Attitude Determination for GRACE-FO: Reprocessing the Level-1A SC and IMU Data

被引:5
|
作者
Yang, Fan [1 ,2 ,3 ,4 ,5 ]
Liang, Lei [6 ]
Wang, Changqing [6 ]
Luo, Zhicai [1 ,2 ,3 ,4 ,5 ]
机构
[1] Huazhong Univ Sci & Technol, MOE, Key Lab Fundamental Phys Quant Measurement, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Hubei Key Lab Gravitat & Quantum Phys, PGMF, Wuhan 430074, Peoples R China
[3] Huazhong Univ Sci & Technol, Sch Phys, Wuhan 430074, Peoples R China
[4] Huazhong Univ Sci & Technol, Inst Geophys, Wuhan 430074, Peoples R China
[5] Huazhong Univ Sci & Technol, PGMF, Wuhan 430074, Peoples R China
[6] Chinese Acad Sci, Innovat Acad Precis Measurement Sci & Technol, Wuhan 430071, Peoples R China
基金
中国国家自然科学基金;
关键词
GRACE-FO; attitude determination; temporal gravity field; Kalman filter; SC; IMU; GRAVITY-FIELD; VARIABILITY;
D O I
10.3390/rs14010126
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The satellite gravity mission GRACE(-FO) has not yet reached its designed baseline accuracy. Previous studies demonstrated that the deficiency in the sensor system or the related signal processing might be responsible, which in turn motivates us to keep revising the sensor data processing, typically the spacecraft's attitude. Many efforts in the past have been made to enhance the attitude modeling for GRACE, for instance, the latest release reprocesses the attitude by fusing the angular acceleration with the star camera/tracker (SC) measurements, which helps to reduce the error in Level-2 temporal gravity fields. Therefore, in addition to GRACE, revising GRACE-FO attitude determination might make sense as well. This study starts with the most original raw GRACE-FO Level-1A data including those from three SCs and one IMU (Inertial Measurement Unit) sensors, and manage to generate a new publicly available Level-1B attitude product called HUGG-01 covering from June 2018 to December 2020, using our independently-developed software. The detailed treatment of individual payload is present in this study, and an indirect Kalman filter method is introduced to fuse the multiple sensors to acquire a relatively stable and precise attitude estimation. Unlike the direct SC combination method with a predefined weight as recommended in previous work, we propose an involvement of each SC measurement in the Kalman filter to enable a dynamic weight adjustment. Intensive experiments are further carried out to assess the HUGG-01, which demonstrate that the error level of HUGG-01 is entirely within the design requirement, i.e., the resulting KBR pointing variations are well controlled within 1 mrad (pitch), 5 mrad (roll) and 1 mrad (yaw). Moreover, comparisons with the official JPL-V04 attitude product demonstrate an equivalent performance in the low-to-middle spectrum, with even a slightly lower noise level (in the high spectrum) than JPL-V04. Further analysis on KBR range-rate residuals and gravity recovery on January 2019 indicates that, i.e., RMS of the difference (HUGG-01 minus JPL-V04) for the range rate is less than 3.234x10(-8) m/s, and the amplitude of geoid height difference is approximately 0.5 cm. Both differences are below the sensitivity of the state-of-the-art satellite gravity mission, demonstrating a good agreement between HUGG-01 and JPL-V04.
引用
收藏
页数:24
相关论文
共 50 条
  • [31] Joint inversion of GNSS and GRACE/GRACE-FO data for terrestrial water storage changes in Southwest China
    Yang X.
    Yuan L.
    Jiang Z.
    Tang M.
    Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 2024, 53 (05): : 813 - 822
  • [32] Data-Driven Gap Filling and Spatio-Temporal Filtering of the GRACE and GRACE-FO Records
    Gauer, Louis-Marie
    Chanard, Kristel
    Fleitout, Luce
    JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH, 2023, 128 (05)
  • [33] Interpretable Machine Learning for Thermospheric Mass Density Modeling Using GRACE/GRACE-FO Satellite Data
    Pan, Qian
    Xiong, Chao
    Gao, Shunzu
    Chen, Zhou
    Smirnov, Artem
    Xu, Chunyu
    Huang, Yuyang
    SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS, 2025, 23 (03):
  • [34] Making the Best Use of GRACE, GRACE-FO and SMAP Data Through a Constrained Bayesian Data-Model Integration
    Mehrnegar, Nooshin
    Schumacher, Maike
    Jagdhuber, Thomas
    Forootan, Ehsan
    WATER RESOURCES RESEARCH, 2023, 59 (09)
  • [35] Data-driven multi-step self-de-aliasing approach for GRACE and GRACE-FO data processing
    Abrykosov, Petro
    Murbock, Michael
    Hauk, Markus
    Pail, Roland
    Flechtner, Frank
    GEOPHYSICAL JOURNAL INTERNATIONAL, 2023, 232 (02) : 1006 - 1030
  • [36] Comparing GRACE-FO KBR and LRI Ranging Data with Focus on Carrier Frequency Variations
    Mueller, Vitali
    Hauk, Markus
    Misfeldt, Malte
    Mueller, Laura
    Wegener, Henry
    Yan, Yihao
    Heinzel, Gerhard
    REMOTE SENSING, 2022, 14 (17)
  • [37] The Water Cycle of the Baltic Sea Region From GRACE/GRACE-FO Missions and ERA5 Data
    Boulahia, Ahmed Kamel
    Garcia-Garcia, David
    Vigo, M. Isabel
    Trottini, Mario
    Sayol, Juan-Manuel
    FRONTIERS IN EARTH SCIENCE, 2022, 10
  • [38] Hydrological Cycle in the Arabian Sea Region from GRACE/GRACE-FO Missions and ERA5 Data
    Boulahia, Ahmed Kamel
    Garcia-Garcia, David
    Trottini, Mario
    Sayol, Juan-Manuel
    Vigo, M. Isabel
    REMOTE SENSING, 2024, 16 (19)
  • [39] Impact of Attitude Model, Phase Wind-Up and Phase Center Variation on Precise Orbit and Clock Offset Determination of GRACE-FO and CentiSpace-1
    Yuan, Junjun
    Zhou, Shanshi
    Hu, Xiaogong
    Yang, Long
    Cao, Jianfeng
    Li, Kai
    Liao, Min
    REMOTE SENSING, 2021, 13 (13)
  • [40] Groundwater Storage Estimation in the Saskatchewan River Basin Using GRACE/GRACE-FO Gravimetric Data and Machine Learning
    Hamdi, Mohamed
    El Alem, Anas
    Goita, Kalifa
    ATMOSPHERE, 2025, 16 (01)