Paper
15 May 2007 Issues and challenges in resource management and its interaction with levels 2/3 fusion with applications to real-world problems: an annotated perspective
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Abstract
Resource management (or process refinement) is critical for information fusion operations in that users, sensors, and platforms need to be informed, based on mission needs, on how to collect, process, and exploit data. To meet these growing concerns, a panel session was conducted at the International Society of Information Fusion Conference in 2006 to discuss the various issues surrounding the interaction of Resource Management with Level 2/3 Situation and Threat Assessment. This paper briefly consolidates the discussion of the invited panel panelists. The common themes include: (1) Addressing the user in system management, sensor control, and knowledge based information collection (2) Determining a standard set of fusion metrics for optimization and evaluation based on the application (3) Allowing dynamic and adaptive updating to deliver timely information needs and information rates (4) Optimizing the joint objective functions at all information fusion levels based on decision-theoretic analysis (5) Providing constraints from distributed resource mission planning and scheduling; and (6) Defining L2/3 situation entity definitions for knowledge discovery, modeling, and information projection
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Erik Blasch, Ivan Kadar, Kenneth Hintz, Joachim Biermann, Chee-Yee Chong, John Salerno, and Subrata Das "Issues and challenges in resource management and its interaction with levels 2/3 fusion with applications to real-world problems: an annotated perspective", Proc. SPIE 6567, Signal Processing, Sensor Fusion, and Target Recognition XVI, 656712 (15 May 2007); https://doi.org/10.1117/12.719613
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Cited by 7 scholarly publications.
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KEYWORDS
Sensors

Information fusion

Weapons

Data fusion

Data processing

Target detection

Data acquisition

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