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Optical Engineering

Toward target recognition from synthetic aperture radar imagery using electromagnetics-based signatures
Author(s): Chen-Pang Yeang; Choongyeun Cho; Jeffrey H. Shapiro
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Paper Abstract

We develop a theory of target detection and classification from physics-based synthetic aperture radar (SAR) signatures. The target-return and clutter-return models are developed from electromagnetic theory. Both stripmap-mode and spotlight-mode SARs are treated. Adaptive-resolution processors, conventional SAR processors, and optimum likelihood-ratio target detectors are presented for multicomponent target detection, and their receiver operating characteristics are compared. Similarly, conventional and optimum likelihood-ratio processors are used for multicomponent target classification. We develop upper and lower bounds and present Monte Carlo simulations for the probabilities of correct classification.

Paper Details

Date Published: 1 July 2003
PDF: 21 pages
Opt. Eng. 42(7) doi: 10.1117/1.1579031
Published in: Optical Engineering Volume 42, Issue 7
Show Author Affiliations
Chen-Pang Yeang, Massachusetts Institute of Technology (United States)
Choongyeun Cho, Massachusetts Institute of Technology (United States)
Jeffrey H. Shapiro, Massachusetts Institute of Technology (United States)

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