会议论文详细信息
2019 2nd International Conference on Advanced Materials, Intelligent Manufacturing and Automation
Vehicle Target Tracking Method for Crooked Roads Based on UKF and Sensor Fusion
Li, Lifu^1 ; Zhang, Wenying^1 ; Liang, Yi^1 ; Zhou, Hui^2
School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, Guangdong
510642, China^1
Guangzhou FLYAUDIO Co. Ltd, Guangzhou, Guangdong
510000, China^2
关键词: Continuous tracking;    Historical data;    Image information;    Measurement information;    State information;    Tracking method;    Unscented Kalman Filter;    Vehicle parameters;   
Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/569/4/042057/pdf
DOI  :  10.1088/1757-899X/569/4/042057
来源: IOP
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【 摘 要 】

Aiming at the problem that mm-wave radar tracking target is easy to lose when in crooked roads, a vehicle target tracking method based on Unscented Kalman Filter (UKF) and sensor fusion is proposed. This method uses mm-wave radar and camera to obtain vehicle targets' information in crooked roads at the same time. Then, according to whether mm-wave radar tracking target is lost or not, different tracking methods based on UKF are adopted. When the mm-wave radar tracking target is not lost, the historical and current data information of mm-wave radar are taken as the state information and measurement information, directly calculating the tracking vehicle parameters such as position, distance and speed; When the mm-wave radar tracking target is lost, a sensor fusion strategy is adopted. The historical data information of mm-wave radar is still the state information, and the camera vision image information of the tracking target becomes the measurement information, integrating the two sensors' information to get the tracking vehicle parameters. And the result will serve as next moment's state information for continuous tracking to solve the mm-wave radar tracking target loss problem in crooked roads. Finally, the validity of this method is verified by real road experiments.

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