Distributed Fusion Filtering for Time-Varying Stochastic Systems Subject to Multiplicative Noises and Coding-Decoding Scheme

In this paper, the coding-decoding-based distributed fusion (DF) filtering problem is investigated for a class of stochastic systems with multiple sensors and multiplicative noises. The white noise with certain statistical features is utilizing to describe the multiplicative noise, and the coding-decoding communication scheme is adopted to adjust the transmitted data and ensure the data security by means of the uniform quantization method. The primary objective of this paper is that the DF filtering approach is implemented under the codingdecoding communication scheme and multiplicative noises based on the covariance intersection fusion rule. In addition, the local upper bound (UB) on the estimation error covariance is deduced and then the gain matrix is given with the help of determining the solution for the optimal DF. Finally, the simulation example is provided to test the presented fusion filter.