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Ionospheric VTEC and satellite DCB estimated from single-frequency BDS observations with multi-layer mapping function
Su, Ke1,2; Jin, Shuanggen1,3,4; Jiang, J.3; Hoque, Mainul5; Yuan, Liangliang1,2
2021-03-01
Source PublicationGPS SOLUTIONS
ISSN1080-5370
Volume25Issue:2Pages:17
AbstractThe ionospheric delays and satellite differential code biases (DCBs) act as the significant error sources in the global navigation satellite system (GNSS) positioning, navigation and timing (PNT) services, and are still challenging to estimate correctly. In this study, the ionospheric vertical total electron content (VTEC) and satellite DCBs are estimated by a refining single-frequency precise point positioning (SFPPP) method based on the multi-layer ionosphere mapping function (MF), as well as the dual-frequency methods, including the carrier-to-code leveling (CCL) and dual-frequency PPP (DFPPP). The solutions isolate the ionospheric VTEC values from the slant ionospheric delay with the generalized trigonometric series function (GTSF) and precisely estimate the satellite DCB with a zero-mean condition. The SFPPP-derived VTEC estimates are validated and evaluated by comparing with the International GNSS Service (IGS) products and using ionosphere-corrected (IC) SFPPP in both static and kinematic scenarios. Using the 74 experimental stations collected from the multi-GNSS experiment (MGEX) network from January to March 2020, the results show that the VTEC estimation precision by applying the multi-layer MF is improved for the SFPPP approach. The positioning performances of the static and kinematic BDS IC SFPPP with the ionospheric correction derived from the multi-layer MF SFPPP are better when compared to the single-layer MF. The estimated BDS DCB with the SFPPP is stable and of high accuracy. The SFPPP approach with multi-layer MF is demonstrated as a promising and reliable method to retrieve the VTEC and satellite DCB with the low-cost property for the GNSS users.
KeywordBeiDou Navigation Satellite System (BDS) Vertical total electron content (VTEC) Single-frequency Precise point positioning (PPP) Differential code bias (DCB)
Funding OrganizationNational Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China-German Science Foundation ; National Natural Science Foundation of China-German Science Foundation ; Shanghai Leading Talent Project ; Shanghai Leading Talent Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China-German Science Foundation ; National Natural Science Foundation of China-German Science Foundation ; Shanghai Leading Talent Project ; Shanghai Leading Talent Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China-German Science Foundation ; National Natural Science Foundation of China-German Science Foundation ; Shanghai Leading Talent Project ; Shanghai Leading Talent Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China-German Science Foundation ; National Natural Science Foundation of China-German Science Foundation ; Shanghai Leading Talent Project ; Shanghai Leading Talent Project
DOI10.1007/s10291-021-01102-5
Language英语
Funding ProjectNational Natural Science Foundation of China[12073012] ; National Natural Science Foundation of China-German Science Foundation[41761134092] ; Shanghai Leading Talent Project[E056061]
Funding OrganizationNational Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China-German Science Foundation ; National Natural Science Foundation of China-German Science Foundation ; Shanghai Leading Talent Project ; Shanghai Leading Talent Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China-German Science Foundation ; National Natural Science Foundation of China-German Science Foundation ; Shanghai Leading Talent Project ; Shanghai Leading Talent Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China-German Science Foundation ; National Natural Science Foundation of China-German Science Foundation ; Shanghai Leading Talent Project ; Shanghai Leading Talent Project ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China-German Science Foundation ; National Natural Science Foundation of China-German Science Foundation ; Shanghai Leading Talent Project ; Shanghai Leading Talent Project
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000625177000001
PublisherSPRINGER HEIDELBERG
Citation statistics
Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/78655
Collection中国科学院国家天文台
Corresponding AuthorJin, Shuanggen
Affiliation1.Chinese Acad Sci, Shanghai Astron Observ, Shanghai 200030, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing 210044, Peoples R China
4.Jiangsu Engn Ctr Collaborat Nav Positioning & Sma, Nanjing 210044, Peoples R China
5.German Aerosp Ctr, Inst Solar Terr Phys, D-17235 Neustrelitz, Germany
Recommended Citation
GB/T 7714
Su, Ke,Jin, Shuanggen,Jiang, J.,et al. Ionospheric VTEC and satellite DCB estimated from single-frequency BDS observations with multi-layer mapping function[J]. GPS SOLUTIONS,2021,25(2):17.
APA Su, Ke,Jin, Shuanggen,Jiang, J.,Hoque, Mainul,&Yuan, Liangliang.(2021).Ionospheric VTEC and satellite DCB estimated from single-frequency BDS observations with multi-layer mapping function.GPS SOLUTIONS,25(2),17.
MLA Su, Ke,et al."Ionospheric VTEC and satellite DCB estimated from single-frequency BDS observations with multi-layer mapping function".GPS SOLUTIONS 25.2(2021):17.
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