Automatic target recognition via classical detection theory

Douglas R. Morgan

doi:10.1117/12.213043

5 July 1995 Automatic target recognition via classical detection theory

Douglas R. Morgan

Proceedings Volume 2484, Signal Processing, Sensor Fusion, and Target Recognition IV; (1995) https://doi.org/10.1117/12.213043
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

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.

Citation Download Citation

Douglas R. Morgan "Automatic target recognition via classical detection theory", Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); https://doi.org/10.1117/12.213043

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