ISAR imaging using parametric L 0-norm minimization

Gang Li; Xiqin Wang; Xiang Gen Xia

doi:10.1109/RADAR.2012.6212177

ISAR imaging using parametric L ₀-norm minimization

Gang Li^*, Xiqin Wang, Xiang Gen Xia

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

We present a sparsity-driven algorithm of inverse synthetic aperture radar (ISAR) imaging. Based on the parametric sparse representation of the received ISAR signal, the problem of ISAR image formation is converted into the joint estimation of the target rotation rate and the sparse power distribution in the spatial domain. This goal is achieved by parametric L ₀-norm minimization, which ensures the sparsest ISAR image.

Original language	English
Title of host publication	2012 IEEE Radar Conference
Subtitle of host publication	Ubiquitous Radar, RADARCON 2012 - Conference Program
Pages	421-424
Number of pages	4
DOIs	https://doi.org/10.1109/RADAR.2012.6212177
Publication status	Published - 2012
Externally published	Yes
Event	2012 IEEE Radar Conference: Ubiquitous Radar, RADARCON 2012 - Atlanta, GA, United States Duration: 7 May 2012 → 11 May 2012

Publication series

Name	IEEE National Radar Conference - Proceedings
ISSN (Print)	1097-5659

Conference

Conference	2012 IEEE Radar Conference: Ubiquitous Radar, RADARCON 2012
Country/Territory	United States
City	Atlanta, GA
Period	7/05/12 → 11/05/12

Access to Document

10.1109/RADAR.2012.6212177

Cite this

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title = "ISAR imaging using parametric L 0-norm minimization",

abstract = "We present a sparsity-driven algorithm of inverse synthetic aperture radar (ISAR) imaging. Based on the parametric sparse representation of the received ISAR signal, the problem of ISAR image formation is converted into the joint estimation of the target rotation rate and the sparse power distribution in the spatial domain. This goal is achieved by parametric L 0-norm minimization, which ensures the sparsest ISAR image.",

author = "Gang Li and Xiqin Wang and Xia, {Xiang Gen}",

year = "2012",

doi = "10.1109/RADAR.2012.6212177",

language = "English",

isbn = "9781467306584",

series = "IEEE National Radar Conference - Proceedings",

pages = "421--424",

booktitle = "2012 IEEE Radar Conference",

note = "2012 IEEE Radar Conference: Ubiquitous Radar, RADARCON 2012 ; Conference date: 07-05-2012 Through 11-05-2012",

}

Li, G, Wang, X & Xia, XG 2012, ISAR imaging using parametric L ₀-norm minimization. in 2012 IEEE Radar Conference: Ubiquitous Radar, RADARCON 2012 - Conference Program., 6212177, IEEE National Radar Conference - Proceedings, pp. 421-424, 2012 IEEE Radar Conference: Ubiquitous Radar, RADARCON 2012, Atlanta, GA, United States, 7/05/12. https://doi.org/10.1109/RADAR.2012.6212177

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AU - Wang, Xiqin

AU - Xia, Xiang Gen

PY - 2012

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AB - We present a sparsity-driven algorithm of inverse synthetic aperture radar (ISAR) imaging. Based on the parametric sparse representation of the received ISAR signal, the problem of ISAR image formation is converted into the joint estimation of the target rotation rate and the sparse power distribution in the spatial domain. This goal is achieved by parametric L 0-norm minimization, which ensures the sparsest ISAR image.

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