Distributed H∞ filtering in sensor networks with randomly occurred missing measurements and communication link failures

This paper is concerned with the distributed H∞ filtering problem in sensor networks for discrete-time systems with missing measurements and communication link failures. The sensor measurements are unavailable randomly and the communication link between nodes may be lost. Both of these phenomena occur with known probabilities. The purpose of this problem is to design a filter on each node in the sensor network such that, for all possible measurements missing and communication link failures, the dynamics of filtering error is mean-square stable and the prescribed average H∞ performance constraint is met. This problem is solved by mean of establishing a filter for a constructed two-dimensional (2-D) system in Roesser model. Consensus protocol is introduced into the filter model as local information fusion strategy. In terms of certain linear matrix inequalities (LMIs), sufficient conditions for the solvability of the addressed problem are obtained. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed design approach.