Synthetic Aperture Radar (SAR) image Automatic Target Recognition (ATR) technology is one of the key technologies of artificial image interpretation, which aims to isolate the influence of inherent noise, obtain the potential characteristic information of the target in the region of interest, and provide strong data support for target recognition.In order to improve the accuracy of target recognition in high-resolution SAR images, focusing on the problems of speckle suppression and feature extraction in algorithm design, an automatic target recognition framework for SAR images is designed by combining the traditional Constant False Alarm Rate (CFAR) detection algorithm and the latest research of the Deep Convolutional Neural Network(DCNN).The experiment is based on MSTAR standard data set, and the results of target recognition show the effectiveness of the model.