The invention relates to a multi-model self-adaptive fusion filtering method of a ship dynamic positioning system and belongs to the technical field of ship dynamic positioning. The method includes the steps: (1), building a ship three-degree-of-freedom low-frequency and high-frequency motion model, and acquiring a filter state formula and a measuring formula; (2), utilizing a differential global positioning system and a platform compass to measure position information and a heading angle, and collecting information in real time; (3), utilizing prior information and posterior information to initialize input of a model-based filter; (4), on the basis of a system model, utilizing a strong tracking filter and a Sage-Husa filter for parallel filtering; (5), subjecting the model to probability updating, and utilizing residual covariance output by the filters to calculate model probability matched with the model; (6), according to the model probability, acquiring fusion output of multi-model state estimation, namely ship position and heading information. The multi-model self-adaptive fusion filtering method has the advantages of strong robustness, high accuracy in Sage-Husa filter state estimation, stable system, high positioning accuracy and the like.