Paper
13 August 1999 New end-to-end SAR ATR system
Quoc Henry Pham, Albert Ezekiel, Michael T. Campbell, Mark J. T. Smith
Author Affiliations +
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.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Quoc Henry Pham, Albert Ezekiel, Michael T. Campbell, and Mark J. T. Smith "New end-to-end SAR ATR system", Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999); https://doi.org/10.1117/12.357647
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Cited by 20 scholarly publications.
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KEYWORDS
Automatic target recognition

Synthetic aperture radar

Detection and tracking algorithms

Image segmentation

Radon transform

Binary data

Target detection

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