A method to combine nonlinear correlation information entropy (NCIE) and multi-resolution representation is proposed for synthetic aperture radar (SAR) target recognition. NCIE is employed to select the multi-resolution representation of an original SAR image, and several resolutions with strong intrinsic correlation are obtained. Then, the joint sparse representation is used to characterize and classify the selected multi-resolution samples simultaneously. Experiments are conducted in which various operating conditions are employed to test the different methods based on the MSTAR dataset. The experimental results demonstrate the validity of the proposed method.