In view of the problem of the existing methods of lowresolution radar target recognition, usually the twostep recognition algorithm is adopted to make feature extraction and target classification, which is not conducive to the improvement of recognition accuracy and the generalization of recognition methods, for the reason mentioned above, an onestep recognition algorithm based on Convolution Neural Network (CNN) for lowresolution radar target is proposed. This algorithm takes the sampled data as input directly, and uses the designed onedimensional CNN to automatically obtain the deep essential features of the data without feature extraction through convolution pooling and other operations, realizing the onestep recognition of the target. The simulation results show that the recognition rate of the onestep recognition method is 10.31% higher than that of traditional twostep recognition method based on artificial feature extraction, and the recognition time of onestep recognition method is 0.142s less than that of twostep recognition method, which proves the effectiveness of onestep recognition method. The onestep recognition method provides a new solution for radar target recognition.