As a small surface intelligent task platform, the Unmanned Surface Vessels (USV) have such advantages as good mobility, strong concealment, and a high degree of automation, which have become a hot spot of research at home and abroad. The USV manipulating model is the basis for the realization of such control operations as autonomous navigation and intelligent obstacle avoidance, and its identifying accuracy directly affects the quality of the final control effect.In order to overcome the effect of “parameter cancellation” occurring in the identifying process, and to improve its identifying accuracyan algorithm for model parameter identification based on the step-by-step processing of experimental data is presented.The working procedures of the algorithm are given in detail, and the model parameters are obtained by a manipulating test operated on the lake. Finally, an experiment is implemented on the identified USV model and a real USV respectively, and the correctness of the identified model is verified through a comparison between the experimental data and the simulation results.