测绘学报 ›› 2026, Vol. 55 ›› Issue (2): 287-300.doi: 10.11947/j.AGCS.2026.20250361

• 大地测量学与导 • 上一篇    

顾及星敏感器安装矩阵校正的GRACE-FO姿态数据处理研究

梁磊1,2,3(), 王长青4,5(), 黄令勇3, 黄志勇3, 于瑶瑶6, 钟敏7, 闫易浩8, 穆庆禄9   

  1. 1.滁州学院地理信息与旅游学院,安徽 滁州 239099
    2.安徽省实景地理环境重点实验室,安徽 滁州 239009
    3.智能空间信息国家级重点实验室,北京 100029
    4.中国科学院精密测量科学与技术创新研究院,湖北 武汉 430077
    5.华中科技大学国家精密重力测量科学中心,湖北 武汉 430074
    6.北京市遥感信息研究所,北京 100124
    7.中山大学遥感科学与技术学院,广东 珠海 519082
    8.马克斯-普朗克引力物理研究所(阿尔伯特-爱因斯坦研究所),德国 汉诺威 30167
    9.江苏海洋大学海洋技术与测绘学院,江苏 连云港 222005
  • 收稿日期:2025-09-04 修回日期:2025-11-10 发布日期:2026-03-13
  • 通讯作者: 王长青 E-mail:lianglei@chzu.edu.cn;whiggsdkd@asch.whigg.ac.cn
  • 作者简介:梁磊(1990—),男,博士,副教授,研究方向为物理大地测量、卫星重力。 E-mail:lianglei@chzu.edu.cn
  • 基金资助:
    国家自然科学基金(42204091; 42174103);安徽省高校自然科学研究重点项目(2024AH051436);智慧地球重点实验室基金(KF2023YB02-04);滁州学院科研启动基金(2023qd08);国家精密重力测量科学中心开放课题(NGL-2025-010)

GRACE-FO attitude data determination with consideration of star camera alignment matrix calibration

Lei LIANG1,2,3(), Changqing WANG4,5(), Lingyong HUANG3, Zhiyong HUANG3, Yaoyao YU6, Min ZHONG7, Yihao YAN8, Qinglu MU9   

  1. 1.School of Geographic Information and Tourism, Chuzhou University, Chuzhou 239099, China
    2.Anhui Provincial Key Laboratory of Physical Geographic Environment, Chuzhou 239009, China
    3.National Key Laboratory of Intelligent Spatial Information, Beijing 100029, China
    4.Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430077, China
    5.National Gravitation Laboratory, Huazhong University of Science and Technology, Wuhan 430074, China
    6.Capital Institute of Geographic Information, Beijing 100124, China
    7.School of Geospatial Engineering and Science, Sun Yat-Sen University, Zhuhai 519082, China
    8.Max-Planck-Institut für Gravitationsphysik (Albert-Einstein-Institute), Hannover 30167, Germany
    9.School of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang 222005, China
  • Received:2025-09-04 Revised:2025-11-10 Published:2026-03-13
  • Contact: Changqing WANG E-mail:lianglei@chzu.edu.cn;whiggsdkd@asch.whigg.ac.cn
  • About author:LIANG Lei (1990—), male, PhD, associate professor, majors in physical geodesy and satellite gravity. E-mail: lianglei@chzu.edu.cn
  • Supported by:
    The National Natural Science Founding of China(42204091; 42174103);The Key Project of Natural Science Research in Universities of Anhui Province(2024AH051436);Funded by Key Laboratory of Smart Earth(KF2023YB02-04);Chuzhou University Research Initiation Fund Project(2023qd08);National Gravitation Laboratory(NGL-2025-010)

摘要:

如何获取高精度的姿态数据是重力卫星载荷数据处理的重要研究内容。GRACE-FO的每颗卫星均搭载了3颗星敏感器和1个陀螺仪,融合这两类载荷的测量数据是获得高精度姿态数据的重要途径。本文首先根据星敏感器测量噪声具有各向异性的特点,建立了星敏感器安装矩阵标定算法;其次,建立了星敏感器低频误差处理方法,使用滑动平均方法抑制低频误差;然后,基于Gibbs矢量建立了四元数改正量和陀螺仪偏差改正量为状态向量的间接Kalman滤波算法;最后,使用GRACE-FO Leve-l1A数据进行验证,并分析其对时变重力场的影响。结果表明,以其中1个星敏感器为基准,校正另外两颗星敏感器安装矩阵时,解算的卫星姿态差异较小,经过星敏感器安装矩阵校正后,可以降低姿态数据在1个轨道周期(CPR)处的低频误差。根据建立的星敏感器低频误差处理策略,可以较好地压制30 CPR频段内的星敏感器低频误差。对于星敏感器和陀螺仪融合,相较于JPL结果,本文解算的姿态数据为0.000 5~0.1 Hz,具有更低的噪声,充分发挥了载荷最大性能。对时变重力场模型反演的影响,从反演的时变重力场的阶方差和等效水高差异上看,基于不同姿态数据解算的时变重力场模型精度基本一致,目前姿态数据精度的提升对时变重力场模型精度影响较小。

关键词: GRACE-FO, 卫星姿态, 星敏感器低频误差, 安装矩阵校正, 间接Kalman滤波

Abstract:

The acquisition of high-precision attitude data is a crucial research aspect in the processing of gravity satellite payload raw data. Each GRACE-FO satellite is equipped with three star cameras and a gyroscope to measure the satellite's attitude data. The fusion of these two types of data is an important approach to obtain high-precision attitude data. Firstly, we establish a calibration algorithm for the star cameras installation matrix according to the anisotropic noise of star camera measurements. Secondly, a low-frequency error processing strategy for star cameras is developed, utilizing a moving average method to suppress low-frequency errors. Then, an indirect Kalman filtering algorithm is proposed, with the quaternion correction based on the Gibbs vector and gyroscope bias correction as state vectors. Finally, the GRACE-FO Level-1A data is used for validation and analysis. The computational results show that using different star cameras as references to calibrate the installation matrix of the other star cameras yields only minor differences in the derived satellite attitude and the low-frequency errors at the 1 CPR frequency band in the attitude data are significantly reduced. The established low-frequency error processing strategy for star cameras can effectively suppress low-frequency errors within the 30 CPR frequency band. For the fusion of star cameras and gyroscope data, compared to the JPL results, the attitude data calculated in this paper reduces noise in the 0.000 5~0.1 Hz frequency band, demonstrating that the fusion fully exploits the instruments'maximum performance. Regarding the impact on time-variable gravity field recovery, both the degree variances of the recovered gravity fields and the equivalent water height differences show that the accuracies of the time-variable gravity models derived from different attitude datasets are essentially identical. At the current level, further improvements in attitude data accuracy have only a minor effect on enhancing the precision of time-variable gravity field models.

Key words: GRACE-FO, satellite attitude, star camera low-frequency error, installation matrix calibration, indirect Kalman filter

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