基于证据理论的数据关联算法

数据关联技术是多传感器目标跟踪系统中最核心而且也是最重要的部分。由于缺乏跟踪环境的先验知识以及受传感器自身性能的制约，整个量测过程不可避免地引入量测误差，密集环境中的目标跟踪比较困难。针对这个问题，提出的新算法利用概率数据关联方法进行密集杂波环境下的数据关联，结合证据理论的思想对多传感器量测信息进行优化组合，有效地减小了量测误差对跟踪目标的影响。通过仿真结果可以看出,改进算法大大提高了跟踪精度，并具有良好的抗干扰能力，适用于解决工程实际问题。

Data association algorithm based on evidence theory

Data association technology is the key part in multi-sensor target tracking system. For the lack of priori knowledge of tracking environment and the restriction of sensor’s performance, the introduced error is unavoidable during measuring process, and the tracking is difficult. Aiming at the problem, a new algorithm based on the probability data association method combining with evidence theory is used to make association under dense clutter environment. After optimization of multi-sensor information, the influence from measure error is lowered, and it can be seen from the simulation result that the improved algorithm greatly advances tracking accuracy and owns favorable anti-jamming ability which is suitable for engineering works.