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A Satellite Clock Bias Estimation Method Considering the Noise Component of GNSS Spaceborne Atomic Clocks
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Linfeng ZHU1, Zhongyuan WANG1, *, Chao HU2, Jiaxing YANG1
Journal of Geodesy and Geodynamics | 2026, 46(5) : 587 - 598
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Journal of Geodesy and Geodynamics | 2026, 46(5): 587-598
A Satellite Clock Bias Estimation Method Considering the Noise Component of GNSS Spaceborne Atomic Clocks
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Linfeng ZHU1, Zhongyuan WANG1, *, Chao HU2, Jiaxing YANG1
Affiliations
  • 1 School of Environment and Surveying, China University of Mining and Technology, Xuzhou 221116, China
  • 2 School of Spatial Information and Surveying Engineering, Anhui University of Science and Technology, Huainan 232001, China
Published: 2026-05-15 doi: 10.14075/j.jgg.2025.07.249
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Given the issue that multi-system satellite clock bias estimation is susceptible to interference from various noise types, an estimation model that fully considers the characteristics of satellite clock noise components is proposed. This model employs two strategies, namely sliding window and overall modeling, and utilizes the Hadamard variance to solve for noise parameters. Based on this, clock bias estimation and accuracy assessment are conducted. In the experimental section, multiple representative satellites from the four major satellite navigation systems—GPS, BDS-3, Galileo, and GLONASS are selected as research subjects. A systematic comparative analysis is performed on the performance differences of the two modeling strategies across different systems and satellites. The experimental results reveal that the BDS-3 exhibits significant inter-satellite variability. Specifically, most satellites in MEO demonstrate more pronounced time-varying noise characteristics, making them more suitable for the sliding modeling strategy. Conversely, for some satellites equipped with MEO rubidium clocks and stable IGSO satellites, the overall modeling strategy offers greater advantages. In the case of the Galileo, the global modeling strategy performs better. For the GPS and GLONASS, after adopting the sliding window strategy, the positioning accuracy in E, N, U directions improves by 10.34%, 17.07%, and 4.30%, respectively, and by 6.27%, 10.34%, and 3.76%, respectively, compared to the overall modeling strategy.

GNSS  /  noise component  /  Hadamard variance  /  clock bias estimation  /  accuracy assessment
朱麟丰, 王中元, 胡超, 杨嘉兴. 顾及GNSS星载原子钟噪声分量的卫星钟差估计方法. 大地测量与地球动力学, 2026 , 46 (5) : 587 -598 . DOI: 10.14075/j.jgg.2025.07.249
Linfeng ZHU, Zhongyuan WANG, Chao HU, Jiaxing YANG. A Satellite Clock Bias Estimation Method Considering the Noise Component of GNSS Spaceborne Atomic Clocks[J]. Journal of Geodesy and Geodynamics, 2026 , 46 (5) : 587 -598 . DOI: 10.14075/j.jgg.2025.07.249
Year 2026 volume 46 Issue 5
29
11
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doi: 10.14075/j.jgg.2025.07.249
  • Receive Date:2025-07-15
  • Online Date:2026-10-29
  • Published:2026-05-15
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  • Received:2025-07-15
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    1 School of Environment and Surveying, China University of Mining and Technology, Xuzhou 221116, China
    2 School of Spatial Information and Surveying Engineering, Anhui University of Science and Technology, Huainan 232001, China
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表12种不同金属材料的力学参数
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Family
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Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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