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Proceedings Paper

Analysis of the impact of feature-enhanced SAR imaging on ATR performance
Author(s): Mujdat Cetin; William Clement Karl; David A. Castanon
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Paper Abstract

We present an evaluation of the impact of a recently proposed feature-enhanced synthetic aperture radar (SAR) imaging technique on automatic target recognition (ATR) performance. We run recognition experiments using conventional and feature-enhanced SAR images of military targets, in three different classifiers. The first classifier is template-based. The second classifier makes a decision through a likelihood test, based on Gaussian models for reflectivities. The third classifier is based on extracted locations of the dominant target scatterers. The experimental results demonstrate that feature-enhanced SAR imaging can improve the recognition performance, especially in scenarios involving reduced data quality or quantity.

Paper Details

Date Published: 1 August 2002
PDF: 12 pages
Proc. SPIE 4727, Algorithms for Synthetic Aperture Radar Imagery IX, (1 August 2002); doi: 10.1117/12.478673
Show Author Affiliations
Mujdat Cetin, Massachusetts Institute of Technology (United States)
William Clement Karl, Boston Univ. (United States)
David A. Castanon, Boston Univ. (United States)


Published in SPIE Proceedings Vol. 4727:
Algorithms for Synthetic Aperture Radar Imagery IX
Edmund G. Zelnio, Editor(s)

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