密集杂波环境下的简化JPDA多目标跟踪算法

为简化联合概率数据关联算法(Joint Probabilistic Data Association, JPDA)的计算复杂度，增强JPDA算法的实时性，设计了一种新的JPDA简化算法。首先根据目标航迹与量测之间的关联规则，定义了一种新的计算关联概率的方法，之后分析公共量测对目标的影响，引入公共量测影响因子修正关联概率。该算法不用进行确认矩阵拆分，有效解决了在密集杂波环境下因回波密度增加而造成的计算上的组合爆炸问题。仿真结果表明，简化的JPDA算法能够在保持对目标有效跟踪的情况下，大大缩短计算时间，提高算法的实时性。 

A Simplified JPDA Multi-target Tracking Algorithm for Dense Clutter Environment

To simplify the computational complexity of Joint Probabilistic Data Association (JPDA) and enhance the real-time performance of JPDA algorithm, a new simplified JPDA algorithm was proposed in this paper. Firstly, according to the association rules between the trajectory and the measurement of the target, a new method to calculate the simple association probability is defined. Then, the influence of the public measurement on the target is analyzed to modify the association probability. The algorithm does not need to split the confirmation matrix, and the problem of combinatorial explosion caused by the increase of echo density in the dense clutter environment can be effectively solved. The simulation results show that the simplified JPDA algorithm can greatly shorten the computation time and improve the real-time performance while keeping effective tracking of the target.