Distributed Federated Kalman Filter Fusion over Multi-Sensor Unreliable Networked Systems

This paper is concerned with the problem of distributed federated Kalman filter fusion (DFKFF) for a class of multi-sensor unreliable networked systems (MUNSs) with uncorrelated noises. An optimal DFKFF algorithm of MUNSs without buffer is presented, and rigorously proved to be equivalent to centralized optimal Kalman filter fusion (COKFF) algorithm of MUNSs without buffer. Finite length buffers deal with measurement delay or loss, and a suboptimal DFKFF algorithm of MUNSs with finite length buffers is proposed based on the optimal local Kalman filter with a buffer of finite length for each subsystem. Compared with COKFF algorithm of MUNSs with buffers, the proposed DFKFF algorithm of MUNSs with buffers has stronger fault-tolerance ability. Two simulation examples are given to illustrate the effectiveness of the proposed approaches.