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Proceedings Paper

Asymmetric fusion strategies for target detection in multisensor environments
Author(s): Belur V. Dasarathy
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Paper Abstract

Most of the studies reported in the open literature on sensor fusion for target detection in multisensor environments have proposed fusion strategies that are essentially independent of the identity of the object as observed by the individual sensors. This independence makes the fusion strategies symmetric relative to the identity of the objects in terms of their target or non-target (decoys, clutter, etc.) status. In this study, new ground is broken in terms of fusion strategies which, by being dependent on the identity of the objects as perceived by the individual sensors, can be asymmetric relative to the identity of the object under observation. The study analyzes the scope for and benefits of deployment of these asymmetric fusion strategies as compared to the conventional Boolean logic based symmetric fusion strategies studied previously. Under these conventional fusion strategies, while use of the Boolean AND logic for fusion tends to minimize the false alarm rate, use of OR logic maximizes the detection probability. Under the asymmetric fusion strategies conceived here, it is possible to drive the decision process towards maximizing the probability of detection of lethal objects (targets) while simultaneously minimizing the false alarm rates. The performance of these asymmetric fusion strategies, when embedded in a recursive structure that permits multiple observation and temporal fusion along the time line, are analyzed relative to that of the conventional symmetric fusion strategies to parametrically determine their domains of beneficial deployment.

Paper Details

Date Published: 16 June 1997
PDF: 12 pages
Proc. SPIE 3067, Sensor Fusion: Architectures, Algorithms, and Applications, (16 June 1997); doi: 10.1117/12.276129
Show Author Affiliations
Belur V. Dasarathy, Dynetics, Inc. (United States)


Published in SPIE Proceedings Vol. 3067:
Sensor Fusion: Architectures, Algorithms, and Applications
Belur V. Dasarathy, Editor(s)

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