Recursive Distributed Filtering for a Class of State-Saturated Systems With Fading Measurements and Quantization Effects

This paper is concerned with the distributed filtering problem over wireless sensor networks for a class of state-saturated systems subject to fading measurements and quantization effects. Each sensor node in the network communicates with its neighbors according to the network topology described by a directed graph. The fading phenomena of measurements are assumed to occur in a random way and the attenuation coefficients of the fading measurements are described by a set of random variables with known stochastic properties. By solving two sets of matrix difference equations, an upper bound for the filtering error covariance is presented. Subsequently, with the topology information of the sensor network, such an upper bound is minimized by properly designing the filter parameters. Moreover, the performance of the proposed filter is investigated through establishing sufficient conditions ensuring that the trace of the upper bound is bounded. The relationship between the filter performance and the mean of attenuation coefficient is also discussed. A numerical simulation is exploited to demonstrate the effectiveness of the proposed filtering method.