Title
Characterization Of Disagreement In Multiplatform And Multisensor Fusion Analysis
Abstract
An interesting problem arises in multiplatform-multisensor information fusion systems when sources disagree on the classification or identity of an unknown entity. If there is disagreement, the ideal situation is a high level of confidence from 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.
Publication Date
1-1-2000
Publication Title
Proceedings of SPIE - The International Society for Optical Engineering
Volume
4052
Number of Pages
240-248
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0033682670 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0033682670
STARS Citation
Myler, Harley R., "Characterization Of Disagreement In Multiplatform And Multisensor Fusion Analysis" (2000). Scopus Export 2000s. 1280.
https://stars.library.ucf.edu/scopus2000/1280