A Distributed Target Tracking Algorithm Based on Asynchronous Wireless Sensor Networks

To reduce the energy consumption in wireless sensor networks during target tracking, a distributed target tracking method applied in asynchronous wireless sensor networks was proposed. Firstly, the dynamic clusters were constructed and adjusted according to the distances between nodes and target, which were the unit for time computing. The cluster headers were responsible for was calculation and transferring of tracking time among different clusters. Then, the set of particle was separated to some subsets by parallel particle filter, which was sampled, weighed and resampled in several nodes. Finally, the estimation of local states was implemented by cluster header through gathering the results uploaded from each node. The simulation results show that parallel particle filter has good performances on tracking accuracy and can reduce communication traffic about 38% compared with center particle filter.