When the targets scale changes or when the target is occludedthe Kernel Correlation Filtering (KCF) tracking algorithm cannot ensure long-time tracking. To solve the problema scale-adaptive and anti-occlusion long-time tracking algorithm is proposed.FirstlyHOG features and color (CN) features are fused and a scale filter is added to estimate the scale of the target.Secondlythe Average Peak Correlation Energy (APCE) index is introduced to determine whether the target is occluded. When the target is occluded SVM classifier is used to recheck the position of the target after occlusion.Finallyaccording to APCE and maximum correlation response value of the position filterthe corresponding model updating strategy is selected.Two data setsOTB100 and UAV123are selected for experiment. The experimental results show that the improved algorithm can effectively deal with target scale change and target occlusionand realize long-time and stable tracking.