Azimuth Ambiguity Suppression for SAR Imaging based on Group Sparse Reconstruction

The classical methods for synthetic aperture radar (SAR) azimuth ambiguity suppression are based on deterministic methodologies. However, the reconstruction with azimuth ambiguity problem is underdetermined. In this paper, we present a group sparse modeling based approach in which the reflectivity of target is extended as group sparse signal and its components are jointly recovered by lq regularization method. The proposed method is verified on airborne SAR data, which shows effectiveness in reducing the ambiguous power while details of the reconstruction are preserved. The azimuth ambiguity [1] in SAR imaging is an underdetermined problem in mathematical view. The sparse signal processing provides SAR imaging with potentials of achieving better imagery quality [2]. The methodology of group sparse allows the efficient reconstruction of signals whose support is contained in the union of a small number of disjoint groups [3]. We address that the azimuth ambiguity problem can be suppressed by group sparse modeling based approach [4]. In the modeling, we focus on analyzing the properties of the azimuth signal. By proper discretion of the scene, the echoes of the observed scene can be expressed as: