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Proceedings Paper

Adaptive determination of eigenvalues and eigenvectors from perturbed autocorrelation matrices for automatic target recognition
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Paper Abstract

The Modified Eigenvalue problem arises in many applications such as Array Processing, Automatic Target Recognition (ATR), etc. These applications usually involve the Eigenvalue Decomposition (EVD) of matrices that are time varying. It is desirable to have methods that eliminate the need to perform an EVD every time the matrix changes but instead update the EVD adaptively, starting from the initial EVD. In this paper, we propose a novel Optimal Adaptive Algorithm for the Modified EVD problem (OAMEVD). Sample results are presented for an ATR application, which uses Rayleigh Quotient Quadratic Correlation filters (RQQCF). Using a Infrared (IR) dataset, the effectiveness of this new technique as well as its advantages are illustrated.

Paper Details

Date Published: 18 May 2006
PDF: 12 pages
Proc. SPIE 6234, Automatic Target Recognition XVI, 62340F (18 May 2006); doi: 10.1117/12.665750
Show Author Affiliations
P. Ragothaman, Univ. of Central Florida (United States)
W. B. Mikhael, Univ. of Central Florida (United States)
R. Muise, Lockheed Martin (United States)
A. Mahalanobis, Lockheed Martin (United States)
T. Yang, Embry-Riddle Aeronautical Univ. (United States)

Published in SPIE Proceedings Vol. 6234:
Automatic Target Recognition XVI
Firooz A. Sadjadi, Editor(s)

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