Recursive Distributed Filtering for 2-D Shift-Varying Systems Over Sensor Networks Under Random Access Protocols
Jinling Liang, Zidong Wang, Fan Wang · 2021
This chapter is concerned with the distributed filtering problem for a class of two-dimensional shift-varying systems over sensor networks subject to random access (RA) protocol. The communication between the sensor nodes and the filters is implemented through shared channels of limited capacity. To avoid data collisions, the RA protocol is applied to determine the transmission order of the packets for each sensor. The considered scheduling behavior is characterized by mutually uncorrelated random variables with known probability distributions. Recursive distributed filters are proposed to estimate the system state through available information from both individual and neighboring nodes in the sensor network according to a given topology. Sufficient conditions are first established, via intensive stochastic analysis and mathematical induction, on the existence of an upper bound of the estimation error variance. Then, by means of a matrix simplification technique, the desired filter gains are designed to optimize the obtained upper bound at each step. Finally, a practical example is given to verify the effectiveness of the proposed filter strategy. [167 words]