In order to get more detailed information of radar target, the target recognition method based on high resolution range profile (HRRP) sequence is analyzed. A hidden Markov model (HMM), a convolution neural network (CNN), a recurrent neural network (RNN), and long short-term memory (LSTM), analyzes the development process of different classifiers for HRRP target recognition, and points out the advantages, disadvantages and applicability conditions of different recognition methods. The results show that this study can provide some ideas for the application of appropriate classifiers in different recognition scenarios.