Accurately identifying and tracking different types of vehicles is the basis of safe driving of intelligent vehicles. Because of the defects of the traditional rule-based association methods of radar and camera, vehicle detection and tracking method based on local trajectory information of radar and camera targets are proposed. The local trajectory information of radar and camera targets can be obtained through data preprocessing. Then, a double-layer data association structure combining spatial location association and local trajectory association is designed. First, the direct linear transformation is used to realize the coordinate alignment. Radar projection coordinates define the region of interest of the camera target, and the target association's initial screening is carried out. Then, dynamic time warping is used to calculate the local trajectory similarity for the target that meets the spatial position relationship to judge the final result of target association. Finally, the federated filter is used to fuse the successfully associated targets. The actual vehicle test results show that the proposed algorithm can improve positioning accuracy by fusing vehicle trajectory information.
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