Adaptive calibration method of radar installation angle, radar and storage medium

Abstract

The application provides a radar installation angle self-adaptive calibration method, a radar and a storage medium. The method comprises the following steps: obtaining measurement data of a current frame point cloud obtained by a radar installed on a mobile device and surrounding environment detection in a radar coordinate system; and converting the measurement data to a mobile device coordinate system by using a current effective calibration angle of the radar installation angle; screening out stationary points located on a straight line according to the measurement speed of each detection point and the speed of the mobile device; calculating a theoretical angle of the stationary points located on the straight line based on the measurement speed of the stationary points located on the straight line and the speed of the mobile device; calculating the deviation between the theoretical angle and the measurement angle of the stationary points located on the straight line; and updating the current effective calibration angle according to the calibration angle deviation of the current frame point cloud. The application can calibrate the radar installation angle through the state of the mobile device and stationary objects with straight line characteristics around the mobile device, thereby improving the accuracy of the calibration.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of radar, in particular to a radar installation angle adaptive calibration method, a radar and a storage medium. BACKGROUND

[0002] With the development of intelligentization of the automobile industry, vehicle-mounted millimeter wave radars are increasingly widely used in the automobile market, and the number of millimeter wave radar sensors installed on vehicles is gradually increasing. At the same time, the performance requirements for radars are also constantly improving, so that radars need to achieve accurate positioning of targets in their detection areas.

[0003] When the radar is installed and fixed on the vehicle, the radar is fixed to the standard installation angle according to the design requirements, and the installation angle is written into the radar. At this time, the trajectory information of the detected target is accurate. However, after the vehicle is driven for a long time, the actual installation angle of the radar will also shift due to vehicle shaking, vibration and other occurrences, resulting in a decrease in the accuracy of the target positioning information output by the radar, which seriously affects the safety of autonomous driving. SUMMARY

[0004] The present application provides a radar installation angle adaptive calibration method, a radar and a storage medium to solve the problem of low target detection accuracy caused by the inconsistency between the written radar installation angle and the actual installation angle in the prior art.

[0005] In a first aspect, the present application provides a radar installation angle adaptive calibration method, comprising:

[0006] Obtaining measurement data of a current frame point cloud obtained by a radar installed on a mobile device detecting the surrounding environment in a radar coordinate system; the measurement data includes a measurement angle, a measurement speed and a measurement distance;

[0007] Converting the measurement data of the current frame point cloud from the radar coordinate system to the mobile device coordinate system based on the current effective calibration angle of the radar installation angle;

[0008] Extracting stationary points in the current frame point cloud according to the measurement speed of each detection point in the current frame point cloud in the mobile device coordinate system and the speed of the mobile device;

[0009] Filtering stationary points located on a straight line from the current frame point cloud according to the measurement distance of the stationary points in the current frame point cloud in the mobile device coordinate system; and calculating the theoretical angle of the stationary points located on the straight line based on the measurement speed of the stationary points located on the straight line in the mobile device coordinate system and the speed of the mobile device;

[0010] The deviation between the theoretical angle of a stationary point located on a straight line and the measured angle in the coordinate system of the mobile device is calculated to obtain the calibration angle deviation of the current frame point cloud.

[0011] The current effective calibration angle is updated based on the calibration angle deviation of the current frame point cloud.

[0012] Secondly, this application provides a radar including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the method as described in any possible implementation of the first aspect above.

[0013] Thirdly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in any possible implementation of the first aspect above.

[0014] This application provides an adaptive calibration method for radar installation angle, a radar, and a storage medium. The method first acquires measurement data of the current frame point cloud obtained by the radar installed on a mobile device detecting the surrounding environment in the radar coordinate system. Then, it converts the measurement data to the mobile device coordinate system using the current valid calibration angle of the radar installation angle. Next, it filters out stationary points located on a straight line based on the measurement speed of each detection point and the speed of the mobile device. The theoretical angle of the stationary points on the straight line is calculated based on the measurement speed of the stationary points on the straight line and the speed of the mobile device. Finally, it calculates the deviation between the theoretical angle and the measured angle of the stationary points on the straight line. Based on the calibration angle deviation of the current frame point cloud, the current valid calibration angle is updated. As can be seen from the above scheme, this embodiment can calibrate the radar installation angle by utilizing the mobile device's own state and surrounding stationary objects with straight-line characteristics, thereby improving the accuracy of installation angle calibration and ultimately improving the detection accuracy of the radar. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is an application scenario diagram of the adaptive calibration method for radar installation angle provided in the embodiments of this application;

[0017] Figure 2This is a flowchart illustrating the implementation of the adaptive calibration method for radar installation angle provided in the embodiments of this application.

[0018] Figure 3 This is a schematic diagram of the intercept of a straight line with the origin provided in an embodiment of this application;

[0019] Figure 4 This is a flowchart of the single-frame point cloud calibration method provided in the embodiments of this application;

[0020] Figure 5 This is an overall flowchart of the adaptive calibration method for radar installation angle provided in the embodiments of this application;

[0021] Figure 6 This is a schematic diagram of the structure of the adaptive calibration device for radar installation angle provided in the embodiments of this application;

[0022] Figure 7 This is a schematic diagram of the radar structure provided in the embodiments of this application. Detailed Implementation

[0023] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0024] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0025] The adaptive calibration method for radar installation angle provided in this embodiment is applied to radar on mobile devices, which may include mobile devices such as vehicles, mobile robots, and aircraft. The adaptive calibration method for vehicle-mounted radar installation angle is described in detail below using a vehicle as an example:

[0026] Specifically, Figure 1 This diagram illustrates an application scenario for the adaptive calibration method for the installation angle of vehicle-mounted radar provided in this embodiment. Figure 1 As shown, the vehicle-mounted radar is the corner radar 20 on the vehicle 10. XO1Y represents the vehicle coordinate system (i.e., the mobile device coordinate system in this application), and xO2y represents the corner radar coordinate system. The angle difference between the corner radar coordinate system and the vehicle coordinate system is the radar installation angle ε, which is the angle that needs to be adaptively calibrated in this embodiment.

[0027] See Figure 2The flowchart illustrating the implementation of the adaptive calibration method for radar installation angle provided in this application embodiment is described in detail below:

[0028] S101: Obtain measurement data of the current frame point cloud obtained by the radar installed on the mobile device in the radar coordinate system; the measurement data includes measurement angle, measurement speed and measurement distance.

[0029] Specifically, during vehicle operation, the radar acquires point cloud signals from the surrounding environment in real time and calculates the measurement data of each frame of point cloud in the radar coordinate system.

[0030] In one possible implementation, prior to S101, the method provided in this embodiment further includes:

[0031] If the speed of the mobile device is within a preset speed range, and the yaw rate of the mobile device is less than the maximum yaw rate, and the turning radius of the mobile device is greater than the minimum turning radius, and the acceleration of the mobile device is less than the adaptive calibration allowable acceleration, then the step of obtaining the measurement data of the current frame point cloud in the radar coordinate system obtained by the radar installed on the mobile device detecting the surrounding environment is executed.

[0032] Since the radar can more accurately identify static targets with straight-line characteristics under the above driving conditions, this embodiment needs to monitor the vehicle's driving environment before performing the adaptive calibration method for the radar installation angle. The adaptive calibration method will only be started when the above conditions are met, thereby improving the accuracy of the adaptive calibration method.

[0033] Specifically, such as Figure 4 As shown, the radar can calibrate its installation angle according to a certain cycle. The adaptive calibration method is started. After the current cycle calibration time is reached, the radar outputs a calibration start command. After the vehicle is powered on, it first judges whether the vehicle's own state meets the requirements. If it meets the requirements, the adaptive calibration method provided in this embodiment is executed. If it does not meet the requirements, the adaptive calibration method is not executed, and the vehicle's own state is continued to be detected until its own state meets the requirements.

[0034] Specifically, the conditions that the vehicle itself must meet are as follows:

[0035] 1. Taking the vehicle's forward movement as the positive direction, determine whether the vehicle's speed is greater than AC_SPD_ACTIVE and less than AC_SPD_EXIT; where AC_SPD_ACTIVE and AC_SPD_EXIT are two boundary values ​​of a preset speed range, and both AC_SPD_ACTIVE and AC_SPD_EXIT are positive values. <AC_SPD_EXIT。

[0036] 2. The vehicle's yaw rate is less than the maximum yaw rate AC_MAX_YAWRATE;

[0037] 3. The vehicle's turning radius is greater than the minimum turning radius AC_MIN_RADIUS;

[0038] 4. The vehicle's acceleration is less than the adaptive calibration allowable acceleration.

[0039] Only when all the above conditions are met can the radar implement the adaptive calibration method.

[0040] S102: Based on the current effective calibration angle of the radar installation angle, the measurement data of the current frame point cloud is transformed from the radar coordinate system to the mobile device coordinate system.

[0041] In this embodiment, since the radar coordinate system is often inconsistent with the mobile device coordinate system, such as Figure 1 As shown, there is a certain angular deviation between the radar coordinate system and the mobile device coordinate system. Therefore, after the radar detects the measurement data of the point cloud, it is necessary to transform the measurement data from the radar coordinate system to the mobile device coordinate system to facilitate the vehicle's obstacle recognition. This coordinate system transformation requires the radar's installation angle; if the installation angle is incorrect, the measurement data of the point cloud transformed to the mobile device coordinate system will be inaccurate, affecting the radar's detection accuracy.

[0042] This embodiment can store the currently valid calibration angle in the radar's NVM (Nonvolatile Memory) each time the radar installation angle is successfully calibrated, so that the radar can call the latest calibrated current valid calibration angle to perform coordinate transformation on the measurement data when performing target detection.

[0043] S103: Based on the measured speed of each detection point in the current frame point cloud in the coordinate system of the mobile device and the speed of the mobile device, extract the stationary points in the current frame point cloud.

[0044] In one possible implementation, such as Figure 4 As shown, the specific implementation process of S103 includes:

[0045] For each detection point in the current frame point cloud, the velocity of the detection point is calculated according to the velocity calculation formula; and if the velocity of the detection point is less than a preset velocity, the detection point is determined to be a stationary point.

[0046] The formula for calculating the speed is:

[0047] diffDoppler=fabs(carSpeed+doppler / cos(θ));

[0048] Where, diffDoppler represents the velocity of the probe point, carSpeed ​​represents the velocity of the mobile device, doppler represents the measured velocity of the probe point in the coordinate system of the mobile device, θ represents the measured angle of the probe point in the coordinate system of the mobile device, and fabs() represents the absolute value function.

[0049] In this embodiment, in order to improve the calibration accuracy of the radar installation angle, the calibration needs to be performed in the presence of objects with strong reflective effects such as iron railings, cement walls, and bushes on the radar side. Therefore, it is first necessary to separate the point cloud into static and dynamic parts and calculate the velocity of each detection point in the point cloud. The smaller the velocity of the detection point, the greater the possibility that the detection point is a stationary point.

[0050] S104: Based on the measured distance of the stationary points in the current frame point cloud under the coordinate system of the mobile device, select the stationary points located on a straight line from the current frame point cloud; and calculate the theoretical angle of the stationary points located on a straight line based on the measured speed of the stationary points located on a straight line under the coordinate system of the mobile device and the speed of the mobile device.

[0051] In one possible implementation, the measured distance includes a lateral measured distance and a longitudinal measured distance; the specific implementation process of S104 includes:

[0052] S201: If the number of stationary points in the current frame point cloud is greater than the first preset number, then the measured distance of each stationary point in the coordinate system of the mobile device is input into the intercept calculation formula to calculate the intercept of each detection point.

[0053] S202: Group stationary points with the same intercept angle and the same intercept into one class, and count the number of stationary points in each cluster group; the intercept angle is the angle between the intercept and the coordinate axis of the mobile device coordinate system;

[0054] S203: Determine whether the number of stationary points in the cluster group with the most stationary points is greater than the second preset number. If the number of stationary points in the cluster group with the most stationary points is greater than the second preset number, then determine that the stationary points in the cluster group with the most stationary points are stationary points on a straight line.

[0055] S204: For each stationary point located on a straight line, input the measured velocity of the stationary point in the coordinate system of the mobile device and the velocity of the mobile device into the theoretical angle calculation formula to obtain the theoretical angle of the stationary point;

[0056] The intercept calculation formula is: r=rx*sin(a)+ry*cos(a);

[0057] Where r represents the intercept, rx represents the lateral distance of the stationary point in the coordinate system of the mobile device, ry represents the longitudinal distance of the stationary point in the coordinate system of the mobile device, and a represents the intercept angle.

[0058] The theoretical angle calculation formula is: dopplerAngle = arccos(doppler / carSpeed);

[0059] Where dopplerAngle represents the theoretical angle, carSpeed ​​represents the speed of the mobile device, and doppler represents the measured speed of the probe point in the coordinate system of the mobile device.

[0060] In this embodiment, as Figure 3 As shown, a straight line is represented by (r, a), where r is the distance from the line to the origin, and α is the angle between the perpendicular line to the line and the x-axis. Detection points on a straight line share the same (r, a). Therefore, to find linear features from stationary points, the lateral and longitudinal distances of each stationary point need to be input into the intercept calculation formula. The intercept corresponding to the stationary point at various intercept angles within the radar detection angle range is calculated according to unit steps; the number of stationary points with the same intercept angle and the same intercept angle is determined. The intercept angle can be the angle between the intercept line between the stationary point and the origin of the mobile device coordinate system and the x-axis of the mobile device coordinate system.

[0061] Specifically, using 0.5° as the unit step and 0–180° as the radar detection angle range, the intercept r of the stationary point at each intercept angle is calculated sequentially. After the traversal is completed, if (r i ,α j The number of stationary points under coordinates (r) is the largest, and (r) i ,α j If the number of stationary points in the coordinate system exceeds the second preset number, then determine (r). i ,α j If a straight line exists in the coordinate system, it means that there is a linear object with strong reflective effect on the radar side in the current frame, which can be used for angle calibration. Here, i = 1, 2...X, where X represents the total number of intercept angles from 0° to 180°. If the unit step is 0.5, then X = 360; j = 1, 2,...Y, where Y represents the total number of intercepts in the stationary point cloud.

[0062] If, after traversing all angles, the number of stationary points in the same cluster group is not greater than the second preset number, then the current frame will not be adaptively calibrated, and the next frame of point cloud measurement data will be directly adjusted to execute steps S101 to S106.

[0063] S105: Calculate the deviation between the theoretical angle of a stationary point located on a straight line and the measured angle in the coordinate system of the mobile device, and obtain the calibration angle deviation of the current frame point cloud.

[0064] In one possible implementation, the specific implementation process of S105 includes:

[0065] For each stationary point located on a straight line, calculate the difference between the theoretical angle of that stationary point and the measured angle in the coordinate system of the mobile device, and use it as the calibration angle deviation of that stationary point;

[0066] The calibration angle deviation of the current frame point cloud is obtained by averaging the calibration angle deviations of all stationary points located on a straight line.

[0067] In this embodiment, stationary points within a certain range along a straight line are selected to ensure high signal-to-noise ratio and angular accuracy for radar target detection within this range, thus guaranteeing calibration accuracy. The theoretical angle of each stationary point is calculated based on its velocity and the speed of the mobile device. Since the measured angle of a stationary point is converted from the radar's current effective calibration angle, the difference between the measured angle and the theoretical angle is the angular deviation between the radar's current effective calibration angle and the actual installation angle, i.e., the calibration angle deviation.

[0068] Therefore, for each stationary point located on a straight line, the calibration angle deviation of that stationary point is calculated using offsetAngle = dopplerAngle - θ. Here, offsetAngle represents the calibration angle deviation of the stationary point. Finally, the average of the calibration angle deviations corresponding to all stationary points is calculated to obtain the calibration angle deviation of the current frame point cloud.

[0069] S106: Update the current effective calibration angle based on the calibration angle deviation of the current frame point cloud.

[0070] In one possible implementation, the specific implementation process of S106 includes:

[0071] S301: If the calibration angle deviation of the current frame point cloud is greater than the maximum calibration deviation threshold, the calibration angle deviation of the current frame point cloud is used to compensate for the current effective calibration angle, and the compensated current effective calibration angle is returned to the current effective calibration angle based on the radar installation angle. The step of converting the measurement data of the current frame point cloud from the radar coordinate system to the mobile device coordinate system continues to be executed until the calibration angle deviation of the current frame point cloud is not greater than the maximum calibration deviation threshold. Then, the calibration angle deviation obtained in each loop is added to the current effective calibration angle to obtain the calibration angle of the current frame point cloud.

[0072] S302: Update the current valid calibration angle based on the calibration angle of the current frame point cloud.

[0073] In this embodiment, although the installation angle of the vehicle-mounted radar may deviate slightly after being subjected to vehicle movement and bumps, the deviation between the actual installation angle and the current effective calibration angle will not be too large under normal circumstances. Therefore, if the calibration angle deviation of the current frame point cloud exceeds the maximum calibration deviation threshold, it indicates that the dynamic-static separation result of the current frame point cloud is inaccurate, resulting in inaccurate angle calibration. To ensure calibration accuracy, this embodiment requires secondary calibration of the radar installation angle based on the current frame point cloud when the calibration angle deviation of the current frame point cloud exceeds the maximum calibration deviation threshold.

[0074] Specifically, the calibration angle deviation of the current frame point cloud is added to the current effective calibration angle to obtain the compensated current effective calibration angle. This compensated current effective calibration angle is then substituted into step S102 to re-convert the measurement data of the current frame point cloud in the mobile device coordinate system. Steps S102 to S106 are repeated until the calibration angle deviation of the current frame point cloud is no greater than the maximum calibration deviation threshold. At this point, the calibration angle deviations of the current frame point cloud obtained in each iteration are summed and then added to the current effective calibration angle to obtain the calibration angle of the current frame point cloud after secondary calibration.

[0075] For example, if the calibration angle deviation of the current frame point cloud obtained for the first time is 6 degrees, which is greater than the maximum calibration deviation threshold of 5 degrees, and the current effective calibration angle is 41 degrees, then 41 degrees plus 6 degrees is used to obtain 47 degrees. 47 degrees is used as the compensated effective calibration angle, and S102 to S106 are executed repeatedly. The calibration angle deviation of the current frame point cloud obtained for the second time is 3 degrees, which is not greater than the maximum calibration deviation threshold. Then the final calibration angle of the current frame point cloud is 41 + 6 + 3 = 50 degrees.

[0076] If the calibration angle deviation of the current frame point cloud is not greater than the maximum calibration deviation threshold, the calibration angle of the current frame point cloud is directly obtained.

[0077] This completes the calibration of the installation angle for a single frame point cloud.

[0078] In one possible implementation, the specific implementation process of S302 includes:

[0079] S401: Calculate the average calibration angle of N frames of point cloud in the current period, and subtract the average calibration angle of N frames of point cloud in the current period from the initial calibration angle of the radar installation angle to obtain the calibration angle deviation of the current period.

[0080] S402: If the calibration angle deviation of the current cycle is less than the preset calibration angle deviation threshold, then it is determined that the radar installation angle calibration of the current cycle is successful.

[0081] S403: If the number of successful calibrations reaches the first preset number, the median value of the calibration angles of each successful calibration cycle shall be taken as the final calibration angle for this calibration.

[0082] S404: The difference between the final calibration angle and the initial calibration angle is taken as the first difference;

[0083] S405: The difference between the final calibration angle and the current valid calibration angle is taken as the second difference;

[0084] S406: If the first difference is less than the first preset difference and the second difference is greater than the second preset difference, then the current valid calibration angle is replaced with the final calibration angle of this time.

[0085] In this embodiment, as Figure 5 As shown, after completing the calibration of a single frame of point cloud, N frames are used as a cycle. After obtaining the calibration angles of N frames of point cloud, the average calibration angle of the current cycle is calculated. If the difference between the average calibration angle of the current cycle and the initial calibration angle (the calibration angle deviation of the current cycle) is less than the preset calibration angle deviation threshold ALLOW_ANGLE, the calibration of the current cycle is considered successful, the calibration success count SUCESS_CNT is updated, and calibration is restarted after an interval AC_SUCESS_INTERVAL. When the cumulative calibration success count SUCESS_CNT reaches the first preset number SUCESS_CNT_ACTIVE, the median value is taken from the calibration angles of each cumulative successful calibration cycle to obtain the final calibration angle, and the final calibration angle is stored in RAM (random access memory). The initial calibration angle is the calibration angle obtained when the radar's installation angle is calibrated for the first time.

[0086] If the first difference is less than the first preset difference ALLOW_ANGLE and the second difference is greater than the second preset difference MIN_ANGLE, then the current effective calibration angle is replaced with the final calibration angle stored in the radar's NVM area, the original current effective calibration angle in the NVM is deleted, and the latest current effective calibration angle is used to calculate the measurement data of subsequent targets.

[0087] Specifically, each time NVM updates the current valid calibration angle, it resets the cumulative number of successful calibrations to zero, and the adaptive calibration method is retried after the radar is powered on again.

[0088] In one possible implementation, after S401, the method provided in this embodiment further includes:

[0089] If the calibration angle deviation of the current cycle is greater than or equal to the preset calibration angle deviation threshold, it is determined that the calibration of the radar installation angle in the current cycle is out of tolerance.

[0090] The cumulative number of calibration errors is counted. If the cumulative number of calibration errors reaches the second preset number, calibration error fault information is generated.

[0091] In this embodiment, when the calibration angle deviation for one cycle is determined to be out of tolerance, calibration is restarted after an interval of AC_OUT_INTERVA. When calibration is determined to be successful, the number of out-of-tolerance calibrations is reset to zero. That is, an out-of-tolerance fault message is only generated and reported to the vehicle terminal or other terminals connected to the radar when the cumulative number of out-of-tolerance calibrations INVALID_CNT reaches the second preset number INVALID_CNT_ACTIVE, so that the user can promptly check the current installation status of the radar.

[0092] As can be seen from the above scheme, this embodiment autonomously judges the vehicle's status and surrounding environment during vehicle operation, selects an environment with stationary straight-line characteristics for calibration, calculates the actual installation angle of the radar based on the angle and speed of stationary objects, compares the actual installation angle with the currently written valid calibration angle, and performs different operations on the currently written valid calibration angle based on the comparison results, thereby achieving the purpose of detecting the target's true position and true speed.

[0093] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0094] The following are device embodiments of this application. For details not described in detail, please refer to the corresponding method embodiments described above.

[0095] Figure 4 A schematic diagram of the adaptive calibration device for radar installation angle provided in an embodiment of this application is shown. For ease of explanation, only the parts related to the embodiment of this application are shown, and are described in detail below:

[0096] like Figure 4 As shown, the adaptive calibration device 4 for radar installation angle includes:

[0097] The measurement data acquisition module 110 is used to acquire the measurement data of the current frame point cloud obtained by the radar installed on the mobile device from the detection of the surrounding environment in the radar coordinate system; the measurement data includes measurement angle, measurement speed and measurement distance.

[0098] The coordinate transformation module 120 is used to transform the measurement data of the current frame point cloud from the radar coordinate system to the mobile device coordinate system based on the current effective calibration angle of the radar installation angle.

[0099] The stationary point extraction module 130 is used to extract stationary points in the current frame point cloud based on the measured speed of each detection point in the current frame point cloud in the coordinate system of the mobile device and the speed of the mobile device.

[0100] The theoretical angle calculation module 140 is used to filter out stationary points located on a straight line from the current frame point cloud based on the measured distance of stationary points in the current frame point cloud in the mobile device coordinate system; and to calculate the theoretical angle of the stationary points located on a straight line based on the measured speed of the stationary points located on the straight line in the mobile device coordinate system and the speed of the mobile device.

[0101] The calibration angle deviation calculation module 150 is used to calculate the deviation between the theoretical angle of a stationary point located on a straight line and the measured angle in the coordinate system of the mobile device, so as to obtain the calibration angle deviation of the current frame point cloud.

[0102] The effective calibration angle update module 160 is used to update the current effective calibration angle based on the calibration angle deviation of the current frame point cloud.

[0103] In one possible implementation, the adaptive calibration device for radar installation angle provided in this embodiment further includes an environment judgment module, used for:

[0104] If the speed of the mobile device is within a preset speed range, and the yaw rate of the mobile device is less than the maximum yaw rate, and the turning radius of the mobile device is greater than the minimum turning radius, and the acceleration of the mobile device is less than the adaptive calibration allowable acceleration, then the step of obtaining the measurement data of the current frame point cloud in the radar coordinate system obtained by the radar installed on the mobile device detecting the surrounding environment is executed.

[0105] In one possible implementation, the stationary point extraction module is specifically used for:

[0106] For each detection point in the current frame point cloud, the velocity of the detection point is calculated according to the velocity calculation formula; and if the velocity of the detection point is less than a preset velocity, the detection point is determined to be a stationary point.

[0107] The formula for calculating the speed is:

[0108] diffDoppler=fabs(carSpeed+doppler / cos(θ));

[0109] Where, diffDoppler represents the velocity of the probe point, carSpeed ​​represents the velocity of the mobile device, doppler represents the measured velocity of the probe point in the coordinate system of the mobile device, θ represents the measured angle of the probe point in the coordinate system of the mobile device, and fabs() represents the absolute value function.

[0110] In one possible implementation, the measured distance includes a lateral measured distance and a longitudinal measured distance; the theoretical angle calculation module 140 includes:

[0111] If the number of stationary points in the current frame point cloud is greater than the first preset number, the measured distance of each stationary point in the coordinate system of the mobile device is input into the intercept calculation formula to calculate the intercept of each detection point.

[0112] Stationary points with the same intercept angle and the same intercept are grouped into one class, and the number of stationary points in each cluster is counted; the intercept angle is the angle between the intercept and the coordinate axis of the mobile device coordinate system;

[0113] Determine whether the number of stationary points in the cluster group with the most stationary points is greater than the second preset number. If the number of stationary points in the cluster group with the most stationary points is greater than the second preset number, then determine that the stationary points in the cluster group with the most stationary points are stationary points on a straight line.

[0114] For each stationary point located on a straight line, the measured velocity of the stationary point in the coordinate system of the mobile device and the velocity of the mobile device are input into the theoretical angle calculation formula to obtain the theoretical angle of the stationary point.

[0115] The intercept calculation formula is: r=rx*sin(a)+ry*cos(a);

[0116] Where r represents the intercept, rx represents the lateral distance of the stationary point in the coordinate system of the mobile device, ry represents the longitudinal distance of the stationary point in the coordinate system of the mobile device, and a represents the intercept angle.

[0117] The theoretical angle calculation formula is: dopplerAngle = arccos(doppler / carSpeed);

[0118] Where dopplerAngle represents the theoretical angle, carSpeed ​​represents the speed of the mobile device, and doppler represents the measured speed of the probe point in the coordinate system of the mobile device.

[0119] In one possible implementation, the effective calibration angle update module 160 includes:

[0120] The single-frame calibration angle calculation unit is used to compensate the current effective calibration angle by using the calibration angle deviation of the current frame point cloud if the calibration angle deviation of the current frame point cloud is greater than the maximum calibration deviation threshold, and return the compensated current effective calibration angle to the current effective calibration angle based on the radar installation angle. The step of converting the measurement data of the current frame point cloud from the radar coordinate system to the mobile device coordinate system continues to be executed until the calibration angle deviation of the current frame point cloud is not greater than the maximum calibration deviation threshold. Then, the calibration angle deviation obtained in each loop is added to the current effective calibration angle to obtain the calibration angle of the current frame point cloud.

[0121] An effective calibration angle update unit is used to update the current effective calibration angle based on the calibration angle of the current frame point cloud.

[0122] In one possible implementation, the effective calibration angle update unit includes:

[0123] The periodic calibration angle deviation calculation subunit is used to calculate the average calibration angle of the N frames of point cloud in the current period, and to subtract the average calibration angle of the N frames of point cloud in the current period from the initial calibration angle of the radar installation angle to obtain the calibration angle deviation of the current period.

[0124] The calibration success determination subunit is used to determine that the radar installation angle calibration is successful in the current cycle if the calibration angle deviation of the current cycle is less than the preset calibration angle deviation threshold.

[0125] The final calibration angle calculation subunit is used to take the median value of the calibration angle of each cycle of successful calibration as the final calibration angle if the number of successful calibrations reaches a first preset number.

[0126] The first difference calculation subunit is used to take the difference between the final calibration angle and the initial calibration angle as the first difference.

[0127] The second difference calculation subunit is used to take the difference between the final calibration angle and the current effective calibration angle as the second difference.

[0128] The effective calibration angle update subunit is used to replace the current effective calibration angle with the final calibration angle if the first difference is less than the first preset difference and the second difference is greater than the second preset difference.

[0129] In one possible implementation, the effective calibration angle update unit provided in this embodiment further includes a calibration error judgment unit, used for:

[0130] If the calibration angle deviation of the current cycle is greater than or equal to the preset calibration angle deviation threshold, it is determined that the calibration of the radar installation angle in the current cycle is out of tolerance.

[0131] The cumulative number of calibration errors is counted. If the cumulative number of calibration errors reaches the second preset number, calibration error fault information is generated.

[0132] In one possible implementation, the calibration angle deviation calculation module 150 includes:

[0133] For each stationary point located on a straight line, calculate the difference between the theoretical angle of that stationary point and the measured angle in the coordinate system of the mobile device, and use it as the calibration angle deviation of that stationary point;

[0134] The calibration angle deviation of the current frame point cloud is obtained by averaging the calibration angle deviations of all stationary points located on a straight line.

[0135] Figure 7 This is a schematic diagram of the radar provided in an embodiment of this application. For example... Figure 7 As shown, the radar 7 in this embodiment includes a processor 70, a memory 71, and a computer program 72 stored in the memory 71 and executable on the processor 70. When the processor 70 executes the computer program 72, it implements the steps in the above-described adaptive calibration method embodiments for various radar installation angles, for example... Figure 2 Steps 101 to 106 are shown. Alternatively, when the processor 70 executes the computer program 72, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 6 The functions of modules 110 to 160 are shown.

[0136] For example, the computer program 72 may be divided into one or more modules / units, which are stored in the memory 71 and executed by the processor 70 to complete / implement the solution provided in this application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 72 in the radar 7.

[0137] The radar 7 may include, but is not limited to, a processor 70 and a memory 71. Those skilled in the art will understand that... Figure 7 This is merely an example of radar 7 and does not constitute a limitation on radar 7. It may include more or fewer components than shown, or combine certain components, or different components. For example, the radar may also include input / output devices, network access devices, buses, etc.

[0138] The processor 70 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0139] The memory 71 can be an internal storage unit of the radar 7, such as a hard disk or memory. The memory 71 can also be an external storage device of the radar 7, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the radar 7. Furthermore, the memory 71 can include both internal storage units and external storage devices. The memory 71 is used to store the computer program and other programs and data required by the radar. The memory 71 can also be used to temporarily store data that has been output or will be output.

[0140] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0141] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0142] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0143] In the embodiments provided in this application, it should be understood that the disclosed apparatus / radar and method can be implemented in other ways. For example, the apparatus / radar embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0144] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0145] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0146] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the adaptive calibration method embodiments for each radar installation angle described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately added to or subtracted from the content as required by the legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium may not include electrical carrier signals and telecommunication signals.

[0147] Furthermore, the features of the embodiments shown in the accompanying drawings or the various embodiments mentioned in this specification should not be construed as independent embodiments. Rather, each feature described in one example of an embodiment can be combined with one or more other desired features from other embodiments to produce other embodiments not described in words or with reference to the accompanying drawings.

[0148] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A radar mounting angle self-adaptive calibration method, characterized in that, The method comprises the following steps: acquiring measurement data of a current frame point cloud detected by a radar installed on a mobile device on a surrounding environment in a radar coordinate system; the measurement data comprises a measurement angle, a measurement velocity and a measurement distance; converting the measurement data of the current frame point cloud from the radar coordinate system to a mobile device coordinate system based on a current effective calibration angle of the radar installation angle; extracting stationary points in the current frame point cloud according to the measurement velocity of each detection point in the current frame point cloud in the mobile device coordinate system and the velocity of the mobile device; screening stationary points located on a straight line from the current frame point cloud according to the measurement distance of the stationary points in the current frame point cloud in the mobile device coordinate system; and calculating the theoretical angle of the stationary points located on the straight line based on the measurement velocity of the stationary points located on the straight line in the mobile device coordinate system and the velocity of the mobile device; calculating the deviation of the theoretical angle of the stationary points located on the straight line from the measurement angle in the mobile device coordinate system to obtain a calibration angle deviation of the current frame point cloud; updating the current effective calibration angle according to the calibration angle deviation of the current frame point cloud.

2. The method of adaptive calibration of radar mounting angle according to claim 1, characterized in that, The extraction of the stationary points in the current frame point cloud according to the measurement velocity of each detection point in the current frame point cloud in the mobile device coordinate system and the velocity of the mobile device comprises: for each detection point of the current frame point cloud, calculating the velocity of the detection point according to a velocity calculation formula; and determining the detection point as a stationary point when the velocity of the detection point is less than a preset velocity; the velocity calculation formula is: diffDoppler = fabs(carSpeed + doppler / cos(θ)); wherein, diffDoppler represents the velocity of the detection point, carSpeed represents the velocity of the mobile device, doppler represents the measurement velocity of the detection point in the mobile device coordinate system, θ represents the measurement angle of the detection point in the mobile device coordinate system, and fabs() represents an absolute value function.

3. The method of adaptive calibration of radar mounting angle according to claim 1, characterized in that, The measurement distance comprises a transverse measurement distance and a longitudinal measurement distance; The screening of the stationary points located on a straight line from the current frame point cloud according to the measurement distance of the stationary points in the current frame point cloud in the mobile device coordinate system; and the calculation of the theoretical angle of the stationary points located on the straight line based on the measurement velocity of the stationary points located on the straight line in the mobile device coordinate system and the velocity of the mobile device, comprises: if the number of the stationary points in the current frame point cloud is greater than a first preset number, inputting the measurement distance of each stationary point in the mobile device coordinate system into an intercept calculation formula to calculate the intercept of each detection point; grouping stationary points with the same intercept angle and the same intercept into a class, and counting the number of stationary points in each clustering group; the intercept angle is the angle between the intercept and the coordinate axis of the mobile device coordinate system. determining whether the number of stationary points of the cluster group with the largest number of stationary points is greater than a second preset number, and if the number of stationary points of the cluster group with the largest number of stationary points is greater than the second preset number, determining that the stationary points of the cluster group with the largest number of stationary points are stationary points on a straight line; for each stationary point located on a straight line, inputting a measured speed of the stationary point in the mobile device coordinate system and a speed of the mobile device into a theoretical angle calculation formula to obtain a theoretical angle of the stationary point; wherein the intercept calculation formula is: r = rx*sin(a) + ry*cos(a); wherein r represents an intercept, rx represents a horizontal measured distance of the stationary point in the mobile device coordinate system, ry represents a vertical measured distance of the stationary point in the mobile device coordinate system, and a represents an intercept angle; the theoretical angle calculation formula is: dopplerAngle = arccos(doppler / carSpeed); wherein dopplerAngle represents a theoretical angle, carSpeed represents a speed of the mobile device, and doppler represents a measured speed of a probe point in the mobile device coordinate system.

4. The method of adaptive calibration of radar mounting angle according to claim 1, characterized in that, the updating of the current effective calibration angle according to the calibration angle deviation of the current frame point cloud comprises: if the calibration angle deviation of the current frame point cloud is greater than a maximum calibration deviation threshold, compensating the current effective calibration angle by using the calibration angle deviation of the current frame point cloud, and returning the compensated current effective calibration angle to the current effective calibration angle based on the radar installation angle, so that the measured data of the current frame point cloud is converted from the radar coordinate system to the mobile device coordinate system, and the subsequent steps are continued to be executed until the calibration angle deviation of the current frame point cloud is not greater than the maximum calibration deviation threshold, then adding the calibration angle deviation obtained in each loop to the current effective calibration angle to obtain the calibration angle of the current frame point cloud; updating the current effective calibration angle based on the calibration angle of the current frame point cloud.

5. The method of adaptive calibration of radar mounting angle according to claim 4, characterized in that, the updating of the current effective calibration angle based on the calibration angle of the current frame point cloud comprises: calculating a mean value of the calibration angles of N frame point clouds in a current period, and calculating a calibration angle deviation of the current period by subtracting the initial calibration angle of the radar installation angle from the mean value of the calibration angles of N frame point clouds in the current period; if the calibration angle deviation of the current period is less than a preset calibration angle deviation threshold, determining that the calibration of the radar installation angle in the current period is successful; if the number of successful calibrations reaches a first preset number, taking a middle value of the calibration angles of the periods in which the calibration is successful as a final calibration angle of this time; taking a difference between the final calibration angle of this time and the initial calibration angle as a first difference value; taking a difference between the final calibration angle of this time and the current effective calibration angle as a second difference value; if the first difference value is less than a first preset difference value and the second difference value is greater than a second preset difference value, replacing the current effective calibration angle with the final calibration angle of this time.

6. The method of adaptive calibration of radar mounting angle according to claim 5, characterized in that, After the mean of the N frame point cloud calibration angles in the current period is subtracted from the initial calibration angle of the radar installation angle to obtain the calibration angle deviation of the current period, the method further comprises: If the calibration angle deviation of the current period is greater than or equal to the preset calibration angle deviation threshold, it is determined that the current period is out of calibration for the radar installation angle calibration; The number of calibration out-of-tolerance is accumulated, and if the accumulated number of calibration out-of-tolerance reaches a second preset number, calibration out-of-tolerance fault information is generated.

7. The method of adaptive calibration of radar mounting angle according to any one of claims 1 to 6, characterized in that, Before the measurement data of the current frame point cloud detected by the radar installed on the mobile device is obtained in the radar coordinate system, the method further comprises: If the speed of the mobile device is within a preset speed range, the yaw rate of the mobile device is less than the maximum yaw rate, the turning radius of the mobile device is greater than the minimum turning radius, and the acceleration of the mobile device is less than the adaptive calibration allowed acceleration, the step of obtaining the measurement data of the current frame point cloud detected by the radar installed on the mobile device in the radar coordinate system is executed.

8. The method of adaptive calibration of radar mounting angle according to claim 1, characterized in that, The calculation of the deviation between the theoretical angle of the stationary point located on a straight line and the measurement angle in the mobile device coordinate system to obtain the calibration angle deviation of the current frame point cloud comprises: For each stationary point located on a straight line, the difference between the theoretical angle of the stationary point and the measurement angle in the mobile device coordinate system is calculated and taken as the calibration angle deviation of the stationary point. The calibration angle deviations of all stationary points located on a straight line are averaged to obtain the calibration angle deviation of the current frame point cloud.

9. A radar comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the adaptive calibration method of the radar installation angle according to any one of claims 1 to 8.

10. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 9. The computer program is executed by the processor to implement the steps of the adaptive calibration method of the radar installation angle according to any one of claims 1 to 8.

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