Distributed Fusion Filtering for Multi‐Sensor Multi‐Rate Systems With Packet Disorders Under Hybrid Cyber Attacks

This article investigates the distributed fusion (DF) filtering issue for multi‐sensor multi‐rate systems (MSMRSs) with packet disorders (PDs) under hybrid cyber attacks (HCAs). The PDs caused by random transmission delay are characterized by a random variable that has the known probability distribution, and two groups of Bernoulli random variables are adopted to depict the occurrence of HCAs. To facilitate the design of the filtering scheme, a virtual measurement method is introduced to transform the original multi‐rate systems into single‐rate systems. The purpose of this paper is to design a new local filtering scheme handling PDs, HCAs as well as stochastic nonlinearities simultaneously, and minimize the upper bound (UB) on each local filtering error covariance (LFEC) by selecting an appropriate gain matrix. By using the mathematical induction method, a sufficient condition is obtained to ensure that each LFEC is uniformly bounded. In addition, local estimates are fused based on the inverse covariance intersection (ICI) fusion method. Finally, it is shown that the proposed fusion filtering algorithm is effective through a simulation experiment.