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Proceedings Paper

Information-theoretic bounds on target recognition performance from laser radar data
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Paper Abstract

Laser radar systems historically offer rich data sets for automatic target recognition (ATR). ATR algorithm development for laser radar has focused on achieving real-time performance with current hardware. Our work addresses the issue of understanding how much information can be obtain from the data, independent of any particular algorithm. We present Cramer-Rao lower bounds on target pose estimation based on a statistical model for laser radar data. Specifically, we employ a model based on the underlying physics of a coherent-detection laser radar. Most ATR algorithms for laser radar data are designed to be invariant with respect to position and orientation. Our information-theoretic perspective illustrates that even algorithms that do not explicitly involve the estimation of such nuisance parameters are still affected by them.

Paper Details

Date Published: 18 May 2006
PDF: 10 pages
Proc. SPIE 6234, Automatic Target Recognition XVI, 623419 (18 May 2006); doi: 10.1117/12.674811
Show Author Affiliations
Jason H. Dixon, Georgia Institute of Technology (United States)
Aaron D. Lanterman, Georgia Institute of Technology (United States)

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

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