Paper
4 August 2000 Characterization of disagreement in multiplatform and multisensor fusion analysis
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Abstract
An interesting problem arises in multi platform-multisensor information fusion system when sources disagree on the classification or identity of an unknown entity. If there is disagreement, the ideal situation ins a high level of confidence form a single source with complete disagreement in the remaining sources. This is not always the case and situations may arise where the winner is only successful by a small margin and there is collective disagreement amongst the losing sources. This paper describes a new terminology, disfusion, which is used for the characterization of disagreement between information sources and can enhance the final conclusion of a fusion system.
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Harley R. Myler "Characterization of disagreement in multiplatform and multisensor fusion analysis", Proc. SPIE 4052, Signal Processing, Sensor Fusion, and Target Recognition IX, (4 August 2000); https://doi.org/10.1117/12.395074
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Sensors

Data fusion

Binary data

Detection and tracking algorithms

Information fusion

Probability theory

Sensor fusion

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