Cargando…

A Reliability-Based Method to Sensor Data Fusion

Multi-sensor data fusion technology based on Dempster–Shafer evidence theory is widely applied in many fields. However, how to determine basic belief assignment (BBA) is still an open issue. The existing BBA methods pay more attention to the uncertainty of information, but do not simultaneously cons...

Descripción completa

Detalles Bibliográficos
Autores principales: Jiang, Wen, Zhuang, Miaoyan, Xie, Chunhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5539540/
https://www.ncbi.nlm.nih.gov/pubmed/28678179
http://dx.doi.org/10.3390/s17071575
_version_ 1783254497948073984
author Jiang, Wen
Zhuang, Miaoyan
Xie, Chunhe
author_facet Jiang, Wen
Zhuang, Miaoyan
Xie, Chunhe
author_sort Jiang, Wen
collection PubMed
description Multi-sensor data fusion technology based on Dempster–Shafer evidence theory is widely applied in many fields. However, how to determine basic belief assignment (BBA) is still an open issue. The existing BBA methods pay more attention to the uncertainty of information, but do not simultaneously consider the reliability of information sources. Real-world information is not only uncertain, but also partially reliable. Thus, uncertainty and partial reliability are strongly associated with each other. To take into account this fact, a new method to represent BBAs along with their associated reliabilities is proposed in this paper, which is named reliability-based BBA. Several examples are carried out to show the validity of the proposed method.
format Online
Article
Text
id pubmed-5539540
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-55395402017-08-11 A Reliability-Based Method to Sensor Data Fusion Jiang, Wen Zhuang, Miaoyan Xie, Chunhe Sensors (Basel) Article Multi-sensor data fusion technology based on Dempster–Shafer evidence theory is widely applied in many fields. However, how to determine basic belief assignment (BBA) is still an open issue. The existing BBA methods pay more attention to the uncertainty of information, but do not simultaneously consider the reliability of information sources. Real-world information is not only uncertain, but also partially reliable. Thus, uncertainty and partial reliability are strongly associated with each other. To take into account this fact, a new method to represent BBAs along with their associated reliabilities is proposed in this paper, which is named reliability-based BBA. Several examples are carried out to show the validity of the proposed method. MDPI 2017-07-05 /pmc/articles/PMC5539540/ /pubmed/28678179 http://dx.doi.org/10.3390/s17071575 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jiang, Wen
Zhuang, Miaoyan
Xie, Chunhe
A Reliability-Based Method to Sensor Data Fusion
title A Reliability-Based Method to Sensor Data Fusion
title_full A Reliability-Based Method to Sensor Data Fusion
title_fullStr A Reliability-Based Method to Sensor Data Fusion
title_full_unstemmed A Reliability-Based Method to Sensor Data Fusion
title_short A Reliability-Based Method to Sensor Data Fusion
title_sort reliability-based method to sensor data fusion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5539540/
https://www.ncbi.nlm.nih.gov/pubmed/28678179
http://dx.doi.org/10.3390/s17071575
work_keys_str_mv AT jiangwen areliabilitybasedmethodtosensordatafusion
AT zhuangmiaoyan areliabilitybasedmethodtosensordatafusion
AT xiechunhe areliabilitybasedmethodtosensordatafusion
AT jiangwen reliabilitybasedmethodtosensordatafusion
AT zhuangmiaoyan reliabilitybasedmethodtosensordatafusion
AT xiechunhe reliabilitybasedmethodtosensordatafusion