测绘学报 ›› 2025, Vol. 54 ›› Issue (6): 982-994.doi: 10.11947/j.AGCS.2025.20240451

• 大地测量学与导航 • 上一篇    下一篇

基于GNSS钟差参数先验信息的超快速轨道钟差估计方法

王潜心1(), 胡超2,3(), 程彤1   

  1. 1.中国矿业大学环境与测绘学院,江苏 徐州 221116
    2.安徽理工大学空间信息与测绘工程学院,安徽 淮南 232001
    3.空间基准全国重点实验室,陕西 西安 710054
  • 收稿日期:2024-11-05 修回日期:2025-05-12 出版日期:2025-07-14 发布日期:2025-07-14
  • 通讯作者: 胡超 E-mail:wqx@cumt.edu.cn;chaohu2014gnss@163.com
  • 作者简介:王潜心(1980—),男,博士,教授,研究方向为卫星大地测量数据处理。E-mail:wqx@cumt.edu.cn
  • 基金资助:
    国家重点研发计划(2020YFA0713502);国家自然科学基金(42404015);广西科技基地和人才专项(桂科AD25069103)

A method for satellite ultra-rapid orbit and clock offset estimation based on the prior information of the GNSS clock parameters

Qianxin WANG1(), Chao HU2,3(), Tong CHENG1   

  1. 1.School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
    2.School of Spatial Information and Geomatics Engineering, Anhui University of Science and Technology, Huainan 232001, China
    3.State Key Laboratory of Spatial Datum, Xi'an 710054, China
  • Received:2024-11-05 Revised:2025-05-12 Online:2025-07-14 Published:2025-07-14
  • Contact: Chao HU E-mail:wqx@cumt.edu.cn;chaohu2014gnss@163.com
  • About author:WANG Qianxin (1980—), male, PhD, professor, majors in satellite geodesy data processing. E-mail: wqx@cumt.edu.cn
  • Supported by:
    The National Key Research and Development Program of China(2020YFA0713502);The National Natural Science Foundation of China(42404015);Guangxi Science and Technology Base and Talent Special Project(桂科AD25069103)

摘要:

多系统超快速卫星轨道与钟差产品正被广泛应用于实时与近实时等快速位置服务中。但受参数处理时效性与数据质量限制,超快速精密定轨模型中未顾及轨道钟差参数相关性影响,且无法充分利用星载原子钟信息。本文提出一种基于GNSS钟差参数先验信息的超快速轨道钟差产品估计方法。首先,固定卫星轨道参数,利用相位时间差分算法,单历元滑动解算GNSS钟差;然后,构建卫星钟差短时预报模型,提取星载原子钟先验信息,模型化卫星钟差参数;最后,约束定轨方程中卫星钟差参数,建立超快速轨道钟差估计增强模型。试验结果表明,轨道钟差联合处理中参数间存在显著相关性,且在固定轨道参数条件下,可实现较传统超快速卫星钟差产品估计精度提升30.9%~50.7%的效果;构建卫星钟差参数先验约束,可提升超快速轨道毫米级精度,且钟差解算精度可至少提升了32.9%;静态PPP结果显示,本文估计的多系统超快速轨道钟差参数分别提升了E、N与U方向定位精度9.9%、16.9%与9.3%。因此,本文提出的轨道钟差解算方法可有效改善多系统超快速轨道钟差产品性能,为高质量快速定位服务提供支撑。

关键词: GNSS, 超快速钟差, 先验信息, 轨道钟差参数, 参数估计

Abstract:

GNSS ultra-rapid orbit and clock products are widely used in the area of real-time and near-real-time fast location-based services. However, due to the restriction of time-consuming and observations quality in the parameters estimation, the correlation between orbit and clock offset parameters in ultra-rapid determination is not considered. In addition, the merits of satellite onboard clock information is ignored. Therefore, in this research, an improved ultra-rapid orbit and clock estimation method is proposed based on the prior constraint on the GNSS clock parameters. First, the time-difference carrier phase algorithm is used to epoch-wisely update the satellite clock offset by fixing satellite orbit. Second, the short-term prediction model of clock offset is constructed to extract the prior information and model the satellite onboard atomic clock parameters. Third, the augmented model of ultra-rapid orbit and clock offset is constructed by the constraint of satellite onboard clock parameters in orbit determination equation. According to the experiment results, it is indicated that the significant correlation among orbit and clock offset parameters is presented, in which the accuracy of ultra-rapid clock offset can be improved with 30.9%~50.7%, compared with the traditional ultra-rapid clock products by fixing the orbit parameters. Meanwhile, the millimeter-level and at least 32.9% for orbit and clock offset accuracy improvements can be obtained by the prior constraint on clock parameters. Additionally, the performances of static PPP solution are respectively improved with 9.9%, 16.9% and 9.3% for E, N and U directions, compared with the traditional ultra-rapid orbit and clock products. Therefore, the proposed GNSS satellite orbit and clock offset method can effectively improve the performances of ultra-rapid products, which will further provide supporting for the high-quality PNT services.

Key words: GNSS, ultra-rapid satellite clock offset, prior information, orbit and clock offset parameters, parameters estimation

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