Particle Filtering for Nonlinear Systems with Round-Robin Protocol and Uniform Quantization

In this paper, the particle filter problem is investigated for a class of nonlinear systems with communication constraints. The communication between sensor and remote filter is subject to uniform quantization effects. Moreover, in order to solve the problem of limited network capacity, the Round-Robin protocol is introduced in this paper, which can effectively avoid communication conflicts and reduce packet loss. Through mathematical hypothesis and stochastic analysis, an explicit expression of likelihood function combined with the probability information of networked phenomenon is established under the recursive Bayesian estimation framework. A novel particle filter algorithm is proposed for nonlinear state estimation in the simultaneous presence of uniform quantization and Round-Robin protocol. Finally, a simulation example is given to illustrate the effectiveness of the proposed particle filtering method.