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Proceedings Paper

New end-to-end SAR ATR system
Author(s): Quoc Henry Pham; Albert Ezekiel; Michael T. Campbell; Mark J. T. Smith
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Paper Abstract

In this paper, we introduce an efficient end-to-end system for SAR automatic target recognition, giving particular emphasis to the discrimination and classification stages. The target discrimination method, which we present here, is based on the features extracted from the Radon transform. It is used to estimate length and width of the target for discriminating the object as target or clutter. Like the army research laboratory (ARL) and MIT Lincoln Laboratory (MIT/LL) approaches, our classification stage performs gray scale correlation on full resolution sub-image chips. The pattern matching references are constructed by averaging five consecutive spotlight mode images of targets collected at 1-degree azimuth increments. Morphology operations and feature clustering are used to produce accurate image segmentation. The target aspect is estimated to reduce the pose hypothesis search space. Our efficient end-to-end system has been tested using the public target MSTAR database. The system produces high discrimination and classification probabilities with relatively low false alarm rate.

Paper Details

Date Published: 13 August 1999
PDF: 10 pages
Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999); doi: 10.1117/12.357647
Show Author Affiliations
Quoc Henry Pham, Raytheon Systems Co. (United States)
Albert Ezekiel, Raytheon Systems Co. (United States)
Michael T. Campbell, Raytheon Systems Co. (United States)
Mark J. T. Smith, Georgia Institute of Technology (United States)

Published in SPIE Proceedings Vol. 3721:
Algorithms for Synthetic Aperture Radar Imagery VI
Edmund G. Zelnio, Editor(s)

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