Aiming at the problem of synthetic aperture radar target recognition,a method combining multi-feature joint representation with adaptive weighting is proposed.The Principal Component Analysis (PCA), monogenic signal,and Zernike moment features are used to describe SAR images,and three corresponding feature vectors are obtained.Based on the joint sparse representation model,three corresponding features are jointly represented.The reconstruction error vectors from different features are fused using adaptive weighting algorithm under the framework of linear fusion.The optimal weights are achieved so the fused results can be improved.Finally,decision is made based on the fused reconstruction errors.Experiments are conducted on the MSTAR dataset for the 10-class problem under the standard operating condition,the conditions of noise corruption and partial occlusion,and the results verify the effectiveness of the method.