摘要
引入一种改进的集合经验模式分解方法(improved ensemble empirical mode decomposition,IEEMD)进行多路径误差的建模。与EEMD方法相比较,IEEMD方法可以有效地克服模态分量数目不一致和分解不彻底等问题,并将原始序列分解为不同尺度的模态分量。同时,考虑到不同模态分量中高斯白噪声的能量密度与平均周期之积为常数,设计一种自动选择尺度与重构的方法,用于模态分量的选择与重构,进而构建GPS多路径误差模型。在此基础上,采用恒星日滤波技术,进行邻近周日GPS坐标序列中多路径误差的实时削弱。实验结果表明,采用同样的尺度选择方法和恒星日滤波技术,使用IEEMD方法可以得到比EEMD方法精度更高的GPS坐标序列。
In this article,a new method called IEEMD(improved ensemble empirical mode decomposition)is introduced to build the correction of multipath error.Compared to EEMD(ensemble empirical mode decomposition),the new method can effectively solve the problem of model mixing and incomplete decomposition.It can also decompose the original coordinate sequence into different scales of modal components.The product of Gaussian white noise energy density and the average period is constant.Taking this condition into account,a new method is designed for automatic selection of scale and reconstruction to build the multipath error model.We can use it to correct the later coordinate series by the first day’s multipath model by the reason of the strong correlation between two successive days.The experiment results show that IEEMD can get more accurate coordinate sequence than EEMD,based on the same way of scale selection and stellar day filtering.To a certain extent,this study solidifies the theoretical basis of GPS high\|precision real\|time dynamic deformation monitoring.
作者
张成龙
刘超
赵兴旺
邓永春
ZHANG Chenglong;LIU Chao;ZHAO Xingwang;DENG Yongchun(School of Geodesy and Geomatics,Anhui University of Science and Technology,168 Taifeng Street,Huainan 232001,China)
出处
《大地测量与地球动力学》
CSCD
北大核心
2018年第10期1021-1026,共6页
Journal of Geodesy and Geodynamics
基金
国家自然科学基金(41404004
41474026
41704008)
安徽理工大学2017年研究生创新基金(2017CX2125)~~
关键词
GPS
经验模式分解
多路径误差
集合经验模式分解
动态变形监测
GPS
empirical mode decomposition(EMD)
multipath error
ensemble empirical mode decomposition(EEMD)
dynamic deformation monitoring