共查询到19条相似文献，搜索用时 677 毫秒
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对于GPS区域网坐标序列中普遍存在的共模误差(CME),常规方法是利用堆栈空间滤波去除,通常假设CME是空域不变的;而主成分分析法(PCA)和Karhunen-Loeve(KLE)展开法都是把随时间变化的台站网时间序列分解成时间域的主分量和空间域的特征分量,不限制CME的本征。因此,本文尝试结合PCA和KLE方法对GPS区域网坐标序列进行空间滤波,并通过对美国中加州Carrizo平原的一个连续运行GPS监测网进行分析,表明PCA/KLE法可有效提取共模误差,提高站点坐标精度,增强空间滤波的稳健性。 相似文献
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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. 相似文献
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采用GPS技术对矿区地表移动进行动态监测,针对长距离差分动态定位精度受多因素残余误差的影响,利用主成分分析法(PCA)进行空间滤波,分离区域站点相关的共模误差,以提高坐标序列精度。为进一步分析矿区地表移动受多源影响,采用解决盲信号分离问题的独立分量分析法(ICA),提取各测站形变信息。通过实例与仿真分析,结果表明,利用PCA空间滤波可提高3个分量坐标序列精度分别为46.1%,71.0%及36.8%;基于特征矩阵联合似对角化算法(JADE)进行ICA分解,能够实现各测站形变信息的提取。 相似文献
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顾及有色噪声影响的CGCS2000下我国CORS站速度估计 总被引：6，自引：2，他引：4
研究基于计算获取的CGCS2000(中国大地坐标系统2000)下我国国家CORS(全球导航卫星系统连续运行参考站)网1999年至2009年坐标时间序列,首先采用主成分空间滤波方法(PCA)提取CGCS2000框架下国家CORS网坐标时间序列中公共误差(common mode errors,CME)的时空特性;其次,采用功率谱分析方法分析空间滤波后的国家CORS站坐标残差时间序列的噪声性质,采用最大似然法定量估计坐标残差时间序列中的有色噪声分量;最后,采用加权最小二乘法评定顾及不同噪声影响的CGCS2000框架下的国家CORS网年速度估值和实际精度.研究结果表明:采用空间滤波可提高CGCS2000框架下国家CORS网成果的精确性和可靠性,空间滤波后北、东和高方向的平均坐标重复性相对于滤波前分别减小了26%、22%和46%,滤波后国家CORS站高度方向平均振幅减少近64%.在CGCS2000框架下我国CORS站坐标时间序列中白噪声不是噪声的主要成分,白噪声、闪烁噪声和随机漫步噪声的噪声性质是国家CORS站坐标时间序列的基本特征;我国CORS站有色噪声在水平方向和高度方向表现出一定的规律性,顾及有色噪声的速度误差估值比只考虑白噪声的速度误差估值一般大2～6倍,速度估值偏差一般在2%～10%. 相似文献
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利用小波工具剔除噪声的思想对全球部分GPS测站坐标残差序列进行应用试验。通过选取特定的阈值和小波基函数,成功提取出GPS测站坐标残差序列的一些非线性周期规律,对于进一步深入研究GPS测站坐标非线性变化规律有重要意义。 相似文献
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针对传统主成分分析(PCA)忽视测站各坐标分量之间相关性的问题,提出了一种小波去噪和多方向主成分分析(WD-MPCA)组合的方法. 该方法弥补了传统PCA的缺陷,与经验模态分解和主成分分析(EMD-PCA)组合方法及小波去噪和主成分分析(WD-PCA)组合方法相比,WD-MPCA组合方法精度最高. 经WD-MPCA组合方法去噪后,其平均中误差分别为0.83 mm、0.85 mm和8.30 mm,比原始坐标残差时间序列的平均中误差分别降低了81.14%、81.91%和40.37%. WD-MPCA组合方法充分考虑了各测站不同分量之间的相关性,可以有效去除信号中的高频随机白噪声(WN)和低频有色噪声(CN),这对高频全球卫星导航系统(GNSS)技术的实际应用和理论发展具有重要的意义. 相似文献
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欧洲地区共模误差提取及分析 总被引：1，自引：1，他引：0
针对跨度较长时间序列共模误差噪声特征研究较少,选择空间滤波的方法对较长时间序列进行分析以满足参考框架建立的需要。选取欧洲地区58个IGS基准站2001—2011年的坐标时间序列,采用区域叠加滤波法、分区区域叠加滤波法和相关系数加权叠加滤波法求取共模误差,并以滤波后时间序列相关系数和残差时间序列标准差为标准对其进行对比分析;进而,利用极大似然估计的方法对每个区域共模误差及滤波前后坐标时间序列进行噪声分析。结果表明:分区区域叠加滤波法最适合欧洲地区共模误差的提取;共模误差主要成分是闪烁噪声,也包含白噪声、随机漫步噪声等;当时间序列长度较长时,N、E方向受共模误差影响较小,可忽略,U方向受共模误差影响较大,需要考虑。 相似文献
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Spatiotemporal filtering of regional GNSS network’s position time series with missing data using principle component analysis 总被引：5，自引：0，他引：5
The existing spatiotemporal analysis methods suppose that the involved time series are complete and have the same data interval. However missing data inevitably occur in the position time series of Global Navigation Satellite Systems networks for many reasons. In this paper, we develop a modified principal component analysis to extract the Common Mode Error (CME) from the incomplete position time series. The principle of the proposed method is that a time series can be reproduced from its principle components. The method is equivalent to the method of Dong et al. (J Geophys Res 111:3405–3421, 2006) in case of no missing data in the time series and to the extended ‘stacking’ approach under the assumption of a uniformly spatial response. The new method is first applied to extract the CME from the position time series of the Crustal Movement Observation Network of China (CMONOC) over the period of 1999–2009 where the missing data occur in all stations with the different gaps. The results show that the CMEs are significant in CMONOC. The size of the first principle components for the North, East and Up coordinates are as large as 40, 41 and 37 % of total principle components and their spatial responses are not uniform. The minimum amplitudes of the first eigenvectors are only 41, 15 and 29 % for the North, East and Up coordinate components, respectively. The extracted CMEs of our method are close to the data filling method, and the Root Mean Squared error (RMS) values computed from the differences of maximum CMEs between two methods are only 0.31, 0.52 and 1.55 mm for North, East and Up coordinates, respectively. The RMS of the position time series is greatly reduced after filtering out the CMEs. The accuracies of the reconstructed missing data using the two methods are also comparable. To further comprehensively test the efficiency of our method, the repeated experiments are then carried out by randomly deleting different percentages of data at some stations. The results show that the CMEs can be extracted with high accuracy at the non missing-data epochs. And at the missing-data epochs, the accuracy of extracted CMEs has a strong dependence on the number of stations with missing data. 相似文献
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GPS时间序列的空间滤波可以提高观测数据的信噪比，有利于获取更高精度的地壳形变信息。区域叠加滤波算法的空间滤波结果随着测站数和空间尺度不同而不同，不利于研究GPS时间序列中的形变信息。为了削弱区域叠加滤波受空间尺度的影响，提出一种不以空间尺度作为约束条件，同时引入相关系数和距离因子的区域叠加滤波算法。采用2010—2017年中国区域260个GPS连续观测站的时间序列展开空间滤波方法的研究，计算结果表明，对比相关性区域叠加滤波算法，考虑GPS时间序列之间的相关系数和距离因子更有利于提取GPS时间序列中的共模误差，且受空间尺度的影响较小。对比3种不同距离因子的区域叠加滤波算法，可知引入距离反比的空间滤波算法可实现更优的空间滤波。采用该方法空间滤波后可使GPS时间序列残差降低30%~40%，GPS速度场精度提高30%~40%。此算法实现了更优的GPS形变场估计，为研究中国区域的地壳运动和其动力学机制提供了可靠的数据基础。 相似文献
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Spatiotemporal filtering for regional GPS network in China using independent component analysis 总被引：2，自引：0，他引：2
Removal of the common mode error (CME) is a routine procedure in postprocessing regional GPS network observations, which is commonly performed using principal component analysis (PCA). PCA decomposes a network time series into a group of modes, where each mode comprises a common temporal function and corresponding spatial response based on second-order statistics (variance and covariance). However, the probability distribution function of a GPS time series is non-Gaussian; therefore, the largest variances do not correspond to the meaningful axes, and the PCA-derived components may not have an obvious physical meaning. In this study, the CME was assumed statistically independent of other errors, and it was extracted using independent component analysis (ICA), which involves higher-order statistics. First, the ICA performance was tested using a simulated example and compared with PCA and stacking methods. The existence of strong local effects on some stations causes significant large spatial responses and, therefore, a strategy based on median and interquartile range statistics was proposed to identify abnormal sites. After discarding abnormal sites, two indices based on the analysis of the spatial responses of all sites in each independent component (east, north, and vertical) were used to define the CME quantitatively. Continuous GPS coordinate time series spanning \(\sim \)4.5 years obtained from 259 stations of the Tectonic and Environmental Observation Network of Mainland China (CMONOC II) were analyzed using both PCA and ICA methods and their results compared. The results suggest that PCA is susceptible to deriving an artificial spatial structure, whereas ICA separates the CME from other errors reliably. Our results demonstrate that the spatial characteristics of the CME for CMONOC II are not uniform for the east, north, and vertical components, but have an obvious north–south or east–west distribution. After discarding 84 abnormal sites and performing spatiotemporal filtering using ICA, an average reduction in scatter of 6.3% was achieved for all three components. 相似文献
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GPS时间序列与强震预测研究 总被引：3，自引：0，他引：3
应用经验正交函数(EOF)分析方法，对中国大陆连续观测的基准站水平位移时间序列进行分析。通过对1999年3月份以来GPS1000周至1258周的原始时间序列的EOF分析、时间序列中除去长期位移速率后的EOF分析、及强震前半年时间段内的时间序列的EOF分析，研究强震前中国大陆水平位移场的时空演化特征及与强震发生的关系。 相似文献
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Vertical deformations from homogeneously processed GRACE and global GPS long-term series 总被引：3，自引：1，他引：2
Volker Tesmer Peter Steigenberger Tonie van Dam Torsten Mayer-Gürr 《Journal of Geodesy》2011,85(5):291-310
Temporal variations in the geographic distribution of surface mass cause surface displacements. Surface displacements derived
from GRACE gravity field coefficient time series also should be observed in GPS coordinate time series, if both time series
are sufficiently free of systematic errors. A successful validation can be an important contribution to climate change research,
as the biggest contributors to mass variability in the system Earth include the movement of oceanic, atmospheric, and continental
water and ice. In our analysis, we find that if the signals are larger than their precision, both geodetic sensor systems
see common signals for almost all the 115 stations surveyed. Almost 80% of the stations have their signal WRMS decreased,
when we subtract monthly GRACE surface displacements from those observed by GPS data. Almost all other stations are on ocean
islands or small peninsulas, where the physically expected loading signals are very small. For a fair comparison, the data
(79 months from September 2002 to April 2009) had to be treated appropriately: the GPS data were completely reprocessed with
state-of-the-art models. We used an objective cluster analysis to identify and eliminate stations, where local effects or
technical artifacts dominated the signals. In addition, it was necessary for both sets of results to be expressed in equivalent
reference frames, meaning that net translations between the GPS and GRACE data sets had to be treated adequately. These data
sets are then compared and statistically analyzed: we determine the stability (precision) of GRACE-derived, monthly vertical
deformation data to be ~1.2 mm, using the data from three GRACE processing centers. We statistically analyze the mean annual
signals, computed from the GPS and GRACE series. There is a detailed discussion of the results for five overall representative
stations, in order to help the reader to link the displayed criteria of similarity to real data. A series of tests were performed
with the goal of explaining the remaining GPS–GRACE residuals. 相似文献
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为探讨四川盆地在汶川地震前后地壳运动的规律,本文对2006年3月至2012年9月四川12个连续运行参考站（Continuously Operating Reference Stations, CORS）6年多的观测资料进行了详细的处理和分析。通过比较震前震后CORS站运动的相似性和差异性发现：由于震后形变的影响,震后第一主成分(Principle Component First, PC1)的贡献率下降20%~40%;震后多站的速度场发生了明显的变化,突出表现在PIXI,CHDU,MYAN等站,YAAN,QLAI站处于闭锁状态;盆地垂直分量的周年振幅在震前一年偏大,震后逐年减小。以上发现表明汶川地震可能改变了四川盆地原有的运动特性。 相似文献
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系统分析了改进随机模型和改进函数模型两类GPS基线解算模型的优缺点,在此基础上,提出了一种基于序列平均的高精度GPS基线解算模型,即采用动态单历元技术进行静态基线解算,充分利用多路径效应的低频特性,采用小波变化理论,对坐标序列进行多路径效应的去除,提取低频残差项进行序列平均,得到基线向量解。同时,以动态坐标序列为依据,对出现粗差历元或者卫星进行处理,有效弥补了仅采用残差序列进行粗差判断的不足,提高了基线解算的精度和可靠性。实验表明,新模型可以更为有效地削弱多路径效应的影响,而且对于较短的观测时间尤为突出;结合坐标序列和残差序列,能更为有效地进行粗差的探测和去除,提高基线解的精度和可靠性。 相似文献
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2000中国大地坐标系统（China Geodetic Coordinate System 2000,CGCS2000）的建立和维持主要依赖于GPS技术,不利于保障国家时空信息安全。中国北斗卫星导航系统（BeiDou navigation satellite system,BDS）提供亚太区域服务,可满足中国及周边地区高精度定位导航应用需求,对建立和维持国家大地坐标参考框架具有重要意义。研究利用已建成的北斗基准站网观测数据,实现基于BDS技术、并与国际地球参考框架（International Terrestrial Reference Frame,ITRF）一致的国家大地坐标参考框架,为今后国家级和全球性北斗坐标参考框架（BeiDou Terrestrial Reference Frame,BTRF）的建立和维持提供理论基础和方法支撑。初步计算结果表明,积累2 a以上的观测数据,利用单独BDS数据可以获得与GPS精度相当的水平速度场,精度约为2~3 mm/a。基于单独BDS数据,测站残差平面和高程的重复性分别可优于0.8 cm和1.7 cm。利用BDS数据已可监测到测站高程方向的季节性变化。此外,还对单独BDS与GPS数据计算的坐标可能存在的与经纬度相关的系统误差进行了分析。总体来说,目前的北斗系统可满足建立和维持中国cm级大地坐标框架的需求。 相似文献
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PCA空间滤波在高频GPS定位中的应用研究 总被引：2，自引：0，他引：2
利用主成分分析法(PCA)对高频GPS时间序列进行空间滤波,并结合Karhunen-Loeve展开法(KLE)对其结果进行判定,可有效地提取共模误差,提高单历元定位精度。通过对四川GPS连续观测网的计算分析表明,PCA方法可较好地减弱区域共模误差,并能准确地反映共模误差的空间分布,且精度优于传统的堆栈法,这对高频GPS技术的应用和发展具有重要意义。 相似文献