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Proceedings Paper

Syntactic pattern recognition for HRR signatures
Author(s): Raj K. Bhatnagar; Robert L. Williams; Vijay Tennety
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Paper Abstract

A classifier based on a syntactic approach is developed for High range resolution (HRR) radar target recognition. An attribute grammar is used to represent the structure of an HRR signature and an error-correcting parsing mechanism is implemented to extract peaks in the HRR profile and suppress the extraneous spikes. In the training phase, an error correcting grammatical inference technique is employed for structural inference of HRR signatures using a positive sample set. Recognition is done using a minimum distance classifier where Levenshtein error measure is used as the distance metric. The error-correcting parsing procedure for peak extraction is used to perform both inference and recognition. Experiments performed using public release MSTAR database indicate that this approach has sufficient discrimination power to perform target detection in HRR signatures.

Paper Details

Date Published: 24 August 2000
PDF: 15 pages
Proc. SPIE 4053, Algorithms for Synthetic Aperture Radar Imagery VII, (24 August 2000); doi: 10.1117/12.396356
Show Author Affiliations
Raj K. Bhatnagar, Univ. of Cincinnati (United States)
Robert L. Williams, Air Force Research Lab. (United States)
Vijay Tennety, Univ. of Cincinnati (United States)

Published in SPIE Proceedings Vol. 4053:
Algorithms for Synthetic Aperture Radar Imagery VII
Edmund G. Zelnio, Editor(s)

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