High-precision positioning of underwater targets is an important prerequisite for unmanned surface vehicle (USV) to carry out tasks, such as seabed mapping, channel cleaning, and wreck salvage. However, the existing baseline positioning methods cannot accurately locate the targets in unknown waters. In practical tasks, USV needs to be equipped with side-scan sonar and supplemented by other means to determine the accurate position of underwater targets. In this article, aiming at the underwater target localization problem of the unmanned boat, we first model the underwater target localization process of side-scan sonar. Then, the influence of attitude error on underwater target positioning is analyzed, and the attitude error is eliminated by using an attitude correction matrix. Finally, the discrete Kalman filter algorithm is used to optimally estimate the multi-point measurement data and get the accurate position of the underwater target. The results of simulation experiments and USV integration tests show that the proposed method can effectively reduce the systematic errors in the measurement process and the average positioning accuracy reaches 0. 334 m