Paper
31 July 2002 ATR evaluation through the synthesis of multiple performance measures
Christopher Brian Bassham, William K. Klimack, Kenneth W. Bauer Jr.
Author Affiliations +
Abstract
This research demonstrates the application of decision analysis (DA) techniques to decisions made within Automatic Target Recognition (ATR) technology development. This work is accomplished to improve the means by which ATR technologies are evaluated. The first step in this research was to create a flexible decision analysis framework that could be applied to several decisions across different ATR programs evaluated by the Comprehensive ATR Scientific Evaluation (COMPASE) Center of the Air Force Research Laboratory (AFRL). For the purposes of this research, a single COMPASE Center representative provided the value, utility, and preference functions for the DA framework. The DA framework employs performance measures collected during ATR classification system (CS) testing to calculate value and utility scores. The authors gathered data from the Moving and Stationary Target Acquisition and Recognition (MSTAR) program to demonstrate how the decision framework could be used to evaluate three different ATR CSs. A decision-maker may use the resultant scores to gain insight into any of the decisions that occur throughout the lifecycle of ATR technologies. Additionally, a means of evaluating ATR CS self-assessment ability is presented. This represents a new criterion that emerged from this study, and no present evaluation metric is known.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christopher Brian Bassham, William K. Klimack, and Kenneth W. Bauer Jr. "ATR evaluation through the synthesis of multiple performance measures", Proc. SPIE 4729, Signal Processing, Sensor Fusion, and Target Recognition XI, (31 July 2002); https://doi.org/10.1117/12.477597
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Automatic target recognition

Target detection

Intelligence systems

Analytical research

Target recognition

Sensors

Environmental sensing

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