本文中提出了一种基于雷达测距的车辆识别与跟踪方法，以准确地识别道路上的车辆目标。首先对采集到的每帧数据采用自适应距离阈值的方法进行聚类分析。在聚类内部采用端点迭代拟合算法提取线段，在此基础上得出目标的特征向量，并据之识别车辆目标。然后通过计算特征向量的代价函数进行多目标关联，利用卡尔曼滤波器根据关联结果更新目标的状态。最后，以智能车辆BJUT-IV配备LMS291激光雷达在校园道路上对本方法进行验证测试，结果表明，提出的方法能够准确地对多个行驶车辆进行跟踪。%A method of vehicle identification and tracking based on radar ranging is proposed in this paper to accurately identify vehicle objects on road. Firstly a clustering analysis is conducted on data collected with an a-daptive distance threshold, and iterative end point fitting ( IEPF) algorithm is adopted to extract line segments with-in a cluster. On this basis the feature vector of object is obtained, with which vehicle object is identified. Then by calculating the cost function of feature vector, multi-object association is performed, and based on the results of as-sociation the state of object is updated with Kalman filter. Finally a verification test of the method is performed on the road in campus by an intelligent vehicle BJUT-IV with laser radar LMS291 . The results show that the method proposed can accurately track multiple moving vehicles.
展开▼
