Off-grid sparse ISAR imaging by Hlog-DCD algorithm

In this paper, a novel computationally efficient algorithm is proposed to achieve high resolution for inverse synthetic aperture radar (ISAR) imaging in the compressive sensing (CS) framework, which is based on dichotomous coordinate descent (DCD) iterations, homotopy, and non-convex regularization. Since traditional CS based methods have to assume that unknown scatterers exactly lie on the pre-discretized grids, otherwise their inversion performance would degrade considerably. Herein we present Hlog-DCD algorithm combined with grid refinement technique to provide performance improvement of the image reconstruction for off-grid target. Experimental results verify the effectiveness of the proposed approach and related analysis.