Evaluate the Impact of Regional Ionospheric Data Assimilation Model on Precise Point Positioning
Abstract This study presents an innovative approach to improving the accuracy and reducing the error convergence time of static Precise Point Positioning (PPP) in Global Positioning System (GPS) navigation. The research focuses on the impact of the high spatial and temporal resolution of a regional...
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| Format: | Article |
| Language: | English |
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Wiley
2024-08-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2024SW003858 |
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| _version_ | 1841536447243354112 |
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| author | Yan‐Shen Chen Chia‐Hung Chen Ming Yang Feng‐Yu Chu |
| author_facet | Yan‐Shen Chen Chia‐Hung Chen Ming Yang Feng‐Yu Chu |
| author_sort | Yan‐Shen Chen |
| collection | DOAJ |
| description | Abstract This study presents an innovative approach to improving the accuracy and reducing the error convergence time of static Precise Point Positioning (PPP) in Global Positioning System (GPS) navigation. The research focuses on the impact of the high spatial and temporal resolution of a regional ionospheric data assimilation model on PPP over Taiwan. The study further evaluates the performance of both static PPP with the ionospheric information using commonly used models such as Klobuchar and International Reference Ionosphere (IRI), as well as a global ionospheric data assimilation model. Compared to the default IRI, the data assimilated IRI model can improve the overall ionospheric total electron content by approximately 83%. Additionally, it can significantly reduce horizontal positioning errors and shorten the error convergence time more than 52% for static PPP, even during geomagnetic storm events. The study concludes that the high resolution of a regional ionospheric data assimilation model can enhance the accuracy and reduce the error convergence time of PPP navigation and positioning. This research provides valuable insights for future studies in this field, especially in the development of more precise and efficient models for correcting ionospheric delay in GPS navigation. |
| format | Article |
| id | doaj-art-e4b2c73169754086b870f19cdaeb79ac |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2024-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-e4b2c73169754086b870f19cdaeb79ac2025-01-14T16:27:32ZengWileySpace Weather1542-73902024-08-01228n/an/a10.1029/2024SW003858Evaluate the Impact of Regional Ionospheric Data Assimilation Model on Precise Point PositioningYan‐Shen Chen0Chia‐Hung Chen1Ming Yang2Feng‐Yu Chu3Department of Earth Sciences National Cheng Kung University Tainan TaiwanDepartment of Earth Sciences National Cheng Kung University Tainan TaiwanDepartment of Geomatics National Cheng Kung University Tainan TaiwanDepartment of Geomatics National Cheng Kung University Tainan TaiwanAbstract This study presents an innovative approach to improving the accuracy and reducing the error convergence time of static Precise Point Positioning (PPP) in Global Positioning System (GPS) navigation. The research focuses on the impact of the high spatial and temporal resolution of a regional ionospheric data assimilation model on PPP over Taiwan. The study further evaluates the performance of both static PPP with the ionospheric information using commonly used models such as Klobuchar and International Reference Ionosphere (IRI), as well as a global ionospheric data assimilation model. Compared to the default IRI, the data assimilated IRI model can improve the overall ionospheric total electron content by approximately 83%. Additionally, it can significantly reduce horizontal positioning errors and shorten the error convergence time more than 52% for static PPP, even during geomagnetic storm events. The study concludes that the high resolution of a regional ionospheric data assimilation model can enhance the accuracy and reduce the error convergence time of PPP navigation and positioning. This research provides valuable insights for future studies in this field, especially in the development of more precise and efficient models for correcting ionospheric delay in GPS navigation.https://doi.org/10.1029/2024SW003858ionospheric data assimilationregional ionospheric modelprecise point positioning |
| spellingShingle | Yan‐Shen Chen Chia‐Hung Chen Ming Yang Feng‐Yu Chu Evaluate the Impact of Regional Ionospheric Data Assimilation Model on Precise Point Positioning Space Weather ionospheric data assimilation regional ionospheric model precise point positioning |
| title | Evaluate the Impact of Regional Ionospheric Data Assimilation Model on Precise Point Positioning |
| title_full | Evaluate the Impact of Regional Ionospheric Data Assimilation Model on Precise Point Positioning |
| title_fullStr | Evaluate the Impact of Regional Ionospheric Data Assimilation Model on Precise Point Positioning |
| title_full_unstemmed | Evaluate the Impact of Regional Ionospheric Data Assimilation Model on Precise Point Positioning |
| title_short | Evaluate the Impact of Regional Ionospheric Data Assimilation Model on Precise Point Positioning |
| title_sort | evaluate the impact of regional ionospheric data assimilation model on precise point positioning |
| topic | ionospheric data assimilation regional ionospheric model precise point positioning |
| url | https://doi.org/10.1029/2024SW003858 |
| work_keys_str_mv | AT yanshenchen evaluatetheimpactofregionalionosphericdataassimilationmodelonprecisepointpositioning AT chiahungchen evaluatetheimpactofregionalionosphericdataassimilationmodelonprecisepointpositioning AT mingyang evaluatetheimpactofregionalionosphericdataassimilationmodelonprecisepointpositioning AT fengyuchu evaluatetheimpactofregionalionosphericdataassimilationmodelonprecisepointpositioning |