基于结构多假设目标跟踪算法优化与仿真

摘要

研究雷达跟踪目标性能优化问题,传统多假设算法计算量大、实时性较差,无法应用于实际雷达装备.为解决上述问题,提出一种结构化分枝的多假设目标跟踪算法,同时提出限制最大航迹数量、删除负分航迹、低等级航迹处理、滑动窗口多维分配法、多扫分配法及交互多模型多假设跟踪算法等一系列改进方法,并通过计算机仿真证明改进后的结构化分枝的多假设目标跟踪算法比传统多假设算法及联合概率数据互联算法计算量更小,精度更高,并对改善当前舰载雷达跟踪性能,提高对目标的跟踪能力具有一定的指导意义.%In order to solve the problems of computational complexity, poor real time and practical difficulty to radar equipment of multiple hypotheses target tracking algorithm, this paper introduced a multiple hypotheses target tracking algorithm based on structured branching, and gave some improved methods such as limiting track numbers, deleting minus track, dealing with Bi—Level track and IM3HT. Experimental result shows that this algorithm can significantly reduce errors with higher computational effectiveness when compared with traditional multiple hypotheses tracking(MHT) and joint probabilistic data association( JPDA). The methods have important significances in the improvement of tracking algorithm and tracking abilities of shipborne radars.