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Superresolution inverse synthetic aperture radar (ISAR) imaging using compressive sampling

descriptionPublicationkeyboard_double_arrow_right Article 23 Apr 2010Publisher:SPIEJournal:SPIE Proceedings, volume 7,699, page 76990A (issn: 0277-786X, Copyright policy )
Authors: Suman K. Gunnala; Saibun Tjuatja;

doi: 10.1117/12.850225

Superresolution inverse synthetic aperture radar (ISAR) imaging using compressive sampling

Abstract

A method based on compressive sampling to achieve superresolution in ISAR imaging is presented. The superresolution ISAR imaging algorithm is implemented by enforcing the sparsity constraints via random compressive sampling of the measured data. Sparsity constraint ratio (SCR) is used as a design parameter. Mutual coherence is used as a quantitative measure to determine the optimal SCR. ISAR data for full angular sector as well as different partial angular sectors are utilized in this study. Results show that significant resolution enhancement is achieved around optimal SCR of 0.2.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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