Multi-target tracking in inter-occlusion scene is a challenging issue. The paper proposes an anti-occlusion multi-target tracking method based on the progressive spatio-temporal feature model. The method establishes an occlusion reasoning model according to the associated states, overlap and depth of the target. The occluded target is identified by the occlusion reasoning model and re-detected by the progressive spatio-temporal feature model. Firstly, search region is determined by the spatial position parameter in the target feature model. Then, the similarity between the target model and detection is calculated, an adaptive threshold is presented, and the detection with a similarity higher than the threshold is considered as candidate measurement. Finally, the real detection of the target is obtained by matching the temporal feature, and multi-target tracking is completed. Experimental results conducted on MOT15 and MOT17 benchmarks show that the proposed method can effectively identify the occluded target and be robust for tracking inter-occlusion targets in several complicated scenes. Compared with the state-of-the-art methods, the proposed method achieves outstanding performance in accuracy, precision and trajectory completeness.