Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency
The paradigm of multisensor data fusion has been evolved from a centralized architecture to a decentralized or distributed architecture along with the advancement in sensor and communication technologies. These days, distributed state estimation and data fusion has been widely explored in diverse fi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-10-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/17/11/2472 |
| _version_ | 1817994375062355968 |
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| author | Muhammad Abu Bakr Sukhan Lee |
| author_facet | Muhammad Abu Bakr Sukhan Lee |
| author_sort | Muhammad Abu Bakr |
| collection | DOAJ |
| description | The paradigm of multisensor data fusion has been evolved from a centralized architecture to a decentralized or distributed architecture along with the advancement in sensor and communication technologies. These days, distributed state estimation and data fusion has been widely explored in diverse fields of engineering and control due to its superior performance over the centralized one in terms of flexibility, robustness to failure and cost effectiveness in infrastructure and communication. However, distributed multisensor data fusion is not without technical challenges to overcome: namely, dealing with cross-correlation and inconsistency among state estimates and sensor data. In this paper, we review the key theories and methodologies of distributed multisensor data fusion available to date with a specific focus on handling unknown correlation and data inconsistency. We aim at providing readers with a unifying view out of individual theories and methodologies by presenting a formal analysis of their implications. Finally, several directions of future research are highlighted. |
| first_indexed | 2024-04-14T01:51:07Z |
| format | Article |
| id | doaj.art-e146a771b23c432a96a66cd53f2cf2e7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T01:51:07Z |
| publishDate | 2017-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e146a771b23c432a96a66cd53f2cf2e72022-12-22T02:19:21ZengMDPI AGSensors1424-82202017-10-011711247210.3390/s17112472s17112472Distributed Multisensor Data Fusion under Unknown Correlation and Data InconsistencyMuhammad Abu Bakr0Sukhan Lee1Intelligent Systems Research Institute, Sungkyunkwan University, Suwon, Gyeonggi-do 440-746, KoreaIntelligent Systems Research Institute, Sungkyunkwan University, Suwon, Gyeonggi-do 440-746, KoreaThe paradigm of multisensor data fusion has been evolved from a centralized architecture to a decentralized or distributed architecture along with the advancement in sensor and communication technologies. These days, distributed state estimation and data fusion has been widely explored in diverse fields of engineering and control due to its superior performance over the centralized one in terms of flexibility, robustness to failure and cost effectiveness in infrastructure and communication. However, distributed multisensor data fusion is not without technical challenges to overcome: namely, dealing with cross-correlation and inconsistency among state estimates and sensor data. In this paper, we review the key theories and methodologies of distributed multisensor data fusion available to date with a specific focus on handling unknown correlation and data inconsistency. We aim at providing readers with a unifying view out of individual theories and methodologies by presenting a formal analysis of their implications. Finally, several directions of future research are highlighted.https://www.mdpi.com/1424-8220/17/11/2472multisensor data fusiondecentralized estimationdistributed fusioninconsistent estimatesspurious dataunknown correlation |
| spellingShingle | Muhammad Abu Bakr Sukhan Lee Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency Sensors multisensor data fusion decentralized estimation distributed fusion inconsistent estimates spurious data unknown correlation |
| title | Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency |
| title_full | Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency |
| title_fullStr | Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency |
| title_full_unstemmed | Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency |
| title_short | Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency |
| title_sort | distributed multisensor data fusion under unknown correlation and data inconsistency |
| topic | multisensor data fusion decentralized estimation distributed fusion inconsistent estimates spurious data unknown correlation |
| url | https://www.mdpi.com/1424-8220/17/11/2472 |
| work_keys_str_mv | AT muhammadabubakr distributedmultisensordatafusionunderunknowncorrelationanddatainconsistency AT sukhanlee distributedmultisensordatafusionunderunknowncorrelationanddatainconsistency |