The tracking algorithm shows poor tracking effect when the moving target is occluded and the scale is changed. A discriminant scale space tracking algorithm combined with particle filter is proposed. Firstly, the target area of two adjacent frames is extracted, the structural similarity of the target area is calculated and compared with the updated threshold to determine whether the target is blocked. Secondly, if occlusion occurs, the particle filter algorithm based on color distribution is enabled to track the target, otherwise, the position filter in Discriminative Scale Space Tracking(DSST) is adopted to determine the target position. Finally, the scale filter is utilized to determine the target scale and the particle filter target model is updated according to the target scale. After the experiment on OTB2015 test set, the accuracy and success rate of the algorithm in this paper are improved compared with that of the mainstream algorithms such as DSST and Kernel Correlation Filter(KCF), especially the best tracking performance after occlusion occurs.