东北陆态网坐标时序有色噪声及环境负载分析

利用Hector软件解算我国东北地区16个陆态网络连续站近10 a的时间序列观测数据,获取连续站坐标残差时间序列数据,进而确定最优噪声模型,最终得出基于有色噪声(CN)以及环境负载改正后的速度场.结果表明：东北地区陆态网络坐标时间序列数据中主要存在白噪声(WN)、闪烁噪声(FN)与幂律噪声(PL);北(N)和天顶(U)方向的最优噪声模型为WN+FN;E方向的最优噪声模型均为WN+PL.在顾及CN及环境负载的影响下,东北地区陆态网络基于ITRF14框架下在N方向上运动的平均速率为-13.003 mm/a,东(E)方向上运动的平均速率为27.020 mm/a,U方向上运动的平均速率为0.528 mm/a,整体呈隆升趋势.     

环境负载模型效应位移序列可靠性分析

以12个IGS基准站为研究对象,通过格林函数方法对基于QLM模型的地表环境负载(大气压力、土壤湿度、非潮汐海洋、积雪深度)引起的测站位移序列进行可靠性分析。结合粗差分析、主分量分析、噪声特性分析等对位移序列进行特征分析,结果表明基于QLM计算的负载效应序列是比较可靠的,在对GPS坐标时间序列修正过程中,能较好避免不必要的二次误差的引入。此外,地表环境负载对测站的位移影响甚至达到cm级,对测站垂向位移影响更为明显;且负载位移时间序列存在明显的周期性波动,对高精度的地球动力学研究负载环境效应的影响不可忽略,应施加负载改正,为去除坐标时间序列中虚假的非线性变化提供参考。     

华北区域GNSS基准站高程时间序列的非线性变化分析

基于陆态网络全球卫星导航系统（GNSS）观测成果,采用功率谱分析法和最小二乘方法,以华北地区为例,研究了区域基准站高程时间序列的非线性变化特征,并分析了不同环境负载的影响.结果表明,GNSS基准站高程方向存在显著的周年和半年周期特征,且周年特征要显著于半周年特征.位于不同地区的基准站的振幅和相位存在差异,华北平原南部地区的周年振幅要大于北部地区,整体上华北地区周年变化在秋季时节振幅达到最大.不同环境负载效应对华北GNSS高程位移的影响不一致,利用三种环境负载修正GNSS序列后,水文负载的修正效果最好,非潮汐大气负载次之,非潮汐海洋负载修正结果不理想.      

环境负载对区域GPS基准站时间序列的影响分析

基于1999-2011年中国地壳运动观测网络(CMONOC)及2007-2012年武汉市连续运行卫星定位服务系统(WHCORS)的观测数据,联合中国及周边35个IGS基准站数据,采用GAMIT软件解算,获得了ITRF2008框架下的GPS基准站坐标时间序列.然后采用QOCA计算了环境负载位移,并利用其对GPS时间序列进行改正.研究结果表明环境负载造成的中国区域基准站位移呈现显著的区域性特征,东北、华北、华中区域变化较为一致且较大,西南区域基准站(KUNM)垂直方向的负载位移均方根(RMS)最大值达6.09 mm.通过对改正前后的数据进行时间序列分析,认为环境负载改正能够削弱中国区域大多数GPS基准站(约70%)垂直及水平东方向位移时间序列的非线性变化,其加权均方根(WRMS)减小量最大达1.5 mm,但是对于水平北方向坐标时间序列的改善作用不明显.     

中国区域IGS基准站坐标时间序列噪声模型建立与分析

选取ITRF2005框架下中国区域(包括台湾地区)11个IGS基准站1995-2010年的坐标时间序列,采用不同噪声模型组合对它们进行噪声分析,并计算大气压负载、非潮汐海洋负载、积雪深度及土壤湿度负载对测站位移的影响,得到地表质量负载改正前后各测站分量的最优噪声模型。结果表明,中国区域IGS基准站的噪声模型存在多样性,且各分量具有不同的噪声特性,主要表现为闪烁噪声+白噪声和带通幂律噪声+白噪声。噪声模型与地表质量负载及其测站速度、速度不确定度之间的定量分析表明地表质量负载会造成测站的噪声特性变化,主要表现为带通及随机漫步噪声特征。不同复杂噪声模型对测站线性速度及不确定度会产生一定影响,少数测站高程分量差异甚至超过1 mm/a。     

基于IGS连续跟踪站的GPS高程时间序列分析

对全球分布的IGS连续跟踪站GPS高程分量时间序列,进行了小波多分辨率分析,发现各台站高程时间序列大都存在着季节性变化,这种以半周年项和周年项为主的季节性变化是由多种地球物理现象引起的,我们从多个方面分析了原因,并着重分析了大气压强的影响。利用分析的结果讨论了地壳垂直变化的规律,得出地球存在以半年和周年为周期的整体性扩张与收缩振荡运动,同时南北半球的变化规律存在差异的结论。     

基于ARMA模型的GPS基准站坐标时间序列分析

由于利用GAMIT/GLOBK软件对连续运行多年的GPS基准站数据进行处理的原始结果存在一定的噪声,本文利用ARMA模型对GPS基准站坐标进行时间序列分析,其中采用Pandit-Wu方法确定ARMA模型的阶数.试验结果表明,采用Pandit-Wu方法能够准确地确定ARMA模型的阶数,并且基于ARMA的时间序列有效地消除了一定量的噪声,让GPS基准站随着时间的变化规律与趋势更加明显,说明ARMA模型在GPS基准站坐标时间序列分析中剔除噪声及突显变化量与趋势具有良好的效果.     

内蒙古陆态网络坐标时间序列噪声分析及速度场修正

利用中国地震局全球卫星导航系统(GNSS)数据产品服务平台获取内蒙古自治区境内15个陆态网络连续站2010-06—2021-06的观测数据,通过GAMIT/GLOBK软件、HECTOR软件解算得到去奇异值后的坐标时间序列,最后结合贝叶斯信息量准则(BIC)数值分析确定最优噪声模型:内蒙古自治区坐标时间序列在东(E)方向的最优模型为白噪声+闪烁噪声 (WN+FN),在北(N)和天顶(U)方向的最优噪声模型为白噪声+幂律噪声(WN+PL). 采用最佳噪声模型对速度场进行修正,在ITRF14框架下,内蒙古地区陆态网络连续站的平均运动速率为30.653 mm/a,运动方向为26°57′51″SEE;垂直方向上平均运动速率为0.792 mm/a.      

顾及有色噪声影响的甘肃境内CMONOC基准站坐标时间序列分析

针对甘肃省境内19个CMONOC基准站坐标时间序列结果,采用极大似然估计法(MLE)探讨了各基准站的最优噪声模型,确定了基准站的速度场,并分析了甘肃省地壳运动状况.研究结果表明:甘肃省境内CMONOC基准站各坐标分量噪声特性存在较大的差异,"白噪声+闪烁噪声(WN+FN)"为最优噪声模型,能够更好地描述基准站坐标时间序...     

基于独立分量法的新疆GNSS时间序列共模误差分析CSCD

共模误差(CME)是区域连续全球卫星导航系统(GNSS)网中的主要误差来源之一.针对GNSS时间序列具有非高斯分布特征,基于二阶统计量的主成分分析(PCA)难以准确提取出CME分量问题,采用具有高阶统计量的独立分量分析(ICA)对CME进行提取.以2011—2018年新疆区域GNSS坐标时间序列为例,将PCA滤波效果进行对比验证,分析了CME对GNSS坐标时间序列的影响,并对CME序列进行周期分析.结果表明:前6个独立分量包含CME分量,这可能与卫星轨道、地表质量负荷和时钟误差有关,ICA滤波后东(N)、北(E)、天顶(U)三个方向的均方根(RMS)值分别降低31.83%、32.29%、35.49%,速度不确定度分别降低44.14%、38.49%、43.32%,各测站的周期项振幅较滤波前更一致,有效地剔除了CME,提高了坐标时间序列的精度.     

Monument-antenna effects on GPS coordinate time series with application to vertical rates in Antarctica

We examine the electromagnetic coupling of a GPS antenna–monument pair in terms of its simulated affect on long GPS coordinate time series. We focus on the Earth and Polar Observing System (POLENET) monument design widely deployed in Antarctica and Greenland in projects interested particularly in vertical velocities. We base our tests on an absolute robot calibration that included the top ~0.15 m of the monument and use simulations to assess its effect on site coordinate time series at eight representative POLENET sites in Antarctica over the period 2000.0–2011.0. We show that the neglect of this calibration would introduce mean coordinate bias, and most importantly for velocity estimation, coordinate noise which is highly sensitive to observation geometry and hence site location and observation period. Considering only sub-periods longer than 2.5 years, we show vertical site velocities may be biased by up to ±0.4 mm/year, and biases up to 0.2 mm/year may persist for observation spans of 8 years. Changing between uniform and elevation-dependent observation weighting alters the time series but does not remove the velocity biases, nor does ambiguity fixing. The effect on the horizontal coordinates is negligible. The ambiguities fixed series spectra show noise between flicker and random walk with near-white noise at the highest frequencies, with mean spectral indices (frequencies <20 cycles per year) of approximately −1.3 (uniform weighting) and −1.4 (elevation-dependent weighting). While the results are likely highly monument specific, they highlight the importance of accounting for monument effects when analysing vertical coordinate time series and velocities for the highest precision and accuracy geophysical studies.     

Assessment of second- and third-order ionospheric effects on regional networks: case study in China with longer CMONOC GPS coordinate time series

Higher-order ionospheric (HOI) delays are one of the principal technique-specific error sources in precise global positioning system analysis and have been proposed to become a standard part of precise GPS data processing. In this research, we apply HOI delay corrections to the Crustal Movement Observation Network of China’s (CMONOC) data processing (from January 2000 to December 2013) and furnish quantitative results for the effects of HOI on CMONOC coordinate time series. The results for both a regional reference frame and global reference frame are analyzed and compared to clarify the HOI effects on the CMONOC network. We find that HOI corrections can effectively reduce the semi-annual signals in the northern and vertical components. For sites with lower semi-annual amplitudes, the average decrease in magnitude can reach 30 and 10 % for the northern and vertical components, respectively. The noise amplitudes with HOI corrections and those without HOI corrections are not significantly different. Generally, the HOI effects on CMONOC networks in a global reference frame are less obvious than the results in the regional reference frame, probably because the HOI-induced errors are smaller in comparison to the higher noise levels seen when using a global reference frame. Furthermore, we investigate the combined contributions of environmental loading and HOI effects on the CMONOC stations. The largest loading effects on the vertical displacement are found in the mid- to high-latitude areas. The weighted root mean square differences between the corrected and original weekly GPS height time series of the loading model indicate that the mass loading adequately reduced the scatter on the CMONOC height time series, whereas the results in the global reference frame showed better agreements between the GPS coordinate time series and the environmental loading. When combining the effects of environmental loading and HOI corrections, the results with the HOI corrections reduced the scatter on the observed GPS height coordinates better than the height when estimated without HOI corrections, and the combined solutions in the regional reference frame indicate more preferred improvements. Therefore, regional reference frames are recommended to investigate the HOI effects on regional networks.     

Nontectonic signals in reprocessed continuous GPS position time series of CMONOC

The nearly nine-year continuous GPS data collected since 1 March 1999 from the Crustal Motion Observation Network of China(CMONOC) were consistently analyzed.Most of the nonlinear movements in the cumulative position time series pro-duced by CMONOC data center disappeared;and more accurate vertical terms and tectonic signals were extracted.Displacements caused by atmospheric pressure loading,nontidal ocean loading,soil moisture mass loading,and snow cover mass loading using the National Centers for Environmental Prediction(NCEP) Reanalysis I/II models and Estimation of the Circulation and Climate of the Ocean(ECCO) data can explain most of the vertical annual terms at many stations,while only parts can be explained at Lhasa and southern coastal sites,indicating that there are some deformation mechanisms that are still unknown or not modeled accurately.The remarkable differences in vertical position time series for short-baseline sites reveal that GPS stations can be greatly affected by lo-cal factors;and attention should be paid when explaining observed GPS velocity vectors.     

Nontectonic signals in reprocessed continuous GPS position time series of CMONOC

The nearly nine-year continuous GPS data collected since 1 March 1999 from the Crustal Motion Observation Network of China (CMONOC) were consistently analyzed. Most of the nonlinear movements in the cumulative position time series produced by CMONOC data center disappeared; and more accurate vertical terms and tectonic signals were extracted. Displacements caused by atmospheric pressure loading, nontidal ocean loading, soil moisture mass loading, and snow cover mass loading using the National Centers for Environmental Prediction (NCEP) Reanalysis I/II models and Estimation of the Circulation and Climate of the Ocean (ECCO) data can explain most of the vertical annual terms at many stations, while only parts can be explained at Lhasa and southern coastal sites, indicating that there are some deformation mechanisms that are still unknown or not modeled accurately. The remarkable differences in vertical position time series for short-baseline sites reveal that GPS stations can be greatly affected by local factors; and attention should be paid when explaining observed GPS velocity vectors.     

GPS坐标时间序列分析研究

近20年来,以GPS为代表的空间大地测量技术观测精度不断提高,已累积了丰富的、高精度、全球覆盖的坐标时间序列数据。这些数据为研究不同时空尺度下的各类地球物理现象提供了重要的数据支撑和大地测量几何约束。然而,由于GPS坐标时间序列中同时包含了各类“信号”和“噪声”,而且噪声来源复杂,信号类型多样,水平和高程分量上信号与噪声的表现形式差异较大。如何从原始序列中提取可靠的“信号”、分离出“误差”是目前地学界研究的热点和难点之一。     

地表质量负载对格陵兰岛区域GPS站点坐标时序特征的影响

选取ITRF2008框架下格陵兰岛区域12个GPS站2013年1月-2016年12月期间的日解坐标时间序列作为研究对象,并利用极大似然估计分析地表质量负载改正前后各站点的噪声特性、速度场及周期项振幅。结果表明：站点最优噪声模型主要为白噪声+幂律噪声与白噪声+闪烁噪声,地表质量负载形变修正GPS坐标时序后,明显增加U方向闪烁噪声的成分,平均降低其速度约0.36 mm/a,对水平方向影响较小;同时分别降低高程方向44.1%、14.2%的1 a项、0.5 a项振幅,相反,却增加了水平方向的周期项振幅。     

顾及有色噪声的ETS对GPS坐标时间序列影响分析

以12个GPS站12年的坐标序列为研究对象.采用Kashyap信息准则（KIC）噪声模型估计准则对四种组合噪声特性进行估计,探讨慢滑移（ETS）现象对GPS站坐标时间序列的影响,结果表明:ETS引起了GPS站坐标序列模型的变化,E、N方向分量噪声模型占比与U分量模型占比差异较大,可能造成噪声模型的错误估计;ETS后的站速度及其不确定度相比ETS前站速度及其不确定度均有增加,且在U分量表现明显;特殊地理位置的测站可进行标记研究,尽量减少地震运动带来的不利影响,为地壳运动研究提供有价值的参考资料．      

Comparative analysis of different environmental loading methods and their impacts on the GPS height time series

Three different environmental loading methods are used to estimate surface displacements and correct non-linear variations in a set of GPS weekly height time series. Loading data are provided by (1) Global Geophysical Fluid Center (GGFC), (2) Loading Model of Quasi-Observation Combination Analysis software (QLM) and (3) our own daily loading time series (we call it OMD for optimum model data). We find that OMD has the smallest scatter in height across the selected 233 globally distributed GPS reference stations, GGFC has the next smallest variability, and QLM has the largest scatter. By removing the load-induced height changes from the GPS height time series, we are able to reduce the scatter on 74, 64 and 41 % of the stations using the OMD models, the GGFC model and QLM model respectively. We demonstrate that the discrepancy between the center of earth (CE) and the center of figure (CF) reference frames can be ignored. The most important differences between the predicted models are caused by (1) differences in the hydrology data from the National Center for Atmospheric Research (NCEP) vs. those from the Global Land Data Assimilation System (GLDAS), (2) grid interpolation, and (3) whether the topographic effect is removed or not. Both QLM and GGFC are extremely convenient tools for non-specialists to use to calculate loading effects. Due to the limitation of NCEP reanalysis hydrology data compared with the GLDAS model, the GGFC dataset is much more suitable than QLM for applying environmental loading corrections to GPS height time series. However, loading results for Greenland from GGFC should be discarded since hydrology data from GLDAS in this region are not accurate. The QLM model is equivalent to OMD in Greenland and, hence, could be used as a complement to the GGFC product to model the load in this region. We find that the predicted loading from all three models cannot reduce the scatter of the height coordinate for some stations in Europe.