In order to improve the tracking accuracy of fighter in the scene with illumination variation, scale variation,occlusion,and deformation,a kernel correlation filtering algorithm based on multi-feature fusion is proposed.The color feature,texture feature,and convolution feature are fused,and the maximum response value outputted after fusion is the detected fighter position.In addition,the scale filter is adopted to estimate the fighter size.The concept of sidelobe ratio is introduced to judge the fighter occlusion situation while the template is updated.Experimental results show that the accuracy and success rate of the algorithm reach 77.6% and 73.3% respectively.In the cases of fast motion,background clutter,deformation,target out-of-view,illumination variation,rotation,and low resolution,etc.the tracking accuracy and tracking success rate are ranked first compared with the KCF,DSST and MOSSE algorithms.