Event-Triggered State Estimation for USV System with Correlated Noises and Packet Losses

This article focuses on the problem of Unmanned Surface Vehicle (USV) system operating in network environments with noise correlation and packet drop occurrences. An innovative event-triggered state estimation method is considered to effectively reduce the impact of noise correlation and packet dropout. The event-triggered state estimator incorporates both a triggering threshold and a correlation coefficient, enabling an optimized balance between transmission frequency and estimation accuracy. Within the proposed framework, the covariance of the prior estimation error is assured to remain bounded. Ultimately, a mock-up of the USV prototype is provided to confirm the pertinent findings.