测绘学报 ›› 2018, Vol. 47 ›› Issue (10): 1337-1345.doi: 10.11947/j.AGCS.2018.20170616

• 大地测量学与导航 • 上一篇    下一篇

全球GPS测站垂向周年变化统计改正模型的建立

傅彦博, 孙付平, 朱新慧, 刘婧   

  1. 信息工程大学, 河南 郑州 450001
  • 收稿日期:2017-11-05 修回日期:2018-03-23 出版日期:2018-10-20 发布日期:2018-10-24
  • 通讯作者: 孙付平 E-mail:sun.fp@163.com
  • 作者简介:傅彦博(1993-),男,硕士生,研究方向为导航时空基准。E-mail:fybxrlb1993@163.com
  • 基金资助:
    国家自然科学基金(41374027;41674042)

Establishment of Statistical Correction Model for Vertical Annual Variations of Global GPS Stations

FU Yanbo, SUN Fuping, ZHU Xinhui, LIU Jing   

  1. Information Engineering University, Zhengzhou 450001, China
  • Received:2017-11-05 Revised:2018-03-23 Online:2018-10-20 Published:2018-10-24
  • Supported by:
    The National Natural Science Foundation of China (Nos. 41374027;41674042)

摘要: 对GPS测站坐标进行非线性变化的研究和建模,是削弱测站非线性运动的有效途径。由于导致测站坐标非线性变化的机制具有多样性和复杂性,目前还未能建立一个包含多种机制影响的理论改正模型来削弱测站的非线性运动。本文基于全球近500个实测的GPS测站垂向坐标残差时间序列,研究发现了测站垂向坐标周年项的全球分布规律,并分别针对南北半球构建了两个基于实测数据的周年变化统计改正模型。试验表明,本文提出的统计改正模型能削弱全球大部分GPS测站30%~50%的垂向坐标残差。

关键词: 非线性变化, 周年项, 全球分布规律, 统计改正模型, 垂向坐标时间序列

Abstract: The research and modeling of nonlinear variations of GPS stations coordinates are effective ways to weaken nonlinear motion of the stations. However,due to the diversity and complexity of nonlinear variations of stations' coordinates,the theoretical correction model contained multiple mechanisms has not been established to weaken the nonlinear motion of GPS stations.In this paper,global distribution regularity of annual terms of vertical coordinates of stations was discovered based on the measured vertical coordinates residuals of nearly 500 GPS stations,two statistical correction models of annual variations based on measured data were respectively constructed for the northern and southern hemispheres.The experiments show that the statistical correction model proposed in this paper can weaken 30%~50% vertical coordinate residuals of most GPS stations in the world.

Key words: nonlinear variations, annual term, global distribution regularity, statistical correction model, vertical coordinates time series

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