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On adaptive compressive sensing and radar target recognition
Author(s): Ismail Jouny
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Paper Abstract

Adaptive or sequential compressive sensing has received considerable attention recently. While some researchers argue that there are fundamental limits to adaptive sensing that prevents it from outperforming non-adaptive compressive sensing, others have shown that adaptive sensing of sparse signals may help speed up applications such as target detection and/or classification, and might even expedite the signal reconstruction process with less compressive measurements. This paper examines the benefits of adaptive compressive sensing of radar target backscatter with emphasis on target classification (which is accomplished using sequential hypotheses testing) and compares the results to non-adaptive compressive sensing of noisy radar signatures.

Paper Details

Date Published: 30 April 2018
PDF: 10 pages
Proc. SPIE 10648, Automatic Target Recognition XXVIII, 106480L (30 April 2018); doi: 10.1117/12.2305088
Show Author Affiliations
Ismail Jouny, Lafayette College (United States)


Published in SPIE Proceedings Vol. 10648:
Automatic Target Recognition XXVIII
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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