Compressive sensing for interferometric inverse synthetic aperture radar applications

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

doi:10.1049/iet-rsn.2015.0563

Compressive sensing for interferometric inverse synthetic aperture radar applications

Alessio Bacci^*, Daniele Staglianò, Elisa Giusti, Sonia Tomei, Fabrizio Berizzi, Marco Martorella

^*Corresponding author for this work

Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English
Pages (from-to)	1446-1457
Number of pages	12
Journal	IET Radar, Sonar and Navigation
Volume	10
Issue number	8
DOIs	https://doi.org/10.1049/iet-rsn.2015.0563
Publication status	Published - 2016

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© The Institution of Engineering and Technology.

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1049/iet-rsn.2015.0563

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title = "Compressive sensing for interferometric inverse synthetic aperture radar applications",

abstract = "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.",

author = "Alessio Bacci and Daniele Staglian{\`o} and Elisa Giusti and Sonia Tomei and Fabrizio Berizzi and Marco Martorella",

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year = "2016",

doi = "10.1049/iet-rsn.2015.0563",

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T1 - Compressive sensing for interferometric inverse synthetic aperture radar applications

AU - Bacci, Alessio

AU - Staglianò, Daniele

AU - Giusti, Elisa

AU - Tomei, Sonia

AU - Berizzi, Fabrizio

AU - Martorella, Marco

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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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U2 - 10.1049/iet-rsn.2015.0563

DO - 10.1049/iet-rsn.2015.0563

M3 - Article

AN - SCOPUS:85017463820

SN - 1751-8784

VL - 10

SP - 1446

EP - 1457

JO - IET Radar, Sonar and Navigation

JF - IET Radar, Sonar and Navigation

IS - 8

ER -

Compressive sensing for interferometric inverse synthetic aperture radar applications

Abstract

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