Unscented Kalman Filtering for Nonlinear Systems with Stochastic Nonlinearities under FlexRay Protocol

In this paper, an unscented Kalman filtering problem is considered for a class of nonlinear systems with stochastic nonlinearities under the FlexRay protocol. The phenomenon of stochastic nonlinearities is characterized by the statistical means to account for engineering practice. Moreover, with the FlexRay protocol implemented between the sensors and the filter, an appropriate measurement model is established to characterize the measurement outputs after data transmission via the FlexRay protocol. By considering the stochastic nonlinearities and the FlexRay protocol, an tailored unscented Kalman filtering algorithm is designed where the influence of the stochastic nonlinearities and the FlexRay protocol is quantified. In the end, the effectiveness of the proposed filtering algorithm is verified in estimating the state of nonlinear systems through simulation experiments.