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

The applicability of Compressive Sensing (CS) to ISAR has been widely discussed in the last few years. In particular, CS based ISAR image reconstruction algorithms have been developed and their effectiveness proven when dealing with incomplete ISAR data. Resolution enhancement has also been identified as a case for which CS can be effectively applied to ISAR imagery. In this case, the acquired signal can be interpreted as an incomplete data in the frequency/slow-time domain and CS used to reconstruct the super-resolved ISAR image. In this paper, an exhaustive performance analysis is carried out also as a comparison among CS and conventional super resolution techniques. Several concepts and methods are introduced in order to define effective performance analysis that is not simply based on a visual inspection.

The applicability of interferometric inverse synthetic aperture radar (InISAR) techniques to images reconstructed via\ud compressive sensing (CS)-based algorithms is investigated. Specifically, the three-dimensional (3D) reconstruction algorithm is\ud applied after exploiting CS for data compression and image reconstruction. The InISAR signal model is derived and formalised\ud in a CS framework. A comparison between conventional CS reconstruction and global sparsity constrained reconstruction\ud techniques is performed for different compression rates and different signal-to-noise ratio conditions. Performances on the 2D\ud and 3D reconstructions are evaluated. Results obtained on real data acquired during the NATO-SET 196 trial are shown