基于杂波感知的双闭环多假设跟踪方法

A Double Closed Loop Multiple Hypothesis Tracking Method Based on Clutter Perception

针对杂波环境下多假设跟踪方法计算量呈指数增长,不易工程应用的问题,提出了一种基于杂波感知的双闭环多假设跟踪方法。该方法在原有的算法框架中加入杂波感知与处理环节,通过减少杂波点迹的数量,大大地减小了虚假航迹的数量;采用双闭环结构对未稳定跟踪和已稳定跟踪的航迹分别进行处理,避免了由虚假航迹引起的聚类扩大或者合并问题,进一步减小了算法的计算量。通过仿真数据验证了该算法能够减小50%的计算量,同时也降低了虚假航迹的数量,由此验证了该算法的有效性。

In this paper, a double closed loop multiple hypothesis tracking method based on clutter perception is proposed to solve the engineering application problem of multiple hypothesis tracking method, since the calculated amount of the multiple hypothesis tracking method in a clutter environment increases exponentially. In this method, a clutter perception and processing module is added into the original algorithm framework, which greatly reduced the number of false tracks, by reducing the number of clutter points. Based on that, a double closed loop structure is used for processing the unsteady track and the steady track respectively, which further reduced the calculated amount of this algorithm, by solving the cluster expansion and merge problem caused by false tracks. It has been verified that the proposed method can reduce 50% of calculated amount, and the number of false tracks is reduced at the same time, which verified the effectiveness of the proposed method.