Distributed Kalman Filter with Information Matrix Weighted Consensus Strategies

An information matrix weighted consensus strategy is proposed to improve the consensus based distributed Kalman filter(DKF) algorithm in the estimation fusion of sensor networks.In this method,each node fuses the estimates from its neighbors according to the uncertainty of the estimates.Based on the proposed method,the consensus weights optimization problem is also discussed to achieve the better performance.The simulation results demonstrate that the proposed algorithms not only improve the accuracy of the state estimate,but also largely enhance the consistency of the state estimate achieved by each node.