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陆态网络GPS速度场噪声模型分析

龚一航 郑博文 王华 吴希文

广东工业大学学报2025,Vol.42Issue(2):97-102,6.
广东工业大学学报2025,Vol.42Issue(2):97-102,6.

陆态网络GPS速度场噪声模型分析

An Analysis of Noise Model in Land-based Network GPS Velocity Field

龚一航 1郑博文 1王华 1吴希文1

作者信息

  • 1. 广东工业大学 土木与交通工程学院,广东 广州 510006
  • 折叠

摘要

Abstract

GPS observations are influenced by external factors,resulting in various types of noise in their time series.It is necessary to use appropriate noise model to estimate the station’s velocity accuracy.Spectral analysis method and maximum likelihood estimation method are used to perform optimal noise model analysis on the time series of 259 GPS continuous stations in the China Continental Crustal Movement Observation Network.Three consecutive days of observation data are extracted from the annual continuous station data as simulated campaign stations.The main noise models of the continuous stations of China Crustal Movement Observation Network of China are white noise plus flicker noise resulted from spectral analysis method.The difference in velocity calculated using the optimal noise model and the FOGMEx model is not significant,and the speed uncertainty is 1.5±0.7 times(E),1.0±0.5 times(N),and 1.8±1.1 times(U)of the FOGMEx model,respectively.For the simulated campaign station,the velocity uncertainty obtained from the original continuous station covariance matrix is 0.8±0.2 times(E),1.0±0.2 times(N),and 0.9±0.2 times(U),respectively,compared with the velocity uncertainty estimated by the noise model established by reducing its degree of freedom and there is no significant difference in velocity.Therefore,for the majority of real campaign stations in China’s mainland,reducing the degrees of freedom(i.e.,assuming the number of observed values at campaign stations equals the number of years of observation)is suggested to estimate their uncertainty.

关键词

GPS/时间序列/噪声模型/速度不确定性

Key words

GPS/time series/noise mode/velocity uncertainty

分类

天文与地球科学

引用本文复制引用

龚一航,郑博文,王华,吴希文..陆态网络GPS速度场噪声模型分析[J].广东工业大学学报,2025,42(2):97-102,6.

基金项目

国家重点研发计划项目(2017YFC1500501) (2017YFC1500501)

国家自然科学基金资助项目(42274001) (42274001)

广东工业大学学报

1007-7162

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