Compressive sensing-based inverse synthetic radar imaging imaging from incomplete data

The applicability of compressive sensing (CS) to radar imaging has been recently proven and its capability to construct reliable radar images from a limited set of measurements demonstrated. In this study, a common framework for inverse synthetic aperture radar (ISAR) imaging via CS is provided and a CS-based ISAR imaging method is proposed. The proposed method is tested for application such as image reconstruction from compressed data, resolution enhancement and image reconstruction from gapped data. The effectiveness of the proposed method is demonstrated on real datasets and the performance evaluated by means of image contrast.