采用独立跟踪区域的划分和公共量测点数据的去藕聚类技术,将原本只适用于单目标跟踪的概率数据关联(PDA)算法改造成能够在强杂波环境中跟踪多个点状目标交叉运动的情况。该算法比传统基于JPDA(联合数据关联)的多目标跟踪算法的计算量和复杂度都小。仿真试验表明,该跟踪算法具有高精度的跟踪性能。 Using the decoupling clustering technique which divides the independent tracking area and the public measuring point data, the algorithm of the probabilistic data association (PDA) originally applied to single-target tracking is modified to be able to track multiple point-like targets in a strong clutter environment Cross-sport situation. Compared with the traditional multi-target tracking algorithm based on JPDA (Joint Data Association), the proposed algorithm has less computational complexity and complexity. Simulation results show that the tracking algorithm has high precision tracking performance.