Mixed-Norm Regularization-Based Polarimetric Holographic SAR 3-D Imaging

In 3-D synthetic aperture radar (SAR) imaging, the elevation reflectivity function of each azimuth-range pixel is typically recovered through a large number of data collected by parallel flight tracks. Especially for holographic SAR (HoloSAR) tomography with high-resolution and panoramic 3-D imaging capabilities, it provides many important features for applications such as urban monitoring and 3-D mapping. In recent years, the utilization of polarimetric SAR data has been found to have tremendous potential in the performance improvement of 3-D reconstruction. In this letter, we propose a novel L-2,L-1 -norm-based polarimetric HoloSAR imaging method that utilizes the structural correlation between the echoes acquired from different polarimetric channels to achieve high-quality 3-D scene recovery. Compared with typical spectrum estimation-based and compressive sensing (CS)-based methods that only consider the single-polarimetric data, the proposed method can improve the accuracy and robustness of 3-D reconstruction. Experimental results based on the real GOTCHA dataset verify the feasibility and potential of the proposed method.