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Wide-angle SAR imaging based on sub-apertures joint sparse reconstruction

By synthesizing the sub-aperture images at various aspect angles, wide-angle synthetic aperture radar (SAR) can produce a reflectivity estimate for each spatial location and some information on anisotropy, which is useful for scene interpretation and target recognition. In order to improve the imaging resolution and decrease the sampled data, compressed sensing (CS) can be applied to each sub-aperture image formation independently. However, the independent processing is easily affected by the registration errors and the anisotropic scattering behavior of the target, resulting in many desultory points existed in the synthesis image. In this paper, a joint sparse reconstruction method of sub-aperture images is proposed, efficiently solving the above problem. By exploiting the correlation among subaperture images, defining the mixed norm with comprehensive information of full aperture, and constructing the joint sparse reconstruction model of sub-aperture images constricted by the mixed norm, the method can realize the precise match and suppress desultory points in the synthesis image. At last, the experimental data processing results verify the effectiveness and validity of the proposed method.