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Proceedings Paper

Design for HMM-based SAR ATR
Author(s): Dane P. Kottke; Paul D. Fiore; Kathy L. Brown; Jong-Kae Fwu
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Paper Abstract

This paper describes progress on the Automatic Target Recognition (ATR) system for Synthetic Aperture Radar (SAR) imagery. The system is based upon a feature extraction, data ordering, and statistical modeling paradigm. Feature extraction is performed by applying image segmentation to convert the SAR imagery into one of four pixel classes. A description of a real-time image segmentation design is given. The segmented imagery is re-ordered from a 2D spatial representation to a sequential representation through the use of multiple Radon Transforms. Finally, the re-ordered data is classified by target type by applying Hidden Markov Model decoding techniques. Performance results on the MSTAR public targets database is provided.

Paper Details

Date Published: 15 September 1998
PDF: 11 pages
Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, (15 September 1998); doi: 10.1117/12.321857
Show Author Affiliations
Dane P. Kottke, Sanders, A Lockheed Martin Co. (United States)
Paul D. Fiore, Sanders, A Lockheed Martin Co. (United States)
Kathy L. Brown, Sanders, A Lockheed Martin Co. (United States)
Jong-Kae Fwu, Lucent Technologies (United States)


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

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