As a challenging visual task，single target tracking plays an important role in the industrial and military fields. From the traditional method with image features as the core to the deep learning method centered on network architecture design，it has shown a lot of research value. The development process of single target tracking is summarized in this paper. Some popular data sets are introduced. The correlation filter methods based on speed and the deep learning methods based on high accuracy are taken as the main principles. The design ideas of some baseline methods and high performance methods are researched. Finally，the methods of various architectures are summarized，and the subsequent research trends are forecasted.