Decentralized optimal H∞ fusion estimation for multi-sensor networked systems with two-channel hybrid attacks.

Abstract

The article aims at the decentralized optimal H_∞ fusion estimation issue for multi-sensor networked systems with insecure network communications, where hybrid attacks consisting of stochastic deception and denial-of-service attacks happen on both the sensor-to-local filter channel and the local filter-to-fusion center channel simultaneously. Some random variables obeying Bernoulli distributions are utilized to depict the hybrid attacks existing in two classes of communication channels in a unified framework. Relying on a novel augmentation method, the fusion estimation error system with globally internal dynamics is obtained. Two sufficient conditions to assure the corresponding H_∞ performance and exponentially mean-square stability of the local and fusion estimation error systems are derived. To reduce the adverse effect of hybrid attacks, the decentralized optimal H_∞ fusion filter with better H_∞ performance index than each local H_∞ filter is presented by linear matrix inequality technique. An actual civil aircraft system demonstrates the algorithms to be valid.