Compressive sensing-based algorithm for passive bistatic ISAR with DVB-T signals

Wei Qiu; Elisa Giusti; Alessio Bacci; Marco Martorella; Fabrizio Berizzi; Hongzhong Zhao; Qiang Fu

doi:10.1109/TAES.2015.130761

Compressive sensing-based algorithm for passive bistatic ISAR with DVB-T signals

Wei Qiu, Elisa Giusti, Alessio Bacci, Marco Martorella, Fabrizio Berizzi, Hongzhong Zhao, Qiang Fu

Engineering

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

Abstract

Inverse synthetic aperture radar (ISAR) images can be obtained using digital video broadcasting-terrestrial (DVB-T)-based passive radars. However, television broadcast-transmitted signals offer poor range resolution for imaging purposes, because they have a narrower bandwidth with respect to those transmitted by a dedicated ISAR system. To reach finer range resolutions, signals composed of multiple DVB-T channels are required. Problems arise, however, because DVB-T channels are typically widely separated in the frequency domain. The gaps between channels produce high grating lobes in the image domain when Fourier-based algorithms are used to form the ISAR image. In this paper, compressive sensing theory is investigated to address this problem because of its ability to reconstruct sparse signals by using incomplete measures. By solving an optimization problem under the constraint of signal sparsity, passive ISAR images can be obtained with strongly reduced grating lobes. Both simulation and experimental results are shown to demonstrate the validity of the proposed approach.

Original language	English
Article number	7272859
Pages (from-to)	2166-2180
Number of pages	15
Journal	IEEE Transactions on Aerospace and Electronic Systems
Volume	51
Issue number	3
DOIs	https://doi.org/10.1109/TAES.2015.130761
Publication status	Published - 1 Jul 2015

Bibliographical note

Publisher Copyright:
© 1965-2011 IEEE.

ASJC Scopus subject areas

Aerospace Engineering
Electrical and Electronic Engineering

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10.1109/TAES.2015.130761

Cite this

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title = "Compressive sensing-based algorithm for passive bistatic ISAR with DVB-T signals",

abstract = "Inverse synthetic aperture radar (ISAR) images can be obtained using digital video broadcasting-terrestrial (DVB-T)-based passive radars. However, television broadcast-transmitted signals offer poor range resolution for imaging purposes, because they have a narrower bandwidth with respect to those transmitted by a dedicated ISAR system. To reach finer range resolutions, signals composed of multiple DVB-T channels are required. Problems arise, however, because DVB-T channels are typically widely separated in the frequency domain. The gaps between channels produce high grating lobes in the image domain when Fourier-based algorithms are used to form the ISAR image. In this paper, compressive sensing theory is investigated to address this problem because of its ability to reconstruct sparse signals by using incomplete measures. By solving an optimization problem under the constraint of signal sparsity, passive ISAR images can be obtained with strongly reduced grating lobes. Both simulation and experimental results are shown to demonstrate the validity of the proposed approach.",

author = "Wei Qiu and Elisa Giusti and Alessio Bacci and Marco Martorella and Fabrizio Berizzi and Hongzhong Zhao and Qiang Fu",

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AU - Berizzi, Fabrizio

AU - Zhao, Hongzhong

AU - Fu, Qiang

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Compressive sensing-based algorithm for passive bistatic ISAR with DVB-T signals

Abstract

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