Potential Contributors to Common Mode Error in Array GPS Displacement Fields in Taiwan Island

Cuilin Kuang,Xuemin Xing,Xiaojun Ma,Bin Liu,Wujiao Dai

doi:10.3390/rs13214221

Abstract

The existence of the common mode error (CME) in the continuous global navigation satellite system (GNSS) coordinate time series affects geophysical studies that use GNSS observations. To understand the potential contributors of CME in GNSS networks in Taiwan and their effect on velocity estimations, we used the principal component analysis (PCA) and independent component analysis (ICA) to filter the vertical coordinate time series from 44 high-quality GNSS stations in Taiwan island in China, with a span of 10 years. The filtering effects have been evaluated and the potential causes of the CME are analyzed. The root-mean-square values decreased by approximately 14% and 17% after spatio-temporal filtering using PCA and ICA, respectively. We then discuss the relationship between the CME sources obtained by ICA and the environmental loads. The results reveal that the independent displacements extracted by ICA correlate with the atmospheric mass loading (ATML) and land water storage mass loading (LWS) of Taiwan in terms of both its amplitude and phase. We then use the white noise plus power law noise model to quantitatively estimate the noise characteristics of the pre- and post-filtered coordinate time series based on the maximum likelihood estimation criterion. The results indicate that spatio-temporal filtering reduces the amplitude of the PL and the periodic terms in the GPS time series.

Highlights

Continuous global navigation satellite system (GNSS) networks have been widely used in the fields of geodesy and geophysics
Geophysical signals can be difficult to separate from noise and unknown error sources because they are hidden in a detrended residual coordinate time series
To intuitively compare the amplitude of each component, the corresponding spatial response is usually divided by the maximum absolute value and scaled to a variation inresponse is usually divided by the maximum absolute value and scaled to a variation terval of − 100%~100%, where the scaled amount is multiplied by the corresponding interval of −100% ∼ 100%, where the scaled amount is multiplied by the corresponding temporal components

Summary

Introduction

Continuous global navigation satellite system (GNSS) networks have been widely used in the fields of geodesy and geophysics. Previous studies have identified that a spatially correlated error generally exists in regional networks, caused by the reference frame, satellites orbits, ocean tide correction models, and other unknown errors. This is usually referred to as the common mode error (CME) [6,7,8,9,10,11]. The presence of this error affects the accuracy of the station coordinates and velocity solutions, and conceals many weak and transient signals in a coordinate time series (e.g., deep magma motion, fault motion)

Methods

Results

Discussion

Conclusion