scholarly journals Positioning Performance of BDS Observation of the Crustal Movement Observation Network of China and Its Potential Application on Crustal Deformation

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3353 ◽  
Author(s):  
Xiaoning Su ◽  
Guojie Meng ◽  
Haili Sun ◽  
Weiwei Wu
Keyword(s):  
Time Series ◽  
Crustal Deformation ◽  
Potential Application ◽  
Flicker Noise ◽  
Crustal Movement ◽  
Movement Observation ◽  
North East ◽  
Noise Characteristics ◽  
Observation Network ◽  
Position Time Series

The Crustal Movement Observation Network of China (CMONOC) has begun receiving BeiDou Navigation Satellite System (BDS) observations since 2015, and accumulated more than 2.5 years of data. BDS observations has been widely applied in many fields, and long-term continuous data provide a new strategy for the study of crustal deformation in China. This paper focuses on the evaluation of BDS positioning performance and its potential application on crustal deformation in CMONOC. According to the comparative analysis on multipath delay (MPD) and signal to noise ratio (SNR) between BDS and GPS data, the data quality of BDS is at the same level with GPS measurements in COMONC. The spatial distribution of BDS positioning accuracy evaluated as the root mean square (RMS) of daily residual position time series on horizontal component is latitude-dependent, declining with the increasing of station latitude, while the vertical one is randomly distributed in China. The mean RMS of BDS position residual time series is 7 mm and 22 mm on horizontal and vertical components, respectively, and annual periodicity in position time series can be identified by BDS data. In view of the accuracy of BDS positioning, there are no systematic differences between GPS and BDS results. Based on time series analysis with data volume being 2.5 years, the noise characteristics of BDS daily position time series is time-correlated and corresponding noise is white plus flicker noise model, and the derived mean RMS of the BDS velocities is 1.2, 1.5, and 4.1 mm/year on north, east, and up components, respectively. The imperfect performance of BDS positioning relative to GPS is likely attributed to the relatively low accuracy of BDS ephemeris, and the sparse amount of MEO satellites distribution in the BDS constellation. It is expectable to study crustal deformation in CMONOC by BDS with the gradual maturity of its constellation and the accumulation of observations.

Spatiotemporal noise in GPS position time-series from Crustal Movement Observation Network of China

2018 ◽  
Vol 216 (3) ◽  
pp. 1560-1577 ◽  
Author(s):  
Wei Wang ◽  
Xuejun Qiao ◽  
Dijin Wang ◽  
Zhengsong Chen ◽  
Pengfei Yu ◽  
...  
Keyword(s):  
Time Series ◽  
Crustal Movement ◽  
Movement Observation ◽  
Observation Network ◽  
Position Time Series ◽  
Spatiotemporal Noise

scholarly journals Signal Extraction from GNSS Position Time Series Using Weighted Wavelet Analysis

2020 ◽  
Vol 12 (6) ◽  
pp. 992 ◽  
Author(s):  
Kunpu Ji ◽  
Yunzhong Shen ◽  
Fengwei Wang
Keyword(s):  
Time Series ◽  
Wavelet Analysis ◽  
Satellite System ◽  
Signal Extraction ◽  
Average Error ◽  
North East ◽  
Observation Network ◽  
Position Time Series ◽  
Global Navigation Satellite ◽  
Gnss Position Time Series

The daily position time series derived by Global Navigation Satellite System (GNSS) contain nonlinear signals which are suitably extracted by using wavelet analysis. Considering formal errors are also provided in daily GNSS solutions, a weighted wavelet analysis is proposed in this contribution where the weight factors are constructed via the formal errors. The proposed approach is applied to process the position time series of 27 permanent stations from the Crustal Movement Observation Network of China (CMONOC), compared to traditional wavelet analysis. The results show that the proposed approach can extract more exact signals than traditional wavelet analysis, with the average error reductions are 13.24%, 13.53% and 9.35% in north, east and up coordinate components, respectively. The results from 500 simulations indicate that the signals extracted by proposed approach are closer to true signals than the traditional wavelet analysis.

The Investigations on Crustal Deformation in China under ITRF97 Plate Model using Data of “Crustal Movement Observation Network in China”

2002 ◽  
Vol 45 (3) ◽  
pp. 337-344 ◽  
Author(s):  
Yang FU ◽  
Wen-Yao ZHU ◽  
Xiao-Ya WANG ◽  
Wu-Xing DUAN ◽  
Xian-Bing WU ◽  
...  
Keyword(s):  
Crustal Deformation ◽  
Crustal Movement ◽  
Plate Model ◽  
Movement Observation ◽  
Observation Network ◽  
Using Data

scholarly journals Effects of Spatiotemporal Filtering on the Periodic Signals and Noise in the GPS Position Time Series of the Crustal Movement Observation Network of China

2018 ◽  
Vol 10 (9) ◽  
pp. 1472 ◽  
Author(s):  
Peng Yuan ◽  
Weiping Jiang ◽  
Kaihua Wang ◽  
Nico Sneeuw
Keyword(s):  
Time Series ◽  
Velocity Field ◽  
Colored Noise ◽  
Environmental Loading ◽  
Movement Observation ◽  
Observation Network ◽  
Uncertainty Estimates ◽  
Position Time Series ◽  
Periodic Signals ◽  
Gps Velocity Field

Analysis of Global Positioning System (GPS) position time series and its common mode components (CMC) is very important for the investigation of GPS technique error, the evaluation of environmental loading effects, and the estimation of a realistic and unbiased GPS velocity field for geodynamic applications. In this paper, we homogeneously processed the daily observations of 231 Crustal Movement Observation Network of China (CMONOC) Continuous GPS stations to obtain their position time series. Then, we filtered out the CMC and evaluated its effects on the periodic signals and noise for the CMONOC time series. Results show that, with CMC filtering, peaks in the stacked power spectra can be reduced at draconitic harmonics up to the 14th, supporting the point that the draconitic signal is spatially correlated. With the colored noise suppressed by CMC filtering, the velocity uncertainty estimates for both of the two subnetworks, CMONOC-I (≈16.5 years) and CMONOC-II (≈4.6 years), are reduced significantly. However, the CMONOC-II stations obtain greater reduction ratios in velocity uncertainty estimates with average values of 33%, 38%, and 54% for the north, east, and up components. These results indicate that CMC filtering can suppress the colored noise amplitudes and improve the precision of velocity estimates. Therefore, a unified, realistic, and three-dimensional CMONOC GPS velocity field estimated with the consideration of colored noise is given. Furthermore, contributions of environmental loading to the vertical CMC are also investigated and discussed. We find that the vertical CMC are reduced at 224 of the 231 CMONOC stations and 170 of them are with a root mean square (RMS) reduction ratio of CMC larger than 10%, confirming that environmental loading is one of the sources of CMC for the CMONOC height time series.

scholarly journals Analysis of Noise and Velocity in GNSS EPN-Repro 2 Time Series

2021 ◽  
Vol 13 (14) ◽  
pp. 2783
Author(s):  
Sorin Nistor ◽  
Norbert-Szabolcs Suba ◽  
Kamil Maciuk ◽  
Jacek Kudrys ◽  
Eduard Ilie Nastase ◽  
...  
Keyword(s):  
Time Series ◽  
Visual Inspection ◽  
Flicker Noise ◽  
Vertical Component ◽  
Likelihood Estimation ◽  
Noise Model ◽  
Noise Amplitude ◽  
Allan Deviation ◽  
Power Spectral ◽  
Position Time Series

This study evaluates the EUREF Permanent Network (EPN) station position time series of approximately 200 GNSS stations subject to the Repro 2 reprocessing campaign in order to characterize the dominant types of noise and amplitude and their impact on estimated velocity values and associated uncertainties. The visual inspection on how different noise model represents the analysed data was done using the power spectral density of the residuals and the estimated noise model and it is coherent with the calculated Allan deviation (ADEV)-white and flicker noise. The velocities resulted from the dominant noise model are compared to the velocity obtained by using the Median Interannual Difference Adjusted for Skewness (MIDAS). The results show that only 3 stations present a dominant random walk noise model compared to flicker and powerlaw noise model for the horizontal and vertical components. We concluded that the velocities for the horizontal and vertical component show similar values in the case of MIDAS and maximum likelihood estimation (MLE), but we also found that the associated uncertainties from MIDAS are higher compared to the uncertainties from MLE. Additionally, we concluded that there is a spatial correlation in noise amplitude, and also regarding the differences in velocity uncertainties for the Up component.

scholarly journals Extracting Common Mode Errors of Regional GNSS Position Time Series in the Presence of Missing Data by Variational Bayesian Principal Component Analysis

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2298 ◽  
Author(s):  
Wudong Li ◽  
Weiping Jiang ◽  
Zhao Li ◽  
Hua Chen ◽  
Qusen Chen ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Time Series ◽  
Missing Data ◽  
Principal Component ◽  
Component Analysis ◽  
Common Mode ◽  
Variational Bayesian ◽  
North East ◽  
Position Time Series ◽  
Gnss Position Time Series

Removal of the common mode error (CME) is very important for the investigation of global navigation satellite systems’ (GNSS) error and the estimation of an accurate GNSS velocity field for geodynamic applications. The commonly used spatiotemporal filtering methods normally process the evenly spaced time series without missing data. In this article, we present the variational Bayesian principal component analysis (VBPCA) to estimate and extract CME from the incomplete GNSS position time series. The VBPCA method can naturally handle missing data in the Bayesian framework and utilizes the variational expectation-maximization iterative algorithm to search each principal subspace. Moreover, it could automatically select the optimal number of principal components for data reconstruction and avoid the overfitting problem. To evaluate the performance of the VBPCA algorithm for extracting CME, 44 continuous GNSS stations located in Southern California were selected. Compared to previous approaches, VBPCA could achieve better performance with lower CME relative errors when more missing data exists. Since the first principal component (PC) extracted by VBPCA is remarkably larger than the other components, and its corresponding spatial response presents nearly uniform distribution, we only use the first PC and its eigenvector to reconstruct the CME for each station. After filtering out CME, the interstation correlation coefficients are significantly reduced from 0.43, 0.46, and 0.38 to 0.11, 0.10, and 0.08, for the north, east, and up (NEU) components, respectively. The root mean square (RMS) values of the residual time series and the colored noise amplitudes for the NEU components are also greatly suppressed, with average reductions of 27.11%, 28.15%, and 23.28% for the former, and 49.90%, 54.56%, and 49.75% for the latter. Moreover, the velocity estimates are more reliable and precise after removing CME, with average uncertainty reductions of 51.95%, 57.31%, and 49.92% for the NEU components, respectively. All these results indicate that the VBPCA method is an alternative and efficient way to extract CME from regional GNSS position time series in the presence of missing data. Further work is still required to consider the effect of formal errors on the CME extraction during the VBPCA implementation.

scholarly journals General Geometric Model of GNSS Position Time Series for Crustal Deformation Studies – A Case Study of CORS Stations in Vietnam

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Dinh Trong TRAN ◽  
Quoc Long NGUYEN ◽  
Dinh Huy NGUYEN
Keyword(s):  
Time Series ◽  
Crustal Deformation ◽  
Linear Trend ◽  
Geometric Model ◽  
Real Data ◽  
Deformation Monitoring ◽  
Calculation Results ◽  
Position Time Series ◽  
Seismic Deformation ◽  
Gnss Position Time Series

In processing of position time series of crustal deformation monitoring stations by continuousGNSS station, it is very important to determine the motion model to accurately determine the displacementvelocity and other movements in the time series. This paper proposes (1) the general geometric model foranalyzing GNSS position time series, including common phenomena such as linear trend, seasonal term,jumps, and post-seismic deformation; and (2) the approach for directly estimating time decay ofpostseismic deformations from GNSS position time series, which normally is determined based on seismicmodels or the physical process seismicity, etc. This model and approach are tested by synthetic positiontime series, of which the calculation results show that the estimated parameters are equal to the givenparameters. In addition they were also used to process the real data which is GNSS position time series of4 CORS stations in Vietnam, then the estimated velocity of these stations: DANA (n, e, u = -9.5, 31.5, 1.5mm/year), HCMC (n, e, u = -9.5, 26.2, 1.9 mm/year), NADI (n, e, u = -10.6, 31.5, -13.4 mm/year), andNAVI (n, e, u = -13.9, 32.8, -1.1 mm/year) is similar to previous studies.

scholarly journals Variations of the ionospheric TEC using simultaneous measurements from the China Crustal Movement Observation Network

2012 ◽  
Vol 30 (10) ◽  
pp. 1423-1433 ◽  
Author(s):  
Y. W. Wu ◽  
R. Y. Liu ◽  
B. C. Zhang ◽  
Z. S. Wu ◽  
J. S. Ping ◽  
...  
Keyword(s):  
Crustal Movement ◽  
Topside Ionosphere ◽  
Electron Content ◽  
Equatorial Anomaly ◽  
Total Electron ◽  
Movement Observation ◽  
The North ◽  
Ionospheric Total Electron Content ◽  
Observation Network ◽  
Two Peaks

Abstract. Variations of the ionospheric Total Electron Content (TEC) over China are investigated using the TEC data obtained from China Crustal Movement Observation Network in the year 2004. The results show a single-peak occurred in post-noon for the diurnal variation and two peaks exit around two equinox points, respectively, for the seasonal variation. Overall, the values of TEC increased from the north to the south of China. There were small but clear longitudinal differences in both sides of the longitudes with zero magnetic declination. The intensity of the day-to-day variation of TEC was not a monotonic change along the latitudes. It was usually weaker in the middle of China than that in the north or south. Comparing with the maximum F-layer electron density (NmF2) derived from the ionosonde stations in China, it is found that the day-to-day variation of TEC was less significant than that of NmF2, and that the northern crest of the equatorial anomaly identified from the NmF2 data can reach Guangzhou-region. While, the TEC crest was hardly observed in the same location. This is probably caused by the tilt of topside ionosphere near the northern anomaly crest region at lower latitudes.

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