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Proceedings Paper

Discrimination requirements model
Author(s): Robert F. Cuffel; Lisa A. Strugala; C. Pham; James A. Kiessling; P. W. Kelsey
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Paper Abstract

The development of a discrimination software testbed, the Discrimination Requirements Model (DRM), intended to support IR sensor requirements definition is described. The DRM employs the standard pattern recognition paradigm, e.g., the reduction of a Monte Carlo database of noised input object signatures into the corresponding target and non-target feature vector sets. Classification of the feature vectors is performed using a varied threshold. The false alarm (PFA) and leakage (PL) error probabilities are estimated via a leave-one- out procedure. The resultant PFA versus PL curve of user selectable thresholds is used to evaluate discrimination performance for the test signature database. Degradation of input signature data strings is accomplished through a set of user selectable sensor performance capabilities. The selectable feature subset includes statistical, curvilinear fit, dynamical, and centralized moment-based parameters for single and multiple band optical systems as well as various normalization options. The DRM accommodates dropouts and other realistic SNR effects. A centralized approach is employed for multiple sensor data fusion for discrimination based on prior associated object tracks. Applications to sensor design and system performance projections are discussed.

Paper Details

Date Published: 5 July 1995
PDF: 11 pages
Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); doi: 10.1117/12.213033
Show Author Affiliations
Robert F. Cuffel, Lockheed Missiles & Space Co., Inc. (United States)
Lisa A. Strugala, Lockheed Missiles & Space Co., Inc. (United States)
C. Pham, Lockheed Missiles & Space Co., Inc. (United States)
James A. Kiessling, Lockheed Missiles & Space Co., Inc. (United States)
P. W. Kelsey, Coleman Research Corp. (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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