Distributed target tracking in asynchronous wireless sensor networks

To reduce the energy consumption of wireless sensor networks during their target tracking, a distributed target tracking method suited to the condition of time asynchronous was proposed. Firstly, dynamic clusters were established according to the distance between each node and the target. The tracking cluster was used as the calculation unit of time. The tracking time calculation in one cluster and sequential transferring among different clusters were implemented by cluster headers. Then, the particle set was separated into some subsets by the parallel particle filter (PPF) algorithm, which were sampled, weighed and resampled in several nodes. Finally, the estimation of local states was implemented by cluster headers through gathering the results uploaded from nodes. The simulation results show that the PPF algorithm has a good tracking accuracy and can reduce communication traffic about 38% compared with the center particle filter (CPF) algorithm.