Aiming at the scale changes, illumination changes, motion blur and background clutter in the target tracking process, a target tracking algorithm combining multi-feature fusion with scale adaption and based on Background-Aware Correlation Filters(BACF)is proposed. Firstly, various feature information of the target and the background are extracted, and weighting fusion is made to the feature distribution weights according to the response graph, to complete the target position prediction. Then, a single HOG feature in the discriminant scale space tracking algorithm is replaced by two complementary features of the Histogram of Oriented Gradient (HOG) feature and the Color Names (CN) to estimate the target scale. Finally, the adaptively updated threshold is selected to update filter model. The simulation results show that the proposed method has higher success rate and accuracy.