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The fusion of redundant SEVA measurements

Abstract:
The self-validating (SEVA) sensor carries out an internal quality assessment, and generates, for each measurement, standard metrics for its quality, including online uncertainty. This paper discusses consistency checking and data fusion between several SEVA sensors observing the same measurand. Consistency checking is shown to be equivalent to the maximum clique problem, which is NP-hard, but a linear approximation is described. A technique called uncertainty extension is proposed which causes a smooth reduction in the influence of outliers as they become increasingly inconsistent with the majority.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/TCST.2004.840448

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Institution:
University of Oxford
Division:
MSD
Department:
Experimental Psychology
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


Publisher:
Institute of Electrical and Electronics Engineers
Journal:
IEEE Transactions on Control Systems Technology More from this journal
Volume:
13
Issue:
2
Pages:
173-184
Publication date:
2004-02-28
Acceptance date:
2004-05-28
DOI:
ISSN:
1063-6536


Keywords:
Pubs id:
pubs:430726
UUID:
uuid:1afa9f92-116c-4a80-9d86-0155d998751a
Local pid:
pubs:430726
Deposit date:
2016-10-01
ARK identifier:

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