测绘学报 ›› 2023, Vol. 52 ›› Issue (3): 357-366.doi: 10.11947/j.AGCS.2023.20210590

• 大地测量学与导航 • 上一篇    下一篇

卫星激光测距站分级与GNSS卫星轨道精度校核

赵春梅1,2, 王磊1,2, 何正斌1,2   

  1. 1. 中国测绘科学研究院, 北京 100036;
    2. 北京房山人卫激光国家野外科学观测研究站, 北京 100036
  • 收稿日期:2021-11-01 修回日期:2022-10-17 发布日期:2023-04-07
  • 作者简介:赵春梅(1971-),女,博士,研究员,研究方向为卫星轨道确定,空间目标激光测距及数据处理。E-mail:zcm@casm.ac.cn
  • 基金资助:
    国家自然科学基金(42174033);国家重点研发计划项目(2020YFB0505801)

Satellite laser ranging station classification for GNSS satellite orbit accuracy validation

ZHAO Chunmei1,2, WANG Lei1,2, HE Zhengbin1,2   

  1. 1. Chinese Academy of Sueveying and Mapping, Beijing 100036, China;
    2. Beijing Fangshan Satellite Laser Ranging National Observation and Research Station, Beijing 100036, China
  • Received:2021-11-01 Revised:2022-10-17 Published:2023-04-07
  • Supported by:
    The National Natural Science Foundation of China (No. 42174033);The National Key Research and Development Program of China(No. 2020YFB0505801)

摘要: GNSS卫星轨道是实现导航定位等位置服务的基础,对卫星轨道精度的精确评估关系到服务的精度与可靠性。卫星激光测距技术是评估卫星轨道精度的独立外部检核手段,由于SLR站系统水平不一,导致数据质量差异较大,因此合理选用高性能SLR站是精确评估卫星轨道的关键。本文利用聚类分析方法,依据国际激光网发布的近10 a全球SLR站性能评估报告,选择观测总圈数、LAGEOS标准点RMS值和系统短期偏差3个参数作为测站分级评估指标,将全球SLR站进行分级。在此基础上,对2020年所有参与国际激光联测的GNSS卫星的事后精密轨道进行了精度校核。结果表明,SLR站水平与数据质量密切相关,利用模糊C-均值聚类算法可有效对全球SLR测站进行分级,Ⅰ、Ⅱ和Ⅲ级测站占比分别为28%、51%和21%;采用不同级站观测数据得到的检核结果存在明显差异,基于Ⅰ级站数据的校轨残差均值的绝对值和标准差总体小于Ⅱ和Ⅲ级测站,3种GNSS卫星轨道精度在R、T、N方向上的差异不明显,对应分量的RMS值之间的较差均处于毫米级水平。

关键词: 卫星激光测距, 模糊聚类, GNSS, 轨道精度校核

Abstract: GNSS satellite orbit is the basis of the realization of navigation, positioning and other location services. The precision of satellite orbit accuracy evaluation is related to the accuracy and reliability of services. Satellite laser ranging technology is a reliable external check method to evaluate the satellite orbit accuracy. Due to the different level of SLR station system, the data quality is greatly different. The reasonable selection of high performance SLR station is the key to accurately evaluate the satellite orbit. In this study, based on the performance evaluation report of global SLR stations published by the International Laser Network in the last 10 years, three parameters including total number of observations, LAGEOS standard point RMS value and system short-term deviation are selected as the evaluation indexes to grade the global SLR stations. On this basis, the precision of all GNSS satellites participating in the international Laser joint survey in 2020 is checked. The results show that the level of SLR stations is closely related to the data quality. The fuzzy C-means clustering algorithm can effectively classify the global SLR stations, and the proportion of class Ⅰ, class Ⅱ and class Ⅲ stations is 28%, 51% and 21%, respectively. There exist significant differences among the GNSS satellite orbit accuracy obtained by using SLR data of different class stations. The mean absolute value and standard deviation of residual based on class I station are generally smaller than that of class Ⅱ and class Ⅲ stations. According to the GLONASS, BDS and Galileo satellite orbits residuals checked by class Ⅰ station data, the statistical analysis of the residual components in the RTN coordinate system shows that the difference of the three GNSS satellites' orbit accuracy in all directions is not obvious, and the difference between the RMS values of the corresponding components is at mm level.

Key words: satellite laser ranging, fuzzy clustering, GNSS, orbit accuracy validation

中图分类号: