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Proceedings Paper

Efficient end-to-end feature-based system for SAR ATR
Author(s): Quoc Henry Pham; Timothy Myers Brosnan; Mark J. T. Smith; Russell M. Mersereau
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Paper Abstract

In this paper we discuss an end-to-end system for SAR automatic target recognition (ATR), giving particular emphasis to the discrimination and classification stages. The ATR system employs a three sequential stage approach to reduce complexity: a detection stage, a discrimination stage, and a classification stage. Details of the detection stage were presented previously. The target discrimination and classification methods, which we present here, involve extracting rotationally and translationally invariant features from the Radon transform of target chips. The methods are applied in both isolated and complete end-to-end systems on the TESAR baseline SAR database distributed by the U.S. Army Research Laboratory and in isolation using the public MSTAR database. The performance results on these SAR datasets are presented.

Paper Details

Date Published: 15 September 1998
PDF: 11 pages
Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, (15 September 1998); doi: 10.1117/12.321855
Show Author Affiliations
Quoc Henry Pham, Georgia Institute of Technology (United States)
Timothy Myers Brosnan, Georgia Institute of Technology (United States)
Mark J. T. Smith, Georgia Institute of Technology (United States)
Russell M. Mersereau, Georgia Institute of Technology (United States)

Published in SPIE Proceedings Vol. 3370:
Algorithms for Synthetic Aperture Radar Imagery V
Edmund G. Zelnio, Editor(s)

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