联合稀疏约束的双通道星载SAR图像重建

摘 要：针对提高星载SAR图像质量的问题，研究双通道星载SAR图像重建模型。由目标散射中心理论和后向散射特性分析，得出SAR图像具有稀疏特性，并且能够用确定性稀疏先验约束表达。将稀疏特性先验从单幅机载SAR图像处理问题中推广引入到两幅星载SAR图像重建问题中，提出基于散射中心稀疏和强散射梯度的双通道正则化重建模型，并采用椭圆抛物面模型估计重建中的降质矩阵，用双下降求解方法求解重建模型。并用Cosmo-SkyMed数据进行了实验验证。实验表明，该重建模型能够提高SAR图像的距离向和方位向分辨率，改善图像质量，提高解译能力。

Reconstruction of Dual Channel Satellite-Borne SAR Image With Joint Sparsity Constraints

Abstract: In this paper，we consider the problem of SAR image enhancement used dual channel satellite-borne SAR image reconstruction model．Previous work proved the SAR image with sparse characteristic which can be expressed by deterministic sparse prior constraint model based on target scattering center theory and backscattering characteristics．So we inspired by a sparse characteristic from singles airborne SAR image，proposed reconstruction method based on scattering center sparse and strong scattering gradient double channel regularization reconstruction model for dual channel space-borne SAR image．used the elliptic paraboloid model to estimate the degrad matrix，with double down algorithm to solve reconstruction model．The proposed algorithms are applied to Cosmo-SkyMed SAR data，the resulting images are found to improve distance and azimuth resolution compare with single channel data．