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Proceedings Paper

Matching requirements to means using meaning
Author(s): Steve Hookway; Joe Gorman; Brad Rosenberg
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Paper Abstract

The ability to collect an ever-increasing amount of information is outpacing analysts’ ability to interpret and communicate that information in a timely manner. The Army Research Laboratory’s (ARL’s) Signal and Image Processing (SIP) Division is presently engaged in research to develop a system-of-systems methodology designed around a Mission & Means Framework (MMF), a robust, rapid-reaction, autonomous information-generating tool that can provide the mission-relevant information/intelligence that Commanders need to make winning decisions on the battlefield. The MMF provides a structure that enables the optimal allocation of available information sources to capture and exploit Mission-Informed Needed Information based on Discoverable, Available Sensing Sources (MINI-DASS). In this paper, we describe an MMF operator that matches information needs to information means using ontologies that describe both the information requirements and the information sources. We then describe two different multi-objective optimization techniques to effectively explore the large, complex search space o possible matches to discover suitable solutions that match available information-source means to satisfy mission needs.

Paper Details

Date Published: 3 July 2018
PDF: 5 pages
Proc. SPIE 10635, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX, 1063513 (3 July 2018); doi: 10.1117/12.2310044
Show Author Affiliations
Steve Hookway, Charles River Analytics, Inc. (United States)
Joe Gorman, Charles River Analytics, Inc. (United States)
Brad Rosenberg, Charles River Analytics, Inc. (United States)

Published in SPIE Proceedings Vol. 10635:
Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX
Michael A. Kolodny; Dietrich M. Wiegmann; Tien Pham, Editor(s)

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