Dynamic target navigation based on multisensor Kalman filtering and neighbor discovery algorithm

This paper deals with an estimate algorithm which considers optimal control input for dynamic target navigation by using wireless sensor networks and distributed Kalman filter. We propose a novel sensor scheduling algorithm based on a neighbor discovery algorithm for discrete-time linear time-invariant systems. Then we propose an estimate algorithm by sharing predicted estimate values and analyze characteristic of this algorithm. Finally, experimental results show effectiveness of the proposed method in sensor networked feedback systems.