NDLI: An evidential model of multisensor decision fusion for force aggregation and classification

Content Provider	IEEE Xplore Digital Library
Author	Yu, B. Giampapa, J. Owens, S. Sycara, K.
Copyright Year	2005
Description	Author affiliation: Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA (Yu, B.; Giampapa, J.; Owens, S.; Sycara, K.)
Abstract	This paper describes airborne sensor networks for target detection and identification in military applications. One challenge is how to process and aggregate data from many sensor sources to generate an accurate and timely picture of the battlefield. The majority of research in data fusion has focused primarily on level 1 fusion, e.g., using multisensor data to determine the position, velocity, attributes, and identity of individual targets. In this paper we present a novel approach to military force aggregation and classification using the mathematical theory of evidence and doctrinal templates. Our approach helps commanders understand operational pictures of the battlefield, e.g., enemy force levels and deployment, and make better decisions than adversaries in the battlefield. A simple application of our approach is illustrated in the simulated testbed OTBSAF and RETSINA system.
File Size	2784499
File Format	PDF
ISBN	0780392868
DOI	10.1109/ICIF.2005.1591964
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-07-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sensor fusion Sensor phenomena and characterization Force sensors Object detection Synthetic aperture radar Aggregates Fusion power generation Unmanned aerial vehicles Radar tracking Target tracking
Content Type	Text
Resource Type	Article

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