联合EMD-HD和小波分解的GNSS坐标时间序列降噪分析

doi:10.11947/j.AGCS.2022.20210175

测绘学报 ›› 2022, Vol. 51 ›› Issue (9): 1881-1889.doi: 10.11947/j.AGCS.2022.20210175

联合EMD-HD和小波分解的GNSS坐标时间序列降噪分析

杨兵, 杨志强, 田镇, 陈祥

长安大学地质工程与测绘学院, 陕西西安 710054

收稿日期:2021-04-14 修回日期:2021-12-20 发布日期:2022-09-29
通讯作者: 杨志强 E-mail:yang_gps@chd.edu.cn
作者简介:杨兵(1994—),男,博士生,研究方向为GNSS数据处理与地壳形变监测。E-mail:bing.yang@chd.edu.cn
基金资助:
国家自然科学基金（42174054）；大地测量与地球动力学国家重点实验室开放基金（SKLGED2021-4-3）；武汉大学地球空间环境与大地测量教育部重点实验室开放基金（20-01-05）；长安大学中央高校基本科研业务费专项资金（300102261104）

Denoising analysis of GNSS coordinate time series by combining EMD-HD and wavelet decomposition

YANG Bing, YANG Zhiqiang, TIAN Zhen, CHEN Xiang

College of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China

Received:2021-04-14 Revised:2021-12-20 Published:2022-09-29
Supported by:
The National Natural Science Foundation of China (No. 42174054); The State Key Laboratory of Geodesy and Earth's Dynamics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences (No. SKLGED2021-4-3); The Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University (No. 20-01-05); The Fundamental Research Funds for the Central Universities, Chang'an University (No. 300102261104)

摘要/Abstract

摘要： 针对经验模态分解（empirical mode decomposition，EMD）在GNSS坐标时间序列的降噪过程中存在筛选准则的选取和模态混叠效应等问题，本文引入Hausdorff距离（Hausdorff distance，HD）筛选准则并结合小波分解（wavelet decomposition，WD），提出EMD-HD&WD算法。通过对我国大陆构造环境监测网络149个GNSS测站的垂向坐标时间序列降噪处理，分别利用复合指标T值、测站的速度不确定度和闪烁噪声振幅验证算法的可靠性和普适性。结果显示：HD优于现有的筛选准则；EMD-HD&WD算法对测站的速度不确定度和闪烁噪声振幅的平均改正率均为88.4%。分析表明，本文算法能够有效识别和剔除噪声并且改善EMD的模态混叠效应，提高GNSS垂向坐标时间序列的模型精度。

关键词: GNSS坐标时间序列, 经验模态分解, 小波分解, Hausdorff距离, 速度不确定度

Abstract: This study proposes the EMD-HD&WD algorithm to solve the limitations of screening rules and mode mixing in the denoising analysis of the GNSS coordinate time series when using empirical mode decomposition (EMD). The improved algorithm introduces the Hausdorff distance (HD) as a screening criterion for EMD and combines wavelet decomposition (WD). The reliability and universality of EMD-HD&WD algorithm were verified by 149 GNSS vertical time series in the crustal movement observation network of China. The results show that the HD is better than the existing screening criteria; the average correction rates of the EMD-HD&WD for the velocity uncertainty and the amplitude of flicker noise of GNSS stations are 88.4%. The algorithm can effectively identify the observational noise, reduce the mode aliasing of EMD, and improve the model accuracy of GNSS vertical coordinate time series.

Key words: GNSS coordinate time series, empirical mode decomposition, wavelet decomposition, Hausdorff distance, velocity uncertainty

中图分类号:

P228

杨兵, 杨志强, 田镇, 陈祥. 联合EMD-HD和小波分解的GNSS坐标时间序列降噪分析[J]. 测绘学报, 2022, 51(9): 1881-1889.

YANG Bing, YANG Zhiqiang, TIAN Zhen, CHEN Xiang. Denoising analysis of GNSS coordinate time series by combining EMD-HD and wavelet decomposition[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(9): 1881-1889.

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联合EMD-HD和小波分解的GNSS坐标时间序列降噪分析

Denoising analysis of GNSS coordinate time series by combining EMD-HD and wavelet decomposition

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