Distributed estimation over a low-cost sensor network: A Review of state-of-the-art

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dc.contributor.authorHe, Shaomingko
dc.contributor.authorShin, Hyo-Sangko
dc.contributor.authorXu, Shuoyuanko
dc.contributor.authorTsourdos, Antoniosko
dc.date.accessioned2024-03-18T10:01:13Z-
dc.date.available2024-03-18T10:01:13Z-
dc.date.created2024-03-18-
dc.date.issued2020-02-
dc.identifier.citationINFORMATION FUSION, v.54, pp.21 - 43-
dc.identifier.issn1566-2535-
dc.identifier.urihttp://hdl.handle.net/10203/318577-
dc.description.abstractProliferation of low-cost, lightweight, and power efficient sensors and advances in networked systems enable the employment of multiple sensors. Distributed estimation provides a scalable and fault-robust fusion framework with a peer-to-peer communication architecture. For this reason, there seems to be a real need for a critical review of existing and, more importantly, recent advances in the domain of distributed estimation over a low-cost sensor network. This paper presents a comprehensive review of the state-of-the-art solutions in this research area, exploring their characteristics, advantages, and challenging issues. Additionally, several open problems and future avenues of research are highlighted.-
dc.languageEnglish-
dc.publisherELSEVIER-
dc.titleDistributed estimation over a low-cost sensor network: A Review of state-of-the-art-
dc.typeArticle-
dc.identifier.wosid000493802100003-
dc.identifier.scopusid2-s2.0-85068989578-
dc.type.rimsART-
dc.citation.volume54-
dc.citation.beginningpage21-
dc.citation.endingpage43-
dc.citation.publicationnameINFORMATION FUSION-
dc.identifier.doi10.1016/j.inffus.2019.06.026-
dc.contributor.localauthorShin, Hyo-Sang-
dc.contributor.nonIdAuthorHe, Shaoming-
dc.contributor.nonIdAuthorXu, Shuoyuan-
dc.contributor.nonIdAuthorTsourdos, Antonios-
dc.description.isOpenAccessN-
dc.type.journalArticleReview-
dc.subject.keywordAuthorDistributed estimation-
dc.subject.keywordAuthorLow-cost sensor network-
dc.subject.keywordAuthorFusion methodology-
dc.subject.keywordAuthorChallenging issues-
dc.subject.keywordPlusKALMAN CONSENSUS FILTER-
dc.subject.keywordPlusEVENT-TRIGGERED COMMUNICATION-
dc.subject.keywordPlusH-INFINITY CONSENSUS-
dc.subject.keywordPlusTARGET TRACKING-
dc.subject.keywordPlusCOVARIANCE INTERSECTION-
dc.subject.keywordPlusFUSION ESTIMATION-
dc.subject.keywordPlusBLIND CALIBRATION-
dc.subject.keywordPlusMULTITARGET TRACKING-
dc.subject.keywordPlusCONVEX-OPTIMIZATION-
dc.subject.keywordPlusMULTISENSOR FUSION-
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