Classification and recognition of aerial targets by using the radar is a key technology in the field of signal processing of the radar.At present,most target recognition methods by using the radar have poor generality and high requirements on the radar.To solve this problem,this paper proposes a method of aerial target recognition based on the processing of modulation spectrum graphs by using the Convolutional Neural Network (CNN),after visualizing the periodic information of modulation spectrum of the target echo.The modulation spectrum graph of the target automatically learns the target features through the layer-by-layer transformation of the CNN,and finally the aerial targets are classified and recognized by using the classifier.This method avoids the traditional way of manually formulating the characteristics of the modulation spectrum,and realizes an end-to-end recognition of aerial targets.The experimental results show that the CNN model based on the modulation spectrum graph has higher accuracy in aerial target recognition,and the model has better robustness and generalization ability.