RETRACTED: Dynamic Nearest Neighborhood Collaboration Target Tracking for WSN (Retracted Article)

Target tracking is one of the most important applications for wireless sensor networks. Generally, multi-sensors working collaboratively can achieve better performance but with high-energy consumption in target tracking. In this paper, a dynamically clustering algorithm, called nearest neighborhood collaboration, is proposed for collaborative target tracking in wireless sensor networks. It selects cluster head based on minimum distance between predicted target position and sensor nodes. Cluster head forms the cluster of tasking sensors in its neighborhood and fulfills estimation update, next state prediction, and executes information fusion based on central Kalman Filter. Simulation results show that, compared with existing sensor scheduling algorithm, the proposed multisensor scheduling scheme not only achieve superior tracking accuracy but also energy saving, it is also robust to the uncertainty of process noise. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Organizers of 2011 International Conference on Energy and Environmental Science.