In order to realize robust tracking of infrared target in complicated background with lots of disturbed factors, this paper proposes an infrared target tracking method based on multi-feature correlation filter. Considering the visual attention mechanism and motion mechanism, the spatial feature and motion feature are extracted firstly. Then the multi-feature weighted function is generated by fusing the above two features and the improved convolution feature. Secondly, on the basis of traditional correlation filter, the tracking framework vie weighted correlation filter is presented by introducing multi-feature weighted function which could represent the importances of different candidate regions. Finally, the confidence map which indicates the best target location is computed. The experiments under 6 sequences with different conditions demonstrate that the average increase of success rate of the proposed method has increased by about 15% compared with other traditional methods, and the proposed method is applicable to infrared target tracking under different conditions efficiently, such as similar alias target, occlusion, thermal radiance variation of background and detector motion. ©, 2015, Board of Optronics Lasers. All right reserved.