联合稀疏约束的双通道星载SAR图像重建

Reconstruction of Dual Channel Satellite-borne SAR Images Based on Joint Sparsity Constraints

为了提高星载SAR图像质量,提出双通道星载SAR图像重建模型。为此,将用于单幅机载SAR图像的稀疏特性先验推广到两幅星载SAR图像重建问题中,进而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以及用双下降求解方法求解重建模型。验证提出的算法,对Cosmo-SkyMed SAR图像进行重建。试验表明,本文重建模型能够提高SAR图像的距离向和方位向分辨率,改善图像质量,提高SAR图像的解译能力。

In this paper,a new approach to SAR image reconstruction by dual channel satellite-borne SAR is presented.It has been proved that SAR image with sparse characteristic can be expressed by deterministic sparse prior constraint model based on target scattering center theory and backscattering characteristics.Inspired by the sparse characteristic from singles airborne SAR image,the proposed approach is based on scattering center sparse and strong scattering gradient double channel regularization reconstruction model for dual channel spaceborne SAR image,uses the elliptic paraboloid model to estimate the degrade matrix,and solves reconstruction model with double down algorithm.In order to evaluate the proposed reconstruction approach,it is tested with Cosmo-SkyMed SAR data.The experimental results demonstrate that both of range and azimuth resolutions can be extremely improved,comparing with that from reconstruction approach by single channel data.