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Effects of spatiotemporal filtering on the periodic signals and noise in the GPS position time series of the Crustal Movement Observation Network of China

Yuan, Peng 1; Jiang, W.; Wang, K.; Sneeuw, N.
1 Geodätisches Institut (GIK), Karlsruher Institut für Technologie (KIT)


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. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000086241
Veröffentlicht am 05.10.2018
DOI: 10.3390/rs10091472
Zitationen: 22
Web of Science
Zitationen: 23
Zitationen: 24
Cover der Publikation
Zugehörige Institution(en) am KIT Geodätisches Institut (GIK)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2018
Sprache Englisch
Identifikator ISSN: 2072-4292
KITopen-ID: 1000086241
Erschienen in Remote sensing
Verlag MDPI
Band 10
Heft 9
Seiten 1472
Schlagwörter 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
Nachgewiesen in Dimensions
Web of Science
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