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云南地区GPS基准站噪声模型分析
引用本文:管雅慧,王坦,胡顺强,杨振宇. 云南地区GPS基准站噪声模型分析[J]. 全球定位系统, 2020, 45(2): 68-73. DOI: DOI:10.13442/j.gnss.1008-9268.2020.02.011
作者姓名:管雅慧  王坦  胡顺强  杨振宇
作者单位:首都师范大学地球空间信息科学与国际化示范学院,北京100048;首都师范大学资源环境与旅游学院,北京100048;中国地震台网中心,北京100045
基金项目:国家自然科学基金(41672192)。
摘    要:以云南地区陆态网27个全球定位系统(GPS)基准站在2011-2017年不同时间跨度的观测数据为例,使用赤池信息量和贝叶斯信息量估计准则(AIC/BIC)对解算结果进行分析,从而确定其最优有色噪声模型.结果表明,不同时间跨度基准站各坐标分量上噪声特性主要体现为白+闪烁噪声(WN+FN)、幂律噪声(PL)模型组合.部分基准站在北向和垂向的最优噪声模型会随着观测时间的累积而改变,PL模型所占比例有所下降,WN+FN模型所占比例有所上升.当时间跨度大于5 a时,基准站噪声模型的稳定性显著提高.随着坐标时间序列积累时长的增加,未知噪声分量出现的可能性也相应提高.

关 键 词:陆态网  GPS时间序列  时间跨度  噪声分析  最优噪声模型

Analysis of noise model of GPS reference stations in Yunnan area
GUAN Yahui,WANG Tan,HU Shunqiang,YANG Zhenyu. Analysis of noise model of GPS reference stations in Yunnan area[J]. Gnss World of China, 2020, 45(2): 68-73. DOI: DOI:10.13442/j.gnss.1008-9268.2020.02.011
Authors:GUAN Yahui  WANG Tan  HU Shunqiang  YANG Zhenyu
Affiliation:1.College of Geospatial Information Science and Technology,Capital Normal University,Beijing 100048,China2.College of Resource Environment and Tourism,Capital Normal University,Beijing 100048,China3.China Earthquake Networks Center,Beijing 100045,China
Abstract:Taking the observation data of 27 GPS reference stations in Yunnan State Land Network at different time spans from 2011 to 2017 as examples, the Achievement and Bayesian Information Estimation Criterion (AIC/BIC) criterion is used to analyze the solution results. And so as to determine its optimal colored noise model. The results show that the optimal noise model for each coordinate component of the reference station at different time spans is mainly combination of white+flicker noise (WN+FN) and Power-law (PL) noise models. The optimal noise models of some reference stations in the north and vertical directions will change with the accumulation of observation time, and the proportion of PL models will decrease. While the proportion of WN+FN model will increase. When the time span is greater than 5a, the stability of the reference station noise model is significantly improved. As the accumulation time of the coordinate time series increases, the probability of the occurrence of unknown noise components increases accordingly. 
Keywords:CMONOC  GPS time series  time series span  noise analysis  optimal noise model
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