Research on improved evidence theory based on multi-sensor information fusion

Abstract In view of the lack of effective information fusion model for heterogeneous multi-sensor, an improved Dempster/Shafer (DS) evidence theory algorithm is designed to fuse heterogeneous multi-sensor information. The algorithm first introduces the compatibility coefficient to characterize the c...

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Autores principales: Zhen Lin, Jinye Xie
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/cbfb133f7b924cfca910612102ac58f6
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spelling oai:doaj.org-article:cbfb133f7b924cfca910612102ac58f62021-12-02T13:41:22ZResearch on improved evidence theory based on multi-sensor information fusion10.1038/s41598-021-88814-32045-2322https://doaj.org/article/cbfb133f7b924cfca910612102ac58f62021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-88814-3https://doaj.org/toc/2045-2322Abstract In view of the lack of effective information fusion model for heterogeneous multi-sensor, an improved Dempster/Shafer (DS) evidence theory algorithm is designed to fuse heterogeneous multi-sensor information. The algorithm first introduces the compatibility coefficient to characterize the compatibility between the evidence, obtains the weight matrix of each proposition, and then redistributes the basic probability distribution of each focal element to obtain a new evidence source. Then the concept of credibility is introduced, and the average support of evidence credibility and evidence focal element is used to improve the synthesis rule, so as to obtain the fusion result. Compared with other algorithms, the proposed algorithm can solve the problems existing in DS evidence theory when dealing with highly conflicting evidence to a certain extent, and the fusion results are more reasonable and the convergence speed is faster.Zhen LinJinye XieNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-6 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Zhen Lin
Jinye Xie
Research on improved evidence theory based on multi-sensor information fusion
description Abstract In view of the lack of effective information fusion model for heterogeneous multi-sensor, an improved Dempster/Shafer (DS) evidence theory algorithm is designed to fuse heterogeneous multi-sensor information. The algorithm first introduces the compatibility coefficient to characterize the compatibility between the evidence, obtains the weight matrix of each proposition, and then redistributes the basic probability distribution of each focal element to obtain a new evidence source. Then the concept of credibility is introduced, and the average support of evidence credibility and evidence focal element is used to improve the synthesis rule, so as to obtain the fusion result. Compared with other algorithms, the proposed algorithm can solve the problems existing in DS evidence theory when dealing with highly conflicting evidence to a certain extent, and the fusion results are more reasonable and the convergence speed is faster.
format article
author Zhen Lin
Jinye Xie
author_facet Zhen Lin
Jinye Xie
author_sort Zhen Lin
title Research on improved evidence theory based on multi-sensor information fusion
title_short Research on improved evidence theory based on multi-sensor information fusion
title_full Research on improved evidence theory based on multi-sensor information fusion
title_fullStr Research on improved evidence theory based on multi-sensor information fusion
title_full_unstemmed Research on improved evidence theory based on multi-sensor information fusion
title_sort research on improved evidence theory based on multi-sensor information fusion
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/cbfb133f7b924cfca910612102ac58f6
work_keys_str_mv AT zhenlin researchonimprovedevidencetheorybasedonmultisensorinformationfusion
AT jinyexie researchonimprovedevidencetheorybasedonmultisensorinformationfusion
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