To improve the recognition performance of synthetic aperture radar (SAR) image targets, multi-resolution representation and a complex domain convolutional neural network (CNN) are used in combination. Initially, the original SAR image is processed in time and frequency domain to obtain its multi-resolution representation image. Then, the complex domain CNN is used to classify the original image and its multi-resolution representation image. The classification results are weighted using a linearly weighted fusion scheme, and the test sample classification is evaluated according to the fusion result. Finally, the proposed method is tested under standard and extended operating conditions based on the MSTAR data set. The experimental results show that the proposed method is both effective and robust.