基于置信规则推理方法的雷达目标跟踪

Radar target tracking via belief rule-based methodology

针对雷达目标跟踪中数据相关联的问题,提出一种基于雷达目标航向和速度对雷达数据进行数据关联的方法,解决目标密度较大时所出现的目标误跟或丢失问题,并采用基于置信规则库(belief rule-based,BRB)的方法建立了目标速度与航向的置信规则库,通过证据推理(evidential reasoning,ER)算法解决了不同量纲数据之间的冲突问题,从而验证了此方法的可靠性。实验结果表明,其真实目标置信度可达到95%以上。最后,运用此方法将得到的真实目标点进行Kalman滤波,实现对雷达目标的跟踪,通过Monte Carlo仿真验证了此方法具有很好的目标跟踪效果。

To address the data association problems in radar target tracking, a method of associating radar data ac?cording to radar target course and speed is proposed. It aims to troubleshoot erroneous targeting or target loss in the e?vent of a large density of targets. The method adopts the belief rule?based ( BRB) method to establish the rule base of the navigation velocity and course of radar targets. Through evidential reasoning it can mitigate the conflict between different dimensional data and thus proves reliable. The experimental results show that it can reach a real objective confidence of more than 95%. Finally, the real target points obtained by this method are filtered using a Kalman filter to track the radar targets. Monte Carlo simulation verifies that this method shows excellent radar target tracking.