ROTI-Based Stochastic Model to Improve GNSS Precise Point Positioning Under Severe Geomagnetic Storm Activity

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorChina University of Geosciences (Wuhan)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorWuhan University-
Autor(es): dc.contributorHubei Luojia Laboratory-
Autor(es): dc.creatorLuo, Xiaomin-
Autor(es): dc.creatorDu, Junfeng-
Autor(es): dc.creatorMonico, João Francisco Galera-
Autor(es): dc.creatorXiong, Chao-
Autor(es): dc.creatorLiu, Jingbin-
Autor(es): dc.creatorLiang, Xinmei-
Data de aceite: dc.date.accessioned2025-08-21T21:13:50Z-
Data de disponibilização: dc.date.available2025-08-21T21:13:50Z-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2022-07-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1029/2022SW003114-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/240548-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/240548-
Descrição: dc.descriptionFor global navigation satellite system (GNSS), ionospheric disturbances caused by the geomagnetic storm can reduce the accuracy and reliability of precision point positioning (PPP). At present, common stochastic models in GNSS PPP, such as the elevation angle stochastic (EAS) model or carrier-to-noise power-density ratio ((Formula presented.)) based SIGMA- (Formula presented.) model, do not properly consider storm effects on GNSS measurements. To mitigate severe storm effects on GNSS PPP, this study further implements the rate of total electron content index (ROTI) parameter into the EAS model referred to as the EAS-ROTI model. This model contains two operations. The first one is to adjust variance of GNSS measurements using ROTI observations on EAS model. The second one is to determine the ratio of the priori variance factor between pseudorange and carrier phase measurements during severe storm conditions. The performance of EAS-ROTI model is verified by using a large number of international GNSS service stations datasets on 17 March and 23 June in 2015. Experimental results indicate that on a global scale, the EAS-ROTI model improves the PPP accuracy in 3D direction by approximately 12.9%–14.7% compared with the EAS model, and by about 24.8%–45.9% compared with the SIGMA- (Formula presented.) model.-
Descrição: dc.descriptionChina Postdoctoral Science Foundation-
Descrição: dc.descriptionNational Natural Science Foundation of China-
Descrição: dc.descriptionChina University of Geosciences-
Descrição: dc.descriptionSchool of Geography and Information Engineering China University of Geosciences (Wuhan)-
Descrição: dc.descriptionFaculty of Science and Technology Sao Paulo State University-
Descrição: dc.descriptionDepartment of Space Physics Electronic Information School Wuhan University-
Descrição: dc.descriptionHubei Luojia Laboratory-
Descrição: dc.descriptionState Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University-
Descrição: dc.descriptionFaculty of Science and Technology Sao Paulo State University-
Descrição: dc.descriptionChina Postdoctoral Science Foundation: 2021M692975-
Descrição: dc.descriptionNational Natural Science Foundation of China: 41874031-
Descrição: dc.descriptionNational Natural Science Foundation of China: 42104029-
Descrição: dc.descriptionNational Natural Science Foundation of China: 42111530064-
Descrição: dc.descriptionChina University of Geosciences: CUG2106354-
Idioma: dc.languageen-
Relação: dc.relationSpace Weather-
???dc.source???: dc.sourceScopus-
Título: dc.titleROTI-Based Stochastic Model to Improve GNSS Precise Point Positioning Under Severe Geomagnetic Storm Activity-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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