Abstract: Focusing on the problem of target tracking in the wireless sensors networks, a parallel collaborative tracking algorithm based on particle filter is proposed. This algorithm is applied to the target tracking based on wireless sensor network dynamic clustering model and target motion model. The tracking accuracy is improved by using the parallel particles filters collaboratively with multi-sensors nodes. The optimal target tracking is implemented by using the information fusion and exchanging target states between the dynamic clusters heads. The simulation results show the target tracking problem in the wireless sensor networks can be solved better by the proposed algorithm, the precision of tracking is increased by about 30% compared with the traditional particle filtering algorithms.