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Proceedings Paper

Target signature manifold methods applied to MSTAR dataset: preliminary results
Author(s): Michael Lee Bryant
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Paper Abstract

The primary contribution of this paper is to demonstrate the application of signature manifold methods on the MSTAR data. Three manifold estimation methods (FIR, FFT, and Kalman smoothing) are compared to a baseline algorithm, MSE. The preliminary results show the manifold methods perform just as well as the baseline algorithm and have the potential for increased performance. In addition, both GLRT and Bayes hypothesis test algorithms are demonstrated for all of the manifold estimation algorithms.

Paper Details

Date Published: 27 August 2001
PDF: 6 pages
Proc. SPIE 4382, Algorithms for Synthetic Aperture Radar Imagery VIII, (27 August 2001); doi: 10.1117/12.438232
Show Author Affiliations
Michael Lee Bryant, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 4382:
Algorithms for Synthetic Aperture Radar Imagery VIII
Edmund G. Zelnio, Editor(s)

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