Variational Filtering algorithm for interdependent target tracking and sensor localization in wireless sensor network
Résumé
A novel algorithm for interdependent sensor localization and target tracking in wireless sensor networks is proposed in this paper. Based on range measurements between sensors and the target, sensor location estimations and that of the target are interdependently improved. The contribution of this work lies in three aspects: first, the algorithm is executed on a fully decentralized cluster scheme to reduce the energy and bandwidth consumption; second, a general state evolution model is proposed to describe the target and activated sensors, since no a priori information of the the target motion is available; finally, the variational method further lightens the communication burden and terminates the error propagation problem. The effectiveness of the proposed algorithm is evaluated and compared in terms of tracking accuracy, localization precision and execution time.