CN-121977592-A - Perception target motion compensation method, system, equipment and medium based on high-precision positioning information

CN121977592ACN 121977592 ACN121977592 ACN 121977592ACN-121977592-A

Abstract

The application discloses a perception target motion compensation method, a system, equipment and a medium based on high-precision positioning information, which mainly relate to the technical field of target motion compensation and are used for solving the problems that a wheel speed meter on which self-vehicle chassis information depends is easily influenced by external factors and accumulated drift generated by simply calculating pose change by means of integral cannot meet the perception requirement of an intelligent driving system on long period and high precision in the existing motion compensation method. The method comprises the steps of calculating a relative motion transformation matrix from data acquisition time to data processing time, further calculating coordinates of a sensing target at the data processing time, inputting a covariance matrix at the data acquisition time and a time state into a Kalman filter to obtain a predicted time state and a predicted covariance matrix at the data processing time, and calculating the time state of the sensing target after data processing time compensation by using the coordinates of the sensing target at the data processing time, the predicted time state and the predicted covariance matrix at the data processing time.

Inventors

YANG XINGHUA
TIAN LEI
WANG PENGCHENG

Assignees

中国重汽集团济南动力有限公司

Dates

Publication Date: 20260505
Application Date: 20251224

Claims (10)

1. A method for motion compensation of a perceived target based on high-precision positioning information, the method comprising: The method comprises the steps of acquiring vehicle pose information of a vehicle at data acquisition time and data processing time based on a transmission time deviation value, calculating a relative motion transformation matrix from the data acquisition time to the data processing time according to the vehicle pose information, and calculating coordinates of a sensing target at the data processing time by utilizing the relative motion transformation matrix and the coordinates of the sensing target at the data acquisition time; the covariance matrix and the moment state of the data acquisition moment are input into a Kalman filter to obtain the predicted moment state and the predicted covariance matrix of the data processing moment; And calculating the time state of the perceived target after the data processing time compensation by using the coordinates of the perceived target at the data processing time, the predicted time state at the data processing time and the predicted covariance matrix.
2. The high-precision positioning information-based perception target motion compensation method according to claim 1, wherein obtaining vehicle pose information of a vehicle at a data acquisition time and a data processing time specifically comprises: determining a deviation value between the data acquisition time when the sensor acquires the original data and the data processing time when the original data is transmitted to the server, and taking the deviation value as a transmission time deviation value; At the time of data acquisition, acquiring vehicle pose information Pose-tsensor by a preset high-precision positioning module; ; wherein R_ tsensor is a 3x3 rotation matrix which represents the rotation transformation from the vehicle body coordinate system to the global coordinate system at the time of data acquisition, and t_ tsensor is a 3x1 translation vector which represents the coordinates of the vehicle in the global coordinate system at the time of data acquisition ; At the time of data processing, the vehicle pose information Pose-tfusion acquired by the preset high-precision positioning module; ; Wherein: A 3x3 rotation matrix which represents the rotation transformation from the vehicle body coordinate system to the global coordinate system at the time of data processing; Is a 3x1 translation vector and represents the coordinates of the own vehicle in the global coordinate system at the time of data processing 。
3. The high-precision positioning information-based perception target motion compensation method according to claim 1, wherein calculating a relative motion transformation matrix from a data acquisition time to a data processing time according to the vehicle pose information specifically comprises: by the formula: calculating a relative motion transformation matrix ; Wherein, the The self-vehicle pose information representing the data processing time, The vehicle pose information indicating the data acquisition time, inv () indicates the inverse operation of the matrix.
4. The method for motion compensation of a perceived target based on high-precision positioning information according to claim 1, wherein the calculating of coordinates of a perceived target at a data processing time by using a relative motion transformation matrix and coordinates of a perceived target at a data acquisition time, specifically comprises: by the formula: Calculating coordinates of a perception target at a data processing time ; Wherein, the Representing a transformation matrix of the relative motion, And the coordinates of the sensing target at the time of data acquisition are represented.
5. The method for motion compensation of a perceived target based on high-precision positioning information according to claim 1, wherein obtaining the moment state and covariance matrix of the perceived target at the moment of data acquisition, comprises: and acquiring a moment state and a covariance matrix of a data acquisition moment sensing target output by the Kalman filter.
6. The high-precision positioning information-based perception target motion compensation method according to claim 1, wherein the covariance matrix and the time state of the data acquisition time are input into a kalman filter to obtain the predicted time state and the predicted covariance matrix of the data processing time, and the method specifically comprises the following steps: by the formula: , Calculating a predicted time state of a data processing time And a prediction covariance matrix ; Wherein, the Representing a state transition matrix of the Kalman filter, Representing a process noise covariance matrix of the Kalman filter; a time state indicating the time of data acquisition, Representing the covariance matrix at the time of data acquisition.
7. The method for motion compensation of a perception target based on high-precision positioning information according to claim 1, wherein calculating the time state of the perception target after the data processing time compensation by using coordinates of the perception target at the data processing time, the predicted time state at the data processing time, and the predicted covariance matrix comprises: by the formula: , , , K = P_pred * H^T * S^{-1}, X_updated = X_pred + K * y, P_ updated = (I – K * H) * P_pred, calculating to obtain a time state X_updated of the perception target after the data processing time compensation; Wherein, the Representing the coordinates of the perceived target at the time of data processing, Representing the observation matrix of the kalman filter, Indicating the state of the predicted time of day, Representing the observed noise covariance matrix of the Kalman filter, P_pred representing the predicted covariance matrix, and P_updated representing the covariance matrix after compensation of the data processing time.
8. A perceived target motion compensation system based on high-precision positioning information, the system comprising: The computing module is used for acquiring the vehicle pose information of the vehicle at the data acquisition time and the data processing time based on the transmission time deviation value, computing a relative motion transformation matrix from the data acquisition time to the data processing time according to the vehicle pose information, and utilizing the relative motion transformation matrix and the data acquisition time to perceive the coordinates of the target and computing the coordinates of the data processing time to perceive the target; The acquisition module is used for acquiring a time state and a covariance matrix of a data acquisition time sensing target, inputting the covariance matrix and the time state of the data acquisition time into the Kalman filter, and acquiring a predicted time state and a predicted covariance matrix of the data processing time; And the compensation module is used for calculating the time state of the perceived target after the data processing time compensation by utilizing the coordinates of the perceived target at the data processing time, the predicted time state of the data processing time and the predicted covariance matrix.
9. A perception target motion compensation apparatus based on high-precision positioning information, the apparatus comprising: A processor; And a memory having executable code stored thereon that, when executed, causes the processor to perform a perceived target motion compensation method based on high-precision positioning information as recited in any of claims 1-7.
10. A non-transitory computer storage medium having stored thereon computer instructions that, when executed, implement a perceived target motion compensation method based on high-precision positioning information as recited in any of claims 1-7.

Description

Perception target motion compensation method, system, equipment and medium based on high-precision positioning information Technical Field The application relates to the technical field of target motion compensation, in particular to a method, a system, equipment and a medium for sensing target motion compensation based on high-precision positioning information. Background With the development of intelligent driving technology, the road functions of the intelligent driving system are more and more perfect. However, to ensure the safety of the road function, it is important that information such as the movement state of the road object can be accurately perceived. The vehicles on the road move at the moment, the calculation of the sensing algorithm in the system has a certain time delay, and the own vehicle and the target vehicle are in a moving state in the time interval, so that the moving states of the own vehicle and the target vehicle in the time interval need to be compensated to obtain a more accurate position of the sensing target object at the data processing moment. The existing motion compensation method mainly relies on the information of the chassis of the vehicle, calculates the relative translational and rotational changes of the vehicle between the sensor data acquisition time and the fusion time by integrating the angular velocity information provided by a wheel speed meter and an Inertial Measurement Unit (IMU) provided by a vehicle CAN bus, and reversely compensates the target position according to the relative translational and rotational changes. The method has the defects of limited accuracy and accumulated errors, wherein the dependent wheel speed meter is easily influenced by factors such as tyre slip, tyre pressure change, ground adhesion coefficient and the like, and the provided displacement information has limited accuracy. The accumulated drift generated by pose change is calculated by purely relying on IMU integration, and particularly, the error in estimation of pitch angle and roll angle is larger, and the error is continuously increased along with time, so that the intelligent driving system cannot meet the sensing requirement of long period and high precision. Disclosure of Invention The application provides a perception target motion compensation method, a system, equipment and a medium based on high-precision positioning information, which are used for solving the problems that the existing motion compensation method mainly depends on the information of a chassis of a bicycle, a wheel speed meter on which the information depends is easily influenced by external factors, and accumulated drift generated by calculating pose change simply by means of IMU integral cannot meet the perception requirement of an intelligent driving system on long period and high precision. In a first aspect, the present application provides a method for motion compensation of a perceived target based on high-precision positioning information, the method comprising: Acquiring self-vehicle pose information of a vehicle at the data acquisition moment and the data processing moment; calculating a relative motion transformation matrix from the data acquisition time to the data processing time according to the self-vehicle pose information; the covariance matrix and the moment state of the data acquisition moment are input into a Kalman filter to obtain the predicted moment state and the predicted covariance matrix of the data processing moment; And calculating the time state of the perceived target after the data processing time compensation by using the coordinates of the perceived target at the data processing time, the predicted time state at the data processing time and the predicted covariance matrix. In one implementation manner of the present application, acquiring vehicle pose information of a vehicle at a data acquisition time and a data processing time specifically includes: determining a deviation value between the data acquisition time when the sensor acquires the original data and the data processing time when the original data is transmitted to the server, and taking the deviation value as a transmission time deviation value; At the time of data acquisition, acquiring vehicle pose information Pose-tsensor by a preset high-precision positioning module; ; wherein R_ tsensor is a 3x3 rotation matrix which represents the rotation transformation from the vehicle body coordinate system to the global coordinate system at the time of data acquisition, and t_ tsensor is a 3x1 translation vector which represents the coordinates of the vehicle in the global coordinate system at the time of data acquisition ; At the time of data processing, the vehicle pose information Pose-tfusion acquired by the preset high-precision positioning module; ; Wherein: A 3x3 rotation matrix which represents the rotation transformation from the vehicle body coordinate system to the global coordinate system at the time of