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Sensors 2018, 18(5), 1536; https://doi.org/10.3390/s18051536

Sparsity-Driven Reconstruction Technique for Microwave/Millimeter-Wave Computational Imaging

1
XLIM UMR 7252, Université de Limoges/CNRS, 87060 Limoges, France
2
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
*
Author to whom correspondence should be addressed.
Received: 30 March 2018 / Revised: 24 April 2018 / Accepted: 1 May 2018 / Published: 12 May 2018
(This article belongs to the Special Issue Sensors for Microwave Imaging and Detection)
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Abstract

Numerous prototypes of computational imaging systems have recently been presented in the microwave and millimeter-wave domains, enabling the simplification of associated active architectures through the use of radiating cavities and metasurfaces that can multiplex signals encoded in the physical layer. This paper presents a new reconstruction technique leveraging the sparsity of the signals in the time-domain and decomposition of the sensing matrix by support detection, the size of the computational inverse problem being reduced significantly without compromising the image quality. View Full-Text
Keywords: computational imaging; short-range imaging; microwave; millimeter-wave; sparsity computational imaging; short-range imaging; microwave; millimeter-wave; sparsity
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Fromenteze, T.; Decroze, C.; Abid, S.; Yurduseven, O. Sparsity-Driven Reconstruction Technique for Microwave/Millimeter-Wave Computational Imaging. Sensors 2018, 18, 1536.

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