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Proceedings Paper

A Model-Based System For Force Structure Analysis
Author(s): Tod S. Levitt; Robert L. Kirby; Hans E. Muller
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Paper Abstract

Given a set of image-derived vehicle detections and/or recognized military vehicles, SIGINT cues and a priori analysis of terrain, the force structure analysis (FSA) problem is to utilize knowledge of tactical doctrine and spatial deployment information to infer the existence of military forces such as batteries, companies, battalions, regiments, divisions, etc. A model-based system for FSA has been developed. It performs symbolic reasoning about force structures represented as geometric models. The FSA system is a stand-alone module which has also been developed as part of a larger system, the Advanced Digital Radar Image Exploitation System (ADRIES) for automated SAR image exploitation. The models recursively encode the component military units of a force structure, their expected spatial deployment, search priorities for model components, prior match probabilities, and type hierarchies for uncertain recognition. Partial and uncertain matching of models against data is the basic tool for building up hypotheses of the existence of force structures. Hypothesis management includes the functions of matching models against data, predicting the existence and location of unobserved force components, localization of search areas and resolution of conflicts between competing hypotheses. A subjective Bayesian inference calculus is used to accrue certainty of force structure hypotheses and resolve conflicts. Reasoning from uncertain vehicle level data, the system has successfully inferred the correct locations and components of force structures up to the battalion level. Key words: Force structure analysis, SAR, model-based reasoning, hypothesis management, search, matching, conflict resolution, Bayesian inference, uncertainty.

Paper Details

Date Published: 5 April 1985
PDF: 7 pages
Proc. SPIE 0548, Applications of Artificial Intelligence II, (5 April 1985); doi: 10.1117/12.948421
Show Author Affiliations
Tod S. Levitt, Advanced Information & Decision Systems (United States)
Robert L. Kirby, Advanced Information & Decision Systems (United States)
Hans E. Muller, Advanced Information & Decision Systems (United States)


Published in SPIE Proceedings Vol. 0548:
Applications of Artificial Intelligence II
John F. Gilmore, Editor(s)

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