谢树明, 潘鹏飞, 周晓慧. 大空间尺度GPS网共模误差提取方法研究[J]. 武汉大学学报 ( 信息科学版), 2014, 39(10): 1168-1173.
引用本文: 谢树明, 潘鹏飞, 周晓慧. 大空间尺度GPS网共模误差提取方法研究[J]. 武汉大学学报 ( 信息科学版), 2014, 39(10): 1168-1173.
XIE Shuming, PAN Pengfei, ZHOU Xiaohui. Research on Common Mode Error Extraction Method for Large-Scale GPS Network[J]. Geomatics and Information Science of Wuhan University, 2014, 39(10): 1168-1173.
Citation: XIE Shuming, PAN Pengfei, ZHOU Xiaohui. Research on Common Mode Error Extraction Method for Large-Scale GPS Network[J]. Geomatics and Information Science of Wuhan University, 2014, 39(10): 1168-1173.

大空间尺度GPS网共模误差提取方法研究

Research on Common Mode Error Extraction Method for Large-Scale GPS Network

  • 摘要: 基于全球分布均匀且时间跨度大于10a的138个IGS基准站坐标时间序列分析了大空间尺度GPS网基准站坐标时间序列之间的相关性发现部分测站之间的距离超过5 000km时仍存在较显著的相关性针对目前共模误差提取方法存在的不足引入相关系数作为权重因子改进了区域叠加滤波算法 并利用IGS基准站坐标时间序列验证了此方法 结果表明改进后的相关系数加权叠加滤波算法能够有效地提取大空间尺度GPS网坐标时间序列中的共模误差.

     

    Abstract: Based on 138evenl y distributed  IGS coordinate  time  series  spanning more than 10years site -to-site  coefficents  in  lar ge scale GPS network were anal yzed.Their  site -to-site  coefficients  indicate si gnificant  corelationshi p even when the between-site  distance more than 5 000km.Thereforethis paper  proposes  a new method introducing coefficients  as weight  factor  to  calculate  common mode errorand  it  improved  the  correlation-based spatial  filterin g techni que.Time series  from global  and regional  networks were used  to verif y this new method.The results  show that  this  improved coefficientbased spatial  filterin g techni que overcomes  the  spatial  scale  limit  and effectivel y extracts  common mode error  of GPS coordinates  time  series.

     

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