Recursive Distributed Filtering for a Class of State-Saturated Systems With Fading Measurements and Quantization Effects
针对无线传感器网络中状态饱和系统受衰落测量和量化效应影响的问题，提出一种递归分布式滤波方法，通过最小化滤波误差协方差的上界来设计滤波器参数，并分析了衰减系数均值对滤波性能的影响。
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.