The invention discloses a beam jitter model parameter real-time identification method based on a particle swarm algorithm, and the method comprises the following steps: firstly, building a beam jittermodel; secondly, collecting a light beam jitter time sequence signal; thirdly, determining an identification error criterion function; and then, carrying out global random search on the parameters ofthe light beam jitter model by utilizing a particle swarm algorithm so as to obtain the optimal parameters of the model, thereby realizing intelligent optimization of the model parameters. Compared with an existing method, the method has the most remarkable characteristics of random initial value, high calculation speed and high real-time performance. Moreover, in the iteration process, through self-adaptive change of an inertia weight factor, the ability of the algorithm to jump out of local convergence is greatly improved, and meanwhile, the efficiency of the algorithm can be improved. In addition, the method does not need an additional auxiliary system or manual debugging, and is low in implementation cost; and the method can be used for identifying the parameters of the light beam jitter model in different systems, and is high in transportability.