Multisensor data fusion and belief functions for robust singularity detection in signals

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dc.contributor.author LE MOAL, G
dc.contributor.author MORARU, George
dc.contributor.author VERON, Philippe
dc.contributor.author DOUILLY, M
dc.contributor.author RABATE, P
dc.date.accessioned 2015-07-17T13:15:13Z
dc.date.available 2015-07-17T13:15:13Z
dc.date.issued 2011
dc.date.submitted 2015-06-26T05:35:14Z
dc.identifier.uri http://hdl.handle.net/10985/9809
dc.description.abstract This paper addresses the problem of robust

detection of signal singularity in hostile environments

using multisensor data fusion. Measurement

uncertainty is usually treated in a probabilistic way,

assuming lack of knowledge is totally due to random

effects. However, this approach fails when other effects,

such as sensor failure, are involved. In order to improve

the robustness of singularity detection, an evidence

theory based approach is proposed for both modeling

(data alignment) and merging (data fusion) information

coming from multiple redundant sensors. Whereas the

fusion step is done classically, the proposed method for

data alignment has been designed to improve singularity

detection performances in multisensor cases. Several

case studies have been designed to suit real life

situations. Results provided by both probabilistic and

evidential approaches are compared. Evidential methods

show better behavior facing sensors dysfunction and the

proposed method takes fully advantage of component

redundancy.
en
dc.language.iso en
dc.publisher Proceedings of the 14th International Conference on Information Fusion - FUSION
dc.rights Post-print
dc.title Multisensor data fusion and belief functions for robust singularity detection in signals en
dc.typdoc Communications avec actes
dc.localisation Centre de Aix en Provence
dc.subject.hal Informatique: Ingénierie assistée par ordinateur
ensam.audience Internationale
ensam.conference.title Proceedings of the 14th International Conference on Information Fusion - FUSION
ensam.conference.date 2011
ensam.country Etats-Unis
ensam.title.proceeding Proceedings of the 14th International Conference on Information Fusion - FUSION
ensam.page NA
ensam.city Chicago

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