Distributed State Estimation over Sensor Networks with Sensor Resolution under Binary Encoding Scheme

In this paper, the distributed state estimation problem is investigated for a class of discrete time-varying nonlinear systems over sensor networks with sensor resolution, where a binary encoding scheme is employed to address bandwidth limitations. The measurement output is converted into a binary bit string, conveyed through a memoryless binary symmetric channel subject to a certain probability of bit flips, and then reconstructed by a decoder. The influence of both sensor resolution and binary encoding scheme on estimation accuracy is considered simultaneously, where a distributed recursive state estimation strategy over sensor networks is constructed. Subsequently, the estimator gain that minimizes the upper bound on the estimation error covariance is obtained by solving Riccati-like difference equations. Finally, the validity of the developed algorithm is displayed through a simulation example.