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Article

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

by 1,2,3, 1,*, 1,3 and 3
1
GNSS Research Center, Wuhan University, Wuhan 430079, China
2
Geodetic Institute, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
3
Institute of Geodesy, University of Stuttgart, 70174 Stuttgart, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(9), 1472; https://doi.org/10.3390/rs10091472
Received: 3 July 2018 / Revised: 3 September 2018 / Accepted: 11 September 2018 / Published: 14 September 2018
(This article belongs to the Special Issue Remote Sensing of Tectonic Deformation)
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. View Full-Text
Keywords: Global Positioning System (GPS); Crustal Movement Observation Network of China (CMONOC); time series; periodic signals; noise; Common Mode Components (CMC); Principal Component Analysis (PCA); velocity field; environmental loading Global Positioning System (GPS); Crustal Movement Observation Network of China (CMONOC); time series; periodic signals; noise; Common Mode Components (CMC); Principal Component Analysis (PCA); velocity field; environmental loading
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MDPI and ACS Style

Yuan, P.; Jiang, W.; Wang, K.; Sneeuw, N. Effects of Spatiotemporal Filtering on the Periodic Signals and Noise in the GPS Position Time Series of the Crustal Movement Observation Network of China. Remote Sens. 2018, 10, 1472. https://doi.org/10.3390/rs10091472

AMA Style

Yuan P, Jiang W, Wang K, Sneeuw N. Effects of Spatiotemporal Filtering on the Periodic Signals and Noise in the GPS Position Time Series of the Crustal Movement Observation Network of China. Remote Sensing. 2018; 10(9):1472. https://doi.org/10.3390/rs10091472

Chicago/Turabian Style

Yuan, Peng, Weiping Jiang, Kaihua Wang, and Nico Sneeuw. 2018. "Effects of Spatiotemporal Filtering on the Periodic Signals and Noise in the GPS Position Time Series of the Crustal Movement Observation Network of China" Remote Sensing 10, no. 9: 1472. https://doi.org/10.3390/rs10091472

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