Distributed State Estimation Based on Quantized Observations in a Bandwidth Constrained Sensor Network

A distributed state estimation scheme based on quantized observations in wireless sensor network (WSN) is proposed. Unlike the SOI-KF approach, we address the state estimation problem in two steps: firstly, local sensors and the fusion center apply the decentralized estimation scheme (DES) to design the quantized message function and the fusion function; secondly, the fusion center constructs a linear filter to obtain the state estimation by minimizing an upper bound of the error power norm. The optimal filter is computed by the linear matrix inequality (LMI) solver. An example is presented to demonstrate the efficiency of our method.