Distributed IMM-information Kalman filter based on consensus filter for maneuvering target tracking in wireless sensor networks

This paper discusses distributed estimation in discrete linear systems for target tracking by wireless sensor networks. First, a distributed Kalman filter is presented in the form of an information filter based on consensus theory. In the distributed approach, each sensor node communicates only with its neighbors and there is no central node. In the next step, considering the maneuverability of the target and the absence of a single motion model, the algorithm of the interactive multiple model (IMM) based on the distributed information filter (DIMMIKF) is designed. Moreover, the Lyapunov stability of the proposed algorithm is proved. Finally, the simulation results show that this algorithm performs better than similar algorithms.