This paper introduces a novel Kalman filter-based Line-of-Sight (LOS) guidance law for the curved path-following of unmanned surface vehicles in the presence of environmental disturbances. By using an extended Kalman filter and available measurements, the proposed method efficiently estimates the vehicle’s sideslip angle and compensates for the sideslip effect on path-following performance. Through two simulation scenarios, it has been demonstrated that the proposed guidance law exhibits superior performance compared to the two available guidance methods.