Online Identification Method for Motion Model Parameters of Unmanned Surface Vehicle

In order to improve the autonomous navigation and control performance of unmanned surface vehicles (USVs) in complex marine environments, this paper studies the online tracking and identification method of USV motion model parameters. This paper proposes an online identification strategy that introduces a forgetting factor to address the difficulty in accurately obtaining USV motion model parameters and the issue of time-varying parameters under different motion states. The strategy can update model parameters in real-time, enhancing the adaptability and accuracy of the model. The application effect of the proposed algorithm in parameter identification of USV motion model was verified by building an online identification simulation verification platform. The research results show that the proposed method improves the accuracy and applicability of parameter identification, providing reliable technical support for autonomous navigation and intelligent control of USVs. The research results of this article not only enrich the theoretical system of USV motion model parameter identification, but also provide important technical references for the practical application of USV, which is of great significance for promoting the development and application of USV technology.