In recent years, the Correlation Filter (CF) method in the field of tracking applications has made remarkable achievements. In this study, an effective occlusion detection mechanism and a scale transformation strategy are proposed to solve the problem that the relevant tracking is insensitive to the effect of target occlusion and the scale change. The tracking target is divided into four rectangular blocks with the center as the origin, and judging the degree of occlusion by calculating the Peak-to-Sidelobe Ratio (PSR) of the four blocks. And a new adaptive scale update strategy is proposed based on the position of the previous four peak response points. The method is tested on a public data set with problems such as occlusion, scale change, light change, etc. The simulation results show that the adaptive scale CF (OSCF) proposed in this study has good scale processing ability.