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

Sonia Tomei; Alessio Bacci; Elisa Giusti; Marco Martorella; Fabrizio Berizzi

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

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Author(s): Sonia Tomei ^{1, 2} ; Alessio Bacci ^{1, 2} ; Elisa Giusti ^{1, 2} ; Marco Martorella ^{1, 2} ; Fabrizio Berizzi ^{1, 2}
- Affiliations: 1: Department of Information Engineering, University of Pisa, Pisa, Italy ;
  2: CNIT Radar and Surveillance System (RaSS), Pisa, Italy
Source: Volume 10, Issue 2, February 2016, p. 386 – 397
DOI: 10.1049/iet-rsn.2015.0290 , Print ISSN 1751-8784, Online ISSN 1751-8792

Received 04/06/2015, Accepted 04/08/2015, Revised 24/07/2015, Published 01/02/2016

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.

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