Abstract: Objectives To address the challenge of path-following for Unmanned Surface Vehicles (USVs) in complex environments, including wind speed variations and initial position deviations, this study proposes an Time-varying Sideslip Compensation Adaptive Line-of-Sight (TSC-ALOS) guidance algorithm. The aim is to enhance the accuracy and stability of USV path-following under varying environmental disturbances. Methods The TSC-ALOS method dynamically compensates for the sideslip angle changes caused by time-varying environmental disturbances, using real-time wind measurement data. By optimizing the desired heading angle through sideslip compensation, the algorithm improves the robustness and adaptability of USV guidance. A series of numerical simulations were conducted in practical sea environments to evaluate the performance of the TSC-ALOS algorithm under various scenarios, including no-wind, fixed-wind, and random-wind conditions. The algorithm’s performance was compared with the Adaptive LOS (ALOS) and traditional LOS algorithms in terms of key metrics such as lateral tracking error and heading stability. Results Simulation results demonstrate that under no-wind conditions, both TSC-ALOS and ALOS achieved significantly better path-following performance compared to traditional LOS, particularly in turning scenarios. In fixed-wind (8.37 m/s and 16.73 m/s) and random-wind environments, TSC-ALOS exhibits greater robustness by significantly reducing lateral tracking errors compared to ALOS and LOS. Specifically, when initial position deviations are present, the TSC-ALOS algorithm reduce average lateral tracking errors by 24.6% compared to ALOS and by 36.8% compared to LOS. Furthermore, TSC-ALOS shows superior heading stability and path-following accuracy under sharp turning and strong wind disturbances. Conclusions The TSC-ALOS algorithm provides significant advantages over traditional LOS and ALOS algorithms in various operational environments, particularly under complex and dynamic conditions. Its ability to dynamically compensate for sideslip angle changes improves the tracking accuracy and stability of USVs, ensuring safe and reliable navigation. This research contributes to the development of autonomous navigation systems for USVs and aligns with international maritime safety and performance standards such as those set by the International Maritime Organization (IMO). Future research directions include further optimization of the algorithm for broader applications, such as multi-USV cooperative navigation and real-time collision avoidance in congested waterways.