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Proceedings Paper

Automatic target recognition via classical detection theory
Author(s): Douglas R. Morgan
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Paper Abstract

Classical Bayesian detection and decision theory applies to arbitrary problems with underlying probabilistic models. When the models describe uncertainties in target type, pose, geometry, surround, scattering phenomena, sensor behavior, and feature extraction, then classical theory directly yields detailed model-based automatic target recognition (ATR) techniques. This paper reviews options and considerations arising under a general Bayesian framework for model- based ATR, including approaches to the major problems of acquiring probabilistic models and of carrying out the indicated Bayesian computations.

Paper Details

Date Published: 5 July 1995
PDF: 7 pages
Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); doi: 10.1117/12.213043
Show Author Affiliations
Douglas R. Morgan, Booz, Allen and Hamilton (United States)

Published in SPIE Proceedings Vol. 2484:
Signal Processing, Sensor Fusion, and Target Recognition IV
Ivan Kadar; Vibeke Libby, Editor(s)

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