CET-LOS: An Improved LOS Guidance With Event-Triggered Mechanism Compensating Large Heading Measurement Error for ASVs

Low-cost heading sensors and environmental interference lead to significant heading measurement error (HME) in Autonomous Surface Vehicles (ASVs), necessitating compensation to enhance path-following accuracy. To address this, we propose a compensated event-triggered line-of-sight (CET-LOS) guidance law. The core objective is to rapidly estimate and compensate for HME using an exponential estimation model. Specifically, the exponential model enables fast HME estimation, while an event-triggered mechanism, based on the convergence state of the cross-track error, ensures accurate error estimation. Additionally, the integral term from the integral LOS (ILOS) is utilized to refine the error estimation further. Experimental comparisons of CET-LOS with LOS, ILOS, and adaptive LOS (ALOS) demonstrate its effectiveness. For straight-line paths, the average cross-track error is reduced by 72.3%, 34.5%, and 62.3%, respectively. For complex paths, the reductions are 43.8%, 34.0%, and 29.2%, respectively. These results highlight the superiority of the proposed method.