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Proceedings Paper

Asymptotic target recognition performance for FLIR and ladar systems
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Paper Abstract

Automatic target recognition (ATR) performance based on forward-looking infrared (FLIR) and laser radar (LADAR) image sensors is studied for the recognition of ground-based targets with unknown random pose. High signal-to-noise ratio results are obtained by using the Laplace approximation to simplify nuisance integrals which appear in Bayesian likelihood-ratio calculations. This analytical approach applied to simple blocks-world target models and statistical sensor models provides insight into how target and sensor parameters affect recognition performance. The Laplace method used in this paper can be applied to obtain expressions for the probability of error in binary recognition as well as more general situations such as target detection and M-ary recognition. These theoretical results are compared with computer-simulated calculations of the probability of error in binary recognition and sensor fusion scenarios.

Paper Details

Date Published: 22 October 2001
PDF: 14 pages
Proc. SPIE 4379, Automatic Target Recognition XI, (22 October 2001); doi: 10.1117/12.445359
Show Author Affiliations
Brent J. Yen, Massachusetts Institute of Technology (United States)
Jeffrey H. Shapiro, Massachusetts Institute of Technology (United States)

Published in SPIE Proceedings Vol. 4379:
Automatic Target Recognition XI
Firooz A. Sadjadi, Editor(s)

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