A tracking method of multi-sensor to track the multiple targets under the condition of low detection probability

A new algorithm was presented to deal with the multi-target tracking problem. Firstly the target number in an interest region was modeled as a stochastic process; secondly the state vector was augmented with target number; and finally the state estimation was carried using the multi-model particle filter (MMPF), and the numerical simulation was proposed to identify the efficiency of this method in multi-sensor/multi-target tracking application. The simulation results show that the improved method can be applied to track the maneuvering targets effectively by using the non-linear dynamic model.