一种海杂波背景下的目标跟踪数据关联方法

A Method of Target Tracking Data Association in Sea Clutter Background

针对杂波背景下的目标跟踪问题,采用最近邻滤波(NNF)算法和概率数据关联滤波(PDAF)算法对强海杂波背景下的水面舰船目标跟踪进行了理论分析与仿真。并针对密集海杂波环境,在PDAF算法基础上引入二次距离加权概念,对已有PDAF算法的关联概率值计算方法进行改进,对不同密度的海杂波环境中的单目标跟踪进行了仿真。仿真结果表明,该改进算法在密集海杂波环境中的跟踪性能有所提高,能够更有效且可靠实现非机动目标的跟踪。

The problem of surface ship target tracking in strong sea clutter environment is theoretically analyzed and simulated by employing the nearest neighbor filter（NNF） algorithm and the probabilistic data association filter（PDAF） algorithm. Based on the PDAF algorithm, the concept of twice-weighted distance is introduced for the dense sea clutter environment to improve the correlation probability value calculation method of the existing PDAF algorithm, and the single target tracking in the sea clutter environment with different densities is simulated. Simulation results show that the improved algorithm can improve the tracking performance in dense sea clutter environment, hence realize the non-maneuvering target tracking more effectively and reliably. This research may provide reference for accurate tracking of surface ship targets in sea clutter background.