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Proceedings Paper

Statistical pose estimation of land targets in SAR
Author(s): Jose C. Principe; Dongxin Xu; Andrew W. Learn; Qun Zhao
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Paper Abstract

This paper explores statistical pose estimation in SAR ATR using a recently proposed training method based on information theory. The theory of training with information theoretic learning is briefly summarized. Different pose estimator topologies and training criteria are employed. Experimental results in the MSTAR I and II show that our proposed method is capable of producing 1-DOF and 2-DOF pose estimations and we show the dependence of the training parameters on performance.

Paper Details

Date Published: 24 August 2000
PDF: 12 pages
Proc. SPIE 4053, Algorithms for Synthetic Aperture Radar Imagery VII, (24 August 2000); doi: 10.1117/12.396342
Show Author Affiliations
Jose C. Principe, Univ. of Florida (United States)
Dongxin Xu, Univ. of Florida (United States)
Andrew W. Learn, Air Force Research Lab. (United States)
Qun Zhao, Univ. of Florida (United States)


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

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