Aimed at the problems that tracking failure remains in visual tracking, being caused by complex scenes such as scale changes and occlusion, a target scale estimation algorithm with adaptive change of scale aspect ratio is proposed. An aspect ratio estimation of the target is realized by adopting 35×35 scale factors in the algorithm. In order to reduce the amount of calculation, the twodimensional scale sampling factor is selected by hierarchical scale estimation. By so doing, not only the optimal scale of the target is determined, but also the algorithm is improved. In order to further improve the robustness of the tracking algorithm, the Euclidean distance of the response vector between two adjacent frames is used as the criterion for judging whether the template is updated. The scale estimation and template update module proposed in this paper are introduced into the current three excellent correlation filtering algorithms DSST, HCF and OSA. The experiment results show that compared with the original algorithm, the tracking success rate and accuracy are improved significantly by using the new algorithm. On the OTB100 dataset, the success rate increases by 1.3% ,1.4% and 1.4% respectively compared with the above three original algorithms. The accuracy increases by 1.2%, 1.3% and 1.0% respectively, especially in complex scenes such as scale changes and target occlusion. The new algorithm is advantageous to the visual tracking.