An Event-Triggered Unscented Kalman Filter with Correlated Noises and Random Packet Dropouts

Considering the effects of correlated noises and random packet dropouts on filter performance, the design of an event-triggered filter for a class of nonlinear networked control systems with correlated noises and random packet dropouts is studied in this paper. Under the assumptions that the process noise and measurement noise of the system are cross-correlated in one-step and the measurement values are randomly lost during transmission, an event-triggered filter based on unscented Kalman filter is proposed and implemented by introducing noise correlation coefficients into the filter, compensating for the lost measurement values, and designing an event-triggered mechanism whose threshold value can change with the filtering process. Finally, the designed event-triggered filter is verified to maintain good estimation performance while reducing the number of measurement transmissions through simulation.