Abstract: In this paper，Probability Data Association（PDA） which is used to track a target originally is improved.The improved method can track dim point cross-moving multi-target in heavy clutter by adopting the division of independent tracking areas and the decoupling and clustering of the public measurement.This paper’s algorithm has the smaller computational load and computational complexity than the traditional tracking algorithm based on Joint Probabilistic Data Association（JPDA）.Simulation result demonstrate that this tracking algorithm has high quality of tracking.

Key words: Probability Data Association（PDA）, Joint Probabilistic Data Association（JPDA）, independent tracking area, heavy clutter, decoupling and clustering

摘要： 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。

关键词: 概率数据关联, 联合数据关联, 独立跟踪区域, 强杂波, 去藕聚类