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According to problems of cluttered environment or the low contrast between infrared target imaging and background, we extract the gray characteristics of target and use the particle filter algorithm which recursively forecast and update the sample sets of the state space to approximate the posterior density probability. In order to further increase the accuracy of tracking, we fuse the Mean Shift algorithm to search for target in local area. The bandwidth of kernel function in Mean Shift algorithm can also deal with the target occlusion problem effectively. Experimental results indicate the proposed method can not only improve the efficiency of the algorithm and overcome the particle degeneracy phenomenon, but also has good performance in occlusion.