radial basis function of the second distance; calculate a second product of the second radial basis function and the target weight corresponding to the third rectangular coordinate; and calculate a second sum of a plurality of the second products corresponding to a plurality of third point clouds to obtain the second point cloud energy.

[0133] In one possible implementation, the relevant parameter determination unit 304 is used to calculate a third product between the energy of the second point cloud and the energy of the target point cloud corresponding to the second point cloud; and to calculate the sum of multiple third products to obtain the relevant parameters.

[0134] Based on the above method and device embodiments, this application also provides an electronic device. The following description will be provided in conjunction with the accompanying drawings.

[0135] See Figure 4 , Figure 4 This is a schematic diagram of an electronic device provided in an embodiment of this application.

[0136] The device 400 includes: a memory 401 and a processor 402;

[0137] The memory 401 is used to store relevant program code;

[0138] The processor 402 is used to call the program code to execute the method for determining the yaw rate of a vehicle as described in the above method embodiment.

[0139] Furthermore, embodiments of this application also provide a computer-readable storage medium for storing a computer program for executing the method for determining the yaw rate of a vehicle as described in the above method embodiments.

[0140] This application also provides a computer program product, which includes a computer program / instructions. When the computer program / instructions are executed by a processor, they implement the method for determining the yaw rate of a vehicle as described in the above method embodiments.

[0141] It should be noted that the computer-readable medium described above in this application may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0142] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0143] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. In particular, for system or device embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The device embodiments described above are merely illustrative. The units or modules described as separate components may or may not be physically separate. The components shown as units or modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the units or modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0144] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functions, and operations that may be implemented by methods, apparatuses, and devices according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0145] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0146] It should also be noted that, in this application, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0147] The steps of the methods or algorithms described in conjunction with the embodiments disclosed in this application can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0148] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of determining a yaw angular velocity of a vehicle, characterized by, The method comprises: determining a plurality of reference point clouds of a reference frame, the reference point clouds comprising: reference point cloud distances, reference azimuth angles, and reference point cloud energies, the reference point clouds being point clouds belonging to static targets; for a first point cloud, based on first distances between the first point cloud and each of the reference point clouds, and weights corresponding to each of the reference point clouds, establishing an equation relationship of a first point cloud energy corresponding to the first point cloud, and determining a plurality of weights corresponding to the plurality of reference point clouds respectively, the first point cloud representing any point cloud in the plurality of reference point clouds; based on a second point cloud of a current frame, a preset rotation angle, and the plurality of weights, determining a second point cloud energy corresponding to a rotated second point cloud, the second point cloud representing any target point cloud in a plurality of target point clouds of the current frame, the target point cloud comprising: a target point cloud energy; based on a plurality of second point cloud energies corresponding to the plurality of second point clouds and a plurality of target point cloud energies, determining a correlation parameter corresponding to the preset rotation angle, the correlation parameter being used to represent a correlation degree between the second point cloud energy and the target point cloud energy; based on a plurality of correlation parameters corresponding to a plurality of preset rotation angles respectively, determining a yaw angle of a vehicle in the plurality of preset rotation angles; based on the yaw angle, a time interval between the current frame and the reference frame, determining a yaw angular velocity of the vehicle.

2. The method of claim 1, wherein, The method comprises: calculating the first distances between the first point cloud and the reference point clouds; determining a first radial basis function of the first distances; calculating a first product of the first radial basis function and the weight corresponding to the reference point cloud; calculating a first sum of a plurality of first products corresponding to the first point cloud and the plurality of reference point clouds, and establishing an equation relationship between the first sum and the first point cloud energy; determining the plurality of weights based on a plurality of equation relationships corresponding to a plurality of first point clouds.

3. The method of claim 2, wherein, The method comprises: based on a first point cloud distance and a first azimuth angle corresponding to the first point cloud, determining a first rectangular coordinate of the first point cloud; based on a reference point cloud distance and a reference azimuth angle, determining a reference rectangular coordinate of the reference point cloud; based on the first rectangular coordinate and the reference rectangular coordinate, calculating the first distance.

4. The method of claim 1, wherein, The method comprises: obtaining a plurality of original point clouds of the reference frame; based on a point cloud speed of the original point cloud and an azimuth angle of the original point cloud, determining a first candidate vehicle speed of the vehicle; based on a median of a plurality of the first candidate vehicle speeds, screening a plurality of the first candidate vehicle speeds to obtain a plurality of second candidate vehicle speeds; based on a median of a plurality of the second candidate vehicle speeds, determining a target vehicle speed of the vehicle; determine a static point cloud reference speed based on the target vehicle speed and the azimuth angle; determine that the original point cloud is the reference point cloud when a difference between the point cloud speed and the static point cloud reference speed is less than a speed threshold.

5. The method of claim 4, wherein, The determining of the second point cloud energy corresponding to the rotated second point cloud based on the second point cloud of the current frame, the preset rotation angle, and the plurality of weights comprises: obtaining a second point cloud distance and a second azimuth angle corresponding to the second point cloud; determining a preset angle based on the second azimuth angle and the preset rotation angle; determining a second rectangular coordinate corresponding to the rotated second point cloud based on the second point cloud distance and the preset angle; determining a plurality of third point clouds within a preset distance range of the rotated second point cloud from the plurality of reference point clouds based on the second rectangular coordinate; determining the second point cloud energy based on the second rectangular coordinate, a plurality of third rectangular coordinates corresponding to a plurality of third point clouds, and a plurality of target weights corresponding to the plurality of third point clouds.

6. The method of claim 5, wherein, The obtaining of the second point cloud distance and the second azimuth angle corresponding to the second point cloud comprises: obtaining a target point cloud distance and a target azimuth angle corresponding to a plurality of target point clouds of the current frame; determining a target rectangular coordinate based on the target point cloud distance and the target azimuth angle; determining a moving distance based on the target vehicle speed and the time interval; determining a compensation rectangular coordinate based on the target rectangular coordinate and the moving distance; calculating the second point cloud distance and the second azimuth angle based on the compensation rectangular coordinate.

7. The method of claim 5, wherein, The determining of the second point cloud energy based on the second rectangular coordinate, the plurality of third rectangular coordinates corresponding to the plurality of third point clouds, and the plurality of target weights corresponding to the plurality of third point clouds comprises: calculating a second distance between the second rectangular coordinate and the third rectangular coordinate; calculating a second radial basis function of the second distance; calculating a second product of the second radial basis function and the target weight corresponding to the third rectangular coordinate; calculating a second sum of a plurality of second products corresponding to the plurality of third point clouds to obtain the second point cloud energy.

8. The method according to any one of claims 1 to 7, characterized in that, The determining of the relevant parameter corresponding to the preset rotation angle based on a plurality of second point cloud energies corresponding to a plurality of second point clouds and a plurality of target point cloud energies comprises: calculating a third product between the second point cloud energy and a target point cloud energy corresponding to the second point cloud; calculating a sum of a plurality of third products to obtain the relevant parameter.

9. An apparatus for determining a yaw angular velocity of a vehicle, characterized by The device comprises: a point cloud determination unit configured to determine a plurality of reference point clouds of a reference frame, wherein each reference point cloud comprises a reference point cloud distance, a reference azimuth angle, and a reference point cloud energy, and each reference point cloud is a point cloud of a static target; a weight determination unit configured to, for a first point cloud, establish an equation relationship of a first point cloud energy corresponding to the first point cloud based on a first distance between the first point cloud and each reference point cloud and a weight corresponding to each reference point cloud, and determine a plurality of weights corresponding to the plurality of reference point clouds, wherein the first point cloud represents any point cloud in the plurality of reference point clouds. A point cloud energy determination unit is configured to determine a second point cloud energy corresponding to a second point cloud after rotation based on the second point cloud of a current frame, a preset rotation angle, and a plurality of weights, the second point cloud representing any point cloud in a plurality of target point clouds of the current frame, and the target point cloud including a target point cloud energy. A correlation parameter determination unit is configured to determine a correlation parameter corresponding to the preset rotation angle based on a plurality of second point cloud energies corresponding to a plurality of second point clouds and a plurality of target point cloud energies, the correlation parameter being used to represent a correlation degree between the second point cloud energy and the target point cloud energy. An angle determination unit is configured to determine a yaw angle of a vehicle in a plurality of preset rotation angles based on a plurality of correlation parameters corresponding to the plurality of preset rotation angles, respectively. A yaw angular velocity determination unit is configured to determine a yaw angular velocity of the vehicle based on the yaw angle, and a time interval between the current frame and a reference frame.

10. An electronic device, comprising: The device includes a memory and a processor. The memory is configured to store related program codes. The processor is configured to invoke the program codes to execute the method for determining the yaw angular velocity of the vehicle according to any one of claims 1 to 8.

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