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Article: Human mobility enhances global positioning accuracy for mobile phone localization

TitleHuman mobility enhances global positioning accuracy for mobile phone localization
Authors
Keywordsmobile phone localization
GPS
human mobility
Issue Date2015
Citation
IEEE Transactions on Parallel and Distributed Systems, 2015, v. 26, n. 1, p. 131-141 How to Cite?
AbstractGlobal positioning system (GPS) has enabled a number of geographical applications over many years. Quite a lot of location-based services, however, still suffer from considerable positioning errors of GPS (usually 1 to 20 m in practice). In this study, we design and implement a high-accuracy global positioning solution based on GPS and human mobility captured by mobile phones. Our key observation is that smartphone-enabled dead reckoning supports accurate but local coordinates of users' trajectories, while GPS provides global but inconsistent coordinates. Considering them simultaneously, we devise techniques to refine the global positioning results by fitting the global positions to the structure of locally measured ones, so the refined positioning results are more likely to elicit the ground truth. We develop a prototype system, named GloCal, and conduct comprehensive experiments in both crowded urban and spacious suburban areas. The evaluation results show that GloCal can achieve 30 percent improvement on average error with respect to GPS. GloCal uses merely mobile phones and requires no infrastructure or additional reference information. As an effective and light-weight augmentation to global positioning, GloCal holds promise in real-world feasibility.
Persistent Identifierhttp://hdl.handle.net/10722/303435
ISSN
2023 Impact Factor: 5.6
2023 SCImago Journal Rankings: 2.340
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWu, Chenshu-
dc.contributor.authorYang, Zheng-
dc.contributor.authorXu, Yu-
dc.contributor.authorZhao, Yiyang-
dc.contributor.authorLiu, Yunhao-
dc.date.accessioned2021-09-15T08:25:18Z-
dc.date.available2021-09-15T08:25:18Z-
dc.date.issued2015-
dc.identifier.citationIEEE Transactions on Parallel and Distributed Systems, 2015, v. 26, n. 1, p. 131-141-
dc.identifier.issn1045-9219-
dc.identifier.urihttp://hdl.handle.net/10722/303435-
dc.description.abstractGlobal positioning system (GPS) has enabled a number of geographical applications over many years. Quite a lot of location-based services, however, still suffer from considerable positioning errors of GPS (usually 1 to 20 m in practice). In this study, we design and implement a high-accuracy global positioning solution based on GPS and human mobility captured by mobile phones. Our key observation is that smartphone-enabled dead reckoning supports accurate but local coordinates of users' trajectories, while GPS provides global but inconsistent coordinates. Considering them simultaneously, we devise techniques to refine the global positioning results by fitting the global positions to the structure of locally measured ones, so the refined positioning results are more likely to elicit the ground truth. We develop a prototype system, named GloCal, and conduct comprehensive experiments in both crowded urban and spacious suburban areas. The evaluation results show that GloCal can achieve 30 percent improvement on average error with respect to GPS. GloCal uses merely mobile phones and requires no infrastructure or additional reference information. As an effective and light-weight augmentation to global positioning, GloCal holds promise in real-world feasibility.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Parallel and Distributed Systems-
dc.subjectmobile phone localization-
dc.subjectGPS-
dc.subjecthuman mobility-
dc.titleHuman mobility enhances global positioning accuracy for mobile phone localization-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TPDS.2014.2308225-
dc.identifier.scopuseid_2-s2.0-84919484246-
dc.identifier.volume26-
dc.identifier.issue1-
dc.identifier.spage131-
dc.identifier.epage141-
dc.identifier.isiWOS:000348206700013-

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