A Novel Method for Airborne Array-InSAR Tomography Based on Off-Grid Target Modeling and Group Sparsity

Abstract

Airborne array interferometric synthetic aperture radar (array-InSAR) tomography is an effective method for obtaining 3-D point clouds on the ground. However, the quality of point clouds is limited by multiple factors, such as phase noise, reconstruction algorithm, and so on. In this letter, the problem of point cloud stratification is discussed. To solve this problem, the authors propose a novel method. First, the interference phase between multichannel images is filtered to suppress the phase noise. Then, an elevation reconstruction algorithm based on off-grid target modeling and group sparsity is carried out, which can solve the mismatch problem of the target. In the final part, the effectiveness of the proposed method is validated using airborne array-InSAR data from the Sichuan province, China.