Compressive sensing for interferometric inverse synthetic aperture radar applications | Zendy

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

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Compressive sensing for interferometric inverse synthetic aperture radar applications

Author(s) -

Bacci Alessio,

Staglianò Daniele,

Giusti Elisa,

Tomei Sonia,

Berizzi Fabrizio,

Martorella Marco

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.2015.0563

Subject(s) - compressed sensing , synthetic aperture radar , signal reconstruction , interferometry , iterative reconstruction , computer science , inverse synthetic aperture radar , interferometric synthetic aperture radar , inverse problem , noise (video) , radar imaging , algorithm , inverse , radar , signal to noise ratio (imaging) , signal (programming language) , artificial intelligence , signal processing , image (mathematics) , mathematics , optics , physics , telecommunications , mathematical analysis , programming language , geometry

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

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