Abstract: Due to synthetic aperture radar (SAR) image sample data is insufficient,and the similarity of intra-class images,which causes difficulty in recognition. A distance metric learning method was proposed for SAR image recognition. The method was arranged to use CNN networks to obtain the feature distribution of the image,and use the LSTM networks to strengthen the correlation between images. Based on the cosine similarity distance measurement method,the matching degree between images was calculated,and the results were classified based on the attention mechanism. Combined with the training method of few-shot learning,the training experiments were carried out with pre-training strategies and using the public MSTAR data set to perform SAR image recognition. The results show that the recognition rate of the method can reach up to 99.3%,be 2.5% higher than SVM.