Toggle Main Menu Toggle Search

Open Access padlockePrints

An Improved Stacking Filtering for Extracting the Common-Mode Errors on GNSS Coordinate Time Series in Shanxi

Lookup NU author(s): Dr Chuang Song

Downloads


Licence

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

© 2022, Czech Academy of Sciences. All rights reserved.The presence of common mode error (CME) in the coordinate displacement time series of the Global Navigation Satellite System (GNSS) affects geophysical studies using GNSS observations. In order to investigate the effect of CME on the time series in GNSS networks in Shanxi, this paper proposes an improved superposition filtering method by introducing single-day solution accuracy, correlation coefficient, and spherical distance between stations as weights. The filtering effect is evaluated using the GNSS data in Shanxi. By using the improved stacking filtering method, the root mean square (RMS) values for N, E, U are reduced by approximately 27.8 %, 29.0 %, and 46.0 %, respectively. And compared to the traditional stacking filter, our improved method can achieve better results with CME extraction. We investigate the CME spatial-temporal characteristics and its relationship with environmental loading. The results show that the CME between stations decreases as the distance between stations increases. In addition, we analyze the effect of CME on the noise component and velocity estimates. Results show that removing the CME refines the velocity and leads to a significant reduction in the magnitude of noise, indicating that the CME is dominated by the flicker noise in Shanxi Province.


Publication metadata

Author(s): Li W, Li X, Zang J, Sui Z, Song C, Xie X, Huang Y, Zhang T, Yan H

Publication type: Article

Publication status: Published

Journal: Acta Geodynamica et Geomaterialia

Year: 2022

Volume: 19

Issue: 4

Pages: 291-306

Online publication date: 16/12/2022

Acceptance date: 06/12/2022

Date deposited: 31/01/2023

ISSN (print): 1214-9705

ISSN (electronic): 2336-4351

Publisher: Czech Academy of Sciences

URL: https://doi.org/10.13168/AGG.2022.0014

DOI: 10.13168/AGG.2022.0014


Altmetrics

Altmetrics provided by Altmetric


Funding

Funder referenceFunder name
0JR10RA271
2019M660091XB
2020A-037
2022NGCM01
21JR7RA317
1A50190117
42204006
41861061
41930101
E01Z790201/2021kf07

Share