一种杂波环境下的多传感器多目标数据关联算法

Algorithm of Multisensor Multitarget Data Association in Clutter

研究了多传感器多目标的数据关联问题,提出了杂波环境下多传感器多目标跟踪的极大似然关联算法.算法中考虑了传感器对目标的漏检情况,在各个观测站传感器的观测数据不完备的情况下,建立了传感器测量与目标的可行关联分配模型,并综合采用了假点的后验概率比模型,提高了多传感器对同一目标测量的互补性和对弱信号目标的跟踪精度.理论分析和仿真实验结果表明,所提出的算法可实现杂波环境下对弱目标的持续跟踪,并且在确保航迹关联性能和较好跟踪效果的基础上,降低了算法的运算量.

Multisensor multitarget data association is studied in this paper,and the maximum likelihood association algorithm of multisensor multitarget in clutter environment is presented. Considering some circumstances that a single sensor might not be able to acquire enough information about targets,a model of feasible association assignment between sensor measurements and targets is set up, and the post test probability ratio model of false target and the maximum likelihood model of the normal measurement association assignment are integrated so that the complementarity of the measurement of the same target from different sensors is improved, and relative perfect tracks on weak target with improved estimation accuracy is reached. Theoretical analysis and simulation results show that the algorithm presented in this paper may track the weak targets continuously under clutter environment with low calculation load.