Zero-Reconvergence PPP for Real-Time Low-Earth Satellite Orbit Determination in Case of Data Interruption
With the fast development of low earth orbit (LEO) enhanced global navigation satellite system (LeGNSS), there is huge demand in LEO real-time precise orbit determination. Real-time service from international GNSS service (IGS) provides the real-time precise GNSS orbit and clock products, which give...
Ausführliche Beschreibung
Autor*in: |
Haibo Ge [verfasserIn] Guanlong Meng [verfasserIn] Bofeng Li [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2024 |
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Schlagwörter: |
low earth orbit (LEO) satellites |
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Übergeordnetes Werk: |
In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing - IEEE, 2020, 17(2024), Seite 4705-4715 |
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Übergeordnetes Werk: |
volume:17 ; year:2024 ; pages:4705-4715 |
Links: |
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DOI / URN: |
10.1109/JSTARS.2024.3362395 |
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Katalog-ID: |
DOAJ098412043 |
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520 | |a With the fast development of low earth orbit (LEO) enhanced global navigation satellite system (LeGNSS), there is huge demand in LEO real-time precise orbit determination. Real-time service from international GNSS service (IGS) provides the real-time precise GNSS orbit and clock products, which gives an opportunity to make use of kinematic precise point positioning (PPP) method for LEO POD. However, real-time precise GNSS products and onboard GNSS observations interrupt inevitably or even frequently (especially for real-time clock products), resulting in PPP reconvergence as well as large orbit errors in LEO orbit solutions. A new method is put forward to reduce such influence of two types of data interruptions. For interruption of clock products, the Chebyshev extrapolation is used to maintain the continuity of real-time GNSS clock products. For the onboard observation interruption, the predicted dynamic orbits are employed as constraints to overcome the PPP reconvergence. Results show that zero-reconvergence PPP can be realized with our new method, which means there is almost no reconvergence time after data interruption. Moreover, clock prediction can reduce the root–mean-square errors (RMSE) for real-time LEO orbit from 5.40, 4.70, and 7.33 cm to 5.18, 4.55, and 5.99 cm in along-track, cross-track, and radial directions, respectively, while the predicted dynamic orbit constraints reduce the orbit RMSE by 20--30% in cross-track component and 60%–80% in other two components. | ||
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10.1109/JSTARS.2024.3362395 doi (DE-627)DOAJ098412043 (DE-599)DOAJ352aa54c6fc943a0ab686d1f203f2db5 DE-627 ger DE-627 rakwb eng TC1501-1800 QC801-809 Haibo Ge verfasserin aut Zero-Reconvergence PPP for Real-Time Low-Earth Satellite Orbit Determination in Case of Data Interruption 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the fast development of low earth orbit (LEO) enhanced global navigation satellite system (LeGNSS), there is huge demand in LEO real-time precise orbit determination. Real-time service from international GNSS service (IGS) provides the real-time precise GNSS orbit and clock products, which gives an opportunity to make use of kinematic precise point positioning (PPP) method for LEO POD. However, real-time precise GNSS products and onboard GNSS observations interrupt inevitably or even frequently (especially for real-time clock products), resulting in PPP reconvergence as well as large orbit errors in LEO orbit solutions. A new method is put forward to reduce such influence of two types of data interruptions. For interruption of clock products, the Chebyshev extrapolation is used to maintain the continuity of real-time GNSS clock products. For the onboard observation interruption, the predicted dynamic orbits are employed as constraints to overcome the PPP reconvergence. Results show that zero-reconvergence PPP can be realized with our new method, which means there is almost no reconvergence time after data interruption. Moreover, clock prediction can reduce the root–mean-square errors (RMSE) for real-time LEO orbit from 5.40, 4.70, and 7.33 cm to 5.18, 4.55, and 5.99 cm in along-track, cross-track, and radial directions, respectively, while the predicted dynamic orbit constraints reduce the orbit RMSE by 20--30% in cross-track component and 60%–80% in other two components. Data interruption low earth orbit (LEO) satellites precise point positioning (PPP) reconvergence real-time kinematic orbit determination Ocean engineering Geophysics. Cosmic physics Guanlong Meng verfasserin aut Bofeng Li verfasserin aut In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE, 2020 17(2024), Seite 4705-4715 (DE-627)581732634 (DE-600)2457423-5 21511535 nnns volume:17 year:2024 pages:4705-4715 https://doi.org/10.1109/JSTARS.2024.3362395 kostenfrei https://doaj.org/article/352aa54c6fc943a0ab686d1f203f2db5 kostenfrei https://ieeexplore.ieee.org/document/10423121/ kostenfrei https://doaj.org/toc/2151-1535 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2472 GBV_ILN_2522 GBV_ILN_2965 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2024 4705-4715 |
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10.1109/JSTARS.2024.3362395 doi (DE-627)DOAJ098412043 (DE-599)DOAJ352aa54c6fc943a0ab686d1f203f2db5 DE-627 ger DE-627 rakwb eng TC1501-1800 QC801-809 Haibo Ge verfasserin aut Zero-Reconvergence PPP for Real-Time Low-Earth Satellite Orbit Determination in Case of Data Interruption 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the fast development of low earth orbit (LEO) enhanced global navigation satellite system (LeGNSS), there is huge demand in LEO real-time precise orbit determination. Real-time service from international GNSS service (IGS) provides the real-time precise GNSS orbit and clock products, which gives an opportunity to make use of kinematic precise point positioning (PPP) method for LEO POD. However, real-time precise GNSS products and onboard GNSS observations interrupt inevitably or even frequently (especially for real-time clock products), resulting in PPP reconvergence as well as large orbit errors in LEO orbit solutions. A new method is put forward to reduce such influence of two types of data interruptions. For interruption of clock products, the Chebyshev extrapolation is used to maintain the continuity of real-time GNSS clock products. For the onboard observation interruption, the predicted dynamic orbits are employed as constraints to overcome the PPP reconvergence. Results show that zero-reconvergence PPP can be realized with our new method, which means there is almost no reconvergence time after data interruption. Moreover, clock prediction can reduce the root–mean-square errors (RMSE) for real-time LEO orbit from 5.40, 4.70, and 7.33 cm to 5.18, 4.55, and 5.99 cm in along-track, cross-track, and radial directions, respectively, while the predicted dynamic orbit constraints reduce the orbit RMSE by 20--30% in cross-track component and 60%–80% in other two components. Data interruption low earth orbit (LEO) satellites precise point positioning (PPP) reconvergence real-time kinematic orbit determination Ocean engineering Geophysics. Cosmic physics Guanlong Meng verfasserin aut Bofeng Li verfasserin aut In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE, 2020 17(2024), Seite 4705-4715 (DE-627)581732634 (DE-600)2457423-5 21511535 nnns volume:17 year:2024 pages:4705-4715 https://doi.org/10.1109/JSTARS.2024.3362395 kostenfrei https://doaj.org/article/352aa54c6fc943a0ab686d1f203f2db5 kostenfrei https://ieeexplore.ieee.org/document/10423121/ kostenfrei https://doaj.org/toc/2151-1535 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2472 GBV_ILN_2522 GBV_ILN_2965 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2024 4705-4715 |
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10.1109/JSTARS.2024.3362395 doi (DE-627)DOAJ098412043 (DE-599)DOAJ352aa54c6fc943a0ab686d1f203f2db5 DE-627 ger DE-627 rakwb eng TC1501-1800 QC801-809 Haibo Ge verfasserin aut Zero-Reconvergence PPP for Real-Time Low-Earth Satellite Orbit Determination in Case of Data Interruption 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the fast development of low earth orbit (LEO) enhanced global navigation satellite system (LeGNSS), there is huge demand in LEO real-time precise orbit determination. Real-time service from international GNSS service (IGS) provides the real-time precise GNSS orbit and clock products, which gives an opportunity to make use of kinematic precise point positioning (PPP) method for LEO POD. However, real-time precise GNSS products and onboard GNSS observations interrupt inevitably or even frequently (especially for real-time clock products), resulting in PPP reconvergence as well as large orbit errors in LEO orbit solutions. A new method is put forward to reduce such influence of two types of data interruptions. For interruption of clock products, the Chebyshev extrapolation is used to maintain the continuity of real-time GNSS clock products. For the onboard observation interruption, the predicted dynamic orbits are employed as constraints to overcome the PPP reconvergence. Results show that zero-reconvergence PPP can be realized with our new method, which means there is almost no reconvergence time after data interruption. Moreover, clock prediction can reduce the root–mean-square errors (RMSE) for real-time LEO orbit from 5.40, 4.70, and 7.33 cm to 5.18, 4.55, and 5.99 cm in along-track, cross-track, and radial directions, respectively, while the predicted dynamic orbit constraints reduce the orbit RMSE by 20--30% in cross-track component and 60%–80% in other two components. Data interruption low earth orbit (LEO) satellites precise point positioning (PPP) reconvergence real-time kinematic orbit determination Ocean engineering Geophysics. Cosmic physics Guanlong Meng verfasserin aut Bofeng Li verfasserin aut In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE, 2020 17(2024), Seite 4705-4715 (DE-627)581732634 (DE-600)2457423-5 21511535 nnns volume:17 year:2024 pages:4705-4715 https://doi.org/10.1109/JSTARS.2024.3362395 kostenfrei https://doaj.org/article/352aa54c6fc943a0ab686d1f203f2db5 kostenfrei https://ieeexplore.ieee.org/document/10423121/ kostenfrei https://doaj.org/toc/2151-1535 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2472 GBV_ILN_2522 GBV_ILN_2965 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2024 4705-4715 |
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10.1109/JSTARS.2024.3362395 doi (DE-627)DOAJ098412043 (DE-599)DOAJ352aa54c6fc943a0ab686d1f203f2db5 DE-627 ger DE-627 rakwb eng TC1501-1800 QC801-809 Haibo Ge verfasserin aut Zero-Reconvergence PPP for Real-Time Low-Earth Satellite Orbit Determination in Case of Data Interruption 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the fast development of low earth orbit (LEO) enhanced global navigation satellite system (LeGNSS), there is huge demand in LEO real-time precise orbit determination. Real-time service from international GNSS service (IGS) provides the real-time precise GNSS orbit and clock products, which gives an opportunity to make use of kinematic precise point positioning (PPP) method for LEO POD. However, real-time precise GNSS products and onboard GNSS observations interrupt inevitably or even frequently (especially for real-time clock products), resulting in PPP reconvergence as well as large orbit errors in LEO orbit solutions. A new method is put forward to reduce such influence of two types of data interruptions. For interruption of clock products, the Chebyshev extrapolation is used to maintain the continuity of real-time GNSS clock products. For the onboard observation interruption, the predicted dynamic orbits are employed as constraints to overcome the PPP reconvergence. Results show that zero-reconvergence PPP can be realized with our new method, which means there is almost no reconvergence time after data interruption. Moreover, clock prediction can reduce the root–mean-square errors (RMSE) for real-time LEO orbit from 5.40, 4.70, and 7.33 cm to 5.18, 4.55, and 5.99 cm in along-track, cross-track, and radial directions, respectively, while the predicted dynamic orbit constraints reduce the orbit RMSE by 20--30% in cross-track component and 60%–80% in other two components. Data interruption low earth orbit (LEO) satellites precise point positioning (PPP) reconvergence real-time kinematic orbit determination Ocean engineering Geophysics. Cosmic physics Guanlong Meng verfasserin aut Bofeng Li verfasserin aut In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE, 2020 17(2024), Seite 4705-4715 (DE-627)581732634 (DE-600)2457423-5 21511535 nnns volume:17 year:2024 pages:4705-4715 https://doi.org/10.1109/JSTARS.2024.3362395 kostenfrei https://doaj.org/article/352aa54c6fc943a0ab686d1f203f2db5 kostenfrei https://ieeexplore.ieee.org/document/10423121/ kostenfrei https://doaj.org/toc/2151-1535 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2472 GBV_ILN_2522 GBV_ILN_2965 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2024 4705-4715 |
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10.1109/JSTARS.2024.3362395 doi (DE-627)DOAJ098412043 (DE-599)DOAJ352aa54c6fc943a0ab686d1f203f2db5 DE-627 ger DE-627 rakwb eng TC1501-1800 QC801-809 Haibo Ge verfasserin aut Zero-Reconvergence PPP for Real-Time Low-Earth Satellite Orbit Determination in Case of Data Interruption 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the fast development of low earth orbit (LEO) enhanced global navigation satellite system (LeGNSS), there is huge demand in LEO real-time precise orbit determination. Real-time service from international GNSS service (IGS) provides the real-time precise GNSS orbit and clock products, which gives an opportunity to make use of kinematic precise point positioning (PPP) method for LEO POD. However, real-time precise GNSS products and onboard GNSS observations interrupt inevitably or even frequently (especially for real-time clock products), resulting in PPP reconvergence as well as large orbit errors in LEO orbit solutions. A new method is put forward to reduce such influence of two types of data interruptions. For interruption of clock products, the Chebyshev extrapolation is used to maintain the continuity of real-time GNSS clock products. For the onboard observation interruption, the predicted dynamic orbits are employed as constraints to overcome the PPP reconvergence. Results show that zero-reconvergence PPP can be realized with our new method, which means there is almost no reconvergence time after data interruption. Moreover, clock prediction can reduce the root–mean-square errors (RMSE) for real-time LEO orbit from 5.40, 4.70, and 7.33 cm to 5.18, 4.55, and 5.99 cm in along-track, cross-track, and radial directions, respectively, while the predicted dynamic orbit constraints reduce the orbit RMSE by 20--30% in cross-track component and 60%–80% in other two components. Data interruption low earth orbit (LEO) satellites precise point positioning (PPP) reconvergence real-time kinematic orbit determination Ocean engineering Geophysics. Cosmic physics Guanlong Meng verfasserin aut Bofeng Li verfasserin aut In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE, 2020 17(2024), Seite 4705-4715 (DE-627)581732634 (DE-600)2457423-5 21511535 nnns volume:17 year:2024 pages:4705-4715 https://doi.org/10.1109/JSTARS.2024.3362395 kostenfrei https://doaj.org/article/352aa54c6fc943a0ab686d1f203f2db5 kostenfrei https://ieeexplore.ieee.org/document/10423121/ kostenfrei https://doaj.org/toc/2151-1535 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2472 GBV_ILN_2522 GBV_ILN_2965 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2024 4705-4715 |
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Haibo Ge misc TC1501-1800 misc QC801-809 misc Data interruption misc low earth orbit (LEO) satellites misc precise point positioning (PPP) reconvergence misc real-time kinematic orbit determination misc Ocean engineering misc Geophysics. Cosmic physics Zero-Reconvergence PPP for Real-Time Low-Earth Satellite Orbit Determination in Case of Data Interruption |
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TC1501-1800 QC801-809 Zero-Reconvergence PPP for Real-Time Low-Earth Satellite Orbit Determination in Case of Data Interruption Data interruption low earth orbit (LEO) satellites precise point positioning (PPP) reconvergence real-time kinematic orbit determination |
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Zero-Reconvergence PPP for Real-Time Low-Earth Satellite Orbit Determination in Case of Data Interruption |
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zero-reconvergence ppp for real-time low-earth satellite orbit determination in case of data interruption |
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Zero-Reconvergence PPP for Real-Time Low-Earth Satellite Orbit Determination in Case of Data Interruption |
abstract |
With the fast development of low earth orbit (LEO) enhanced global navigation satellite system (LeGNSS), there is huge demand in LEO real-time precise orbit determination. Real-time service from international GNSS service (IGS) provides the real-time precise GNSS orbit and clock products, which gives an opportunity to make use of kinematic precise point positioning (PPP) method for LEO POD. However, real-time precise GNSS products and onboard GNSS observations interrupt inevitably or even frequently (especially for real-time clock products), resulting in PPP reconvergence as well as large orbit errors in LEO orbit solutions. A new method is put forward to reduce such influence of two types of data interruptions. For interruption of clock products, the Chebyshev extrapolation is used to maintain the continuity of real-time GNSS clock products. For the onboard observation interruption, the predicted dynamic orbits are employed as constraints to overcome the PPP reconvergence. Results show that zero-reconvergence PPP can be realized with our new method, which means there is almost no reconvergence time after data interruption. Moreover, clock prediction can reduce the root–mean-square errors (RMSE) for real-time LEO orbit from 5.40, 4.70, and 7.33 cm to 5.18, 4.55, and 5.99 cm in along-track, cross-track, and radial directions, respectively, while the predicted dynamic orbit constraints reduce the orbit RMSE by 20--30% in cross-track component and 60%–80% in other two components. |
abstractGer |
With the fast development of low earth orbit (LEO) enhanced global navigation satellite system (LeGNSS), there is huge demand in LEO real-time precise orbit determination. Real-time service from international GNSS service (IGS) provides the real-time precise GNSS orbit and clock products, which gives an opportunity to make use of kinematic precise point positioning (PPP) method for LEO POD. However, real-time precise GNSS products and onboard GNSS observations interrupt inevitably or even frequently (especially for real-time clock products), resulting in PPP reconvergence as well as large orbit errors in LEO orbit solutions. A new method is put forward to reduce such influence of two types of data interruptions. For interruption of clock products, the Chebyshev extrapolation is used to maintain the continuity of real-time GNSS clock products. For the onboard observation interruption, the predicted dynamic orbits are employed as constraints to overcome the PPP reconvergence. Results show that zero-reconvergence PPP can be realized with our new method, which means there is almost no reconvergence time after data interruption. Moreover, clock prediction can reduce the root–mean-square errors (RMSE) for real-time LEO orbit from 5.40, 4.70, and 7.33 cm to 5.18, 4.55, and 5.99 cm in along-track, cross-track, and radial directions, respectively, while the predicted dynamic orbit constraints reduce the orbit RMSE by 20--30% in cross-track component and 60%–80% in other two components. |
abstract_unstemmed |
With the fast development of low earth orbit (LEO) enhanced global navigation satellite system (LeGNSS), there is huge demand in LEO real-time precise orbit determination. Real-time service from international GNSS service (IGS) provides the real-time precise GNSS orbit and clock products, which gives an opportunity to make use of kinematic precise point positioning (PPP) method for LEO POD. However, real-time precise GNSS products and onboard GNSS observations interrupt inevitably or even frequently (especially for real-time clock products), resulting in PPP reconvergence as well as large orbit errors in LEO orbit solutions. A new method is put forward to reduce such influence of two types of data interruptions. For interruption of clock products, the Chebyshev extrapolation is used to maintain the continuity of real-time GNSS clock products. For the onboard observation interruption, the predicted dynamic orbits are employed as constraints to overcome the PPP reconvergence. Results show that zero-reconvergence PPP can be realized with our new method, which means there is almost no reconvergence time after data interruption. Moreover, clock prediction can reduce the root–mean-square errors (RMSE) for real-time LEO orbit from 5.40, 4.70, and 7.33 cm to 5.18, 4.55, and 5.99 cm in along-track, cross-track, and radial directions, respectively, while the predicted dynamic orbit constraints reduce the orbit RMSE by 20--30% in cross-track component and 60%–80% in other two components. |
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Zero-Reconvergence PPP for Real-Time Low-Earth Satellite Orbit Determination in Case of Data Interruption |
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