22 October 2001 Asymptotic target recognition performance for FLIR and ladar systems
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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.
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Brent J. Yen, Jeffrey H. Shapiro, "Asymptotic target recognition performance for FLIR and ladar systems", Proc. SPIE 4379, Automatic Target Recognition XI, (22 October 2001); doi: 10.1117/12.445359; https://doi.org/10.1117/12.445359
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