Using cubic splines to mitigate systematic errors in GPS relative positioning

Detalhes bibliográficos
Autor(a) principal: Alves, Daniele Barroca Marra [UNESP]
Data de Publicação: 2004
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://www.ion.org/publications/abstract.cfm?articleID=5816
http://hdl.handle.net/11449/68030
Resumo: Systematic errors can have a significant effect on GPS observable. In medium and long baselines the major systematic error source are the ionosphere and troposphere refraction and the GPS satellites orbit errors. But, in short baselines, the multipath is more relevant. These errors degrade the accuracy of the positioning accomplished by GPS. So, this is a critical problem for high precision GPS positioning applications. Recently, a method has been suggested to mitigate these errors: the semiparametric model and the penalised least squares technique. It uses a natural cubic spline to model the errors as a function which varies smoothly in time. The systematic errors functions, ambiguities and station coordinates, are estimated simultaneously. As a result, the ambiguities and the station coordinates are estimated with better reliability and accuracy than the conventional least square method.
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spelling Using cubic splines to mitigate systematic errors in GPS relative positioningData acquisitionElectromagnetic wave refractionIonosphereLeast squares approximationsMathematical modelsMeteorological problemsNavigationReceiving antennasSplinesSystematic errorsTroposphereAtmosphere refractionsGlobal Navigation Satellite Systems (GNSS)Relative positioningTerrestrial surfaceGlobal positioning systemSystematic errors can have a significant effect on GPS observable. In medium and long baselines the major systematic error source are the ionosphere and troposphere refraction and the GPS satellites orbit errors. But, in short baselines, the multipath is more relevant. These errors degrade the accuracy of the positioning accomplished by GPS. So, this is a critical problem for high precision GPS positioning applications. Recently, a method has been suggested to mitigate these errors: the semiparametric model and the penalised least squares technique. It uses a natural cubic spline to model the errors as a function which varies smoothly in time. The systematic errors functions, ambiguities and station coordinates, are estimated simultaneously. As a result, the ambiguities and the station coordinates are estimated with better reliability and accuracy than the conventional least square method.São Paulo State UniversitySão Paulo State UniversityUniversidade Estadual Paulista (Unesp)Alves, Daniele Barroca Marra [UNESP]2014-05-27T11:21:13Z2014-05-27T11:21:13Z2004-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1374-1381http://www.ion.org/publications/abstract.cfm?articleID=5816Proceedings of the 17th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2004, p. 1374-1381.http://hdl.handle.net/11449/680302-s2.0-22144437417Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the 17th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2004info:eu-repo/semantics/openAccess2024-06-18T15:02:39Zoai:repositorio.unesp.br:11449/68030Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:26:58.757632Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Using cubic splines to mitigate systematic errors in GPS relative positioning
title Using cubic splines to mitigate systematic errors in GPS relative positioning
spellingShingle Using cubic splines to mitigate systematic errors in GPS relative positioning
Alves, Daniele Barroca Marra [UNESP]
Data acquisition
Electromagnetic wave refraction
Ionosphere
Least squares approximations
Mathematical models
Meteorological problems
Navigation
Receiving antennas
Splines
Systematic errors
Troposphere
Atmosphere refractions
Global Navigation Satellite Systems (GNSS)
Relative positioning
Terrestrial surface
Global positioning system
title_short Using cubic splines to mitigate systematic errors in GPS relative positioning
title_full Using cubic splines to mitigate systematic errors in GPS relative positioning
title_fullStr Using cubic splines to mitigate systematic errors in GPS relative positioning
title_full_unstemmed Using cubic splines to mitigate systematic errors in GPS relative positioning
title_sort Using cubic splines to mitigate systematic errors in GPS relative positioning
author Alves, Daniele Barroca Marra [UNESP]
author_facet Alves, Daniele Barroca Marra [UNESP]
author_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Alves, Daniele Barroca Marra [UNESP]
dc.subject.por.fl_str_mv Data acquisition
Electromagnetic wave refraction
Ionosphere
Least squares approximations
Mathematical models
Meteorological problems
Navigation
Receiving antennas
Splines
Systematic errors
Troposphere
Atmosphere refractions
Global Navigation Satellite Systems (GNSS)
Relative positioning
Terrestrial surface
Global positioning system
topic Data acquisition
Electromagnetic wave refraction
Ionosphere
Least squares approximations
Mathematical models
Meteorological problems
Navigation
Receiving antennas
Splines
Systematic errors
Troposphere
Atmosphere refractions
Global Navigation Satellite Systems (GNSS)
Relative positioning
Terrestrial surface
Global positioning system
description Systematic errors can have a significant effect on GPS observable. In medium and long baselines the major systematic error source are the ionosphere and troposphere refraction and the GPS satellites orbit errors. But, in short baselines, the multipath is more relevant. These errors degrade the accuracy of the positioning accomplished by GPS. So, this is a critical problem for high precision GPS positioning applications. Recently, a method has been suggested to mitigate these errors: the semiparametric model and the penalised least squares technique. It uses a natural cubic spline to model the errors as a function which varies smoothly in time. The systematic errors functions, ambiguities and station coordinates, are estimated simultaneously. As a result, the ambiguities and the station coordinates are estimated with better reliability and accuracy than the conventional least square method.
publishDate 2004
dc.date.none.fl_str_mv 2004-12-01
2014-05-27T11:21:13Z
2014-05-27T11:21:13Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.ion.org/publications/abstract.cfm?articleID=5816
Proceedings of the 17th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2004, p. 1374-1381.
http://hdl.handle.net/11449/68030
2-s2.0-22144437417
url http://www.ion.org/publications/abstract.cfm?articleID=5816
http://hdl.handle.net/11449/68030
identifier_str_mv Proceedings of the 17th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2004, p. 1374-1381.
2-s2.0-22144437417
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Proceedings of the 17th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2004
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1374-1381
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808129070562541568

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