Analysis of Noise and Velocity in GNSS EPN-Repro 2 Time Series
| Autor: | Alexandra Muntean, Sorin Nistor, Eduard Nastase, Jacek Kudrys, Norbert-Szabolcs Suba, Kamil Maciuk |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
010504 meteorology & atmospheric sciences
Flicker Science Spectral density noise model 010502 geochemistry & geophysics Geodesy 01 natural sciences GNSS time series EPN Noise Amplitude Skewness General Earth and Planetary Sciences Flicker noise Allan variance EUREF Permanent Network 0105 earth and related environmental sciences Mathematics |
| Zdroj: | Remote Sensing, Vol 13, Iss 2783, p 2783 (2021) Remote Sensing; Volume 13; Issue 14; Pages: 2783 |
| ISSN: | 2072-4292 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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