Distributed Robust Filtering for Wireless Sensor Networks with Markov Switching Topologies and Deception Attacks

Fengzeng Zhu, Xu Liu, Jiwei Wen, Linbo Xie, Li Peng
2020 Sensors  
This paper is concerned with the distributed full- and reduced-order l 2 - l ∞ state estimation issue for a class of discrete time-invariant systems subjected to both randomly occurring switching topologies and deception attacks over wireless sensor networks. Firstly, a switching topology model is proposed which uses homogeneous Markov chain to reflect the change of filtering networks communication modes. Then, the sector-bound deception attacks among the communication channels are taken into
more » ... nsideration, which could better characterize the filtering network communication security. Additionally, a random variable obeying the Bernoulli distribution is used to describe the phenomenon of the randomly occurring deception attacks. Furthermore, through an adjustable parameter E, we can obtain full- and reduced-order l 2 - l ∞ state estimator over sensor networks, respectively. Sufficient conditions are established for the solvability of the addressed switching topology-dependent distributed filtering design in terms of certain convex optimization problem. The purpose of solving the problem is to design a distributed full- and reduced-order filter such that, in the presence of deception attacks, stochastic external interference and switching topologies, the resulting filtering dynamic system is exponentially mean-square stable with prescribed l 2 - l ∞ performance index. Finally, a simulation example is provided to show the effectiveness and flexibility of the designed approach.
doi:10.3390/s20071948 pmid:32244323 fatcat:its4w3m7wrhmnmg23jbgmeey4a