Distributed Optimal Filter for Networked Stochastic Uncertain Systems with Correlated Noises and Fading Deception Attacks

This paper studies the distributed security estimation problems for networked stochastic uncertain systems with correlated process and measurement noises and fading deception attacks. Many measurement data from neighbor nodes are first compressed by a weighted measurement fusion algorithm in the least square at each sensor node. Then, a distributed optimal filter in the linear minimum variance sense is presented based on compressed measurement data. It has the same estimation accuracy as and lower computational cost than that based on uncompressed measurement data. A Simulation example verifies the effectiveness of the proposed algorithms.