Compressive sensing‐based inverse synthetic radar imaging imaging from incomplete data | Zendy

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

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

Author(s) -

Tomei Sonia,

Bacci Alessio,

Giusti Elisa,

Martorella Marco,

Berizzi Fabrizio

Publication year - 2016

Publication title -

iet radar, sonar and navigation

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.489

H-Index - 82

eISSN - 1751-8792

pISSN - 1751-8784

DOI - 10.1049/iet-rsn.2015.0290

Subject(s) - inverse synthetic aperture radar , compressed sensing , synthetic aperture radar , radar imaging , computer science , computer vision , artificial intelligence , iterative reconstruction , data set , radar , remote sensing , geology , telecommunications

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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