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.