Graphical Models-Based Track Association Algorithm

In the condition of sensor network (SN), to associate local tracks front multiple sensors is a complex task, due to the combination explosion caused by the increasing number of sensors and targets. A new graphical models-based technique for track association is proposed in this paper to deal with the problem. Firstly, by means of the sparse structure inherent in multisensor multitarget tracking scenario, the graphical structure for track association is established; Secondly, the compatibility function of nodes and edges in graph is properly defined to describe the objective function with constrains about track association problem; finally, max-product message passing scheme is employed to obtain the optimal association result. Simulation results demonstrate the efficiency of the presented method.