Estimates of seasonal signals in GNS time series and environmental loading models with iterative Least-Squares Estimation (iLSE) approach
PBN-AR
Instytucja
Wydział Inżynierii Kształtowania Środowiska i Geodezji (Uniwersytet Przyrodniczy we Wrocławiu)
Informacje podstawowe
Główny język publikacji
angielski
Czasopismo
Acta Geodynamica et Geomaterialia (20pkt w roku publikacji)
ISSN
1214-9705
EISSN
Wydawca
ACAD SCI CZECH REPUBLIC INST ROCK STRUCTURE & MECHANICS
DOI
URL
Rok publikacji
2018
Numer zeszytu
2 (190)
Strony od-do
131-141
Numer tomu
15
Identyfikator DOI
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Autorzy
(liczba autorów: 2)
Słowa kluczowe
angielski
coordinates time series
loading models
cross-correlation
phase shift
correlation coefficient
wavelet analysis
seasonal signal
Streszczenia
Język
angielski
Treść
The GNSS (Global Navigation Satellite System) coordinates time series are still used as a source for determining the velocities of GNSS permanent stations. These coordinates, apart from the geodynamical signals, also contain an interference signal. This paper shows the results of the comparative analysis of the GNSS coordinates time series with a deformation of the Earth's crust obtained from loading models. In the analysis, coordinates time series are used (CODE Repro2013) without loading models (Atmospheric Pressure Loading, Hydrology, Non-Tidal Ocean Loading) at the stage of the reprocessing of GNSS archival data. The analyses showed that in the case of the Up component there is a high correlation between the GNSS coordinates changes and deformations of the Earth's crust from the loading models (coefficient 0.5–0.8). Additionally, we noticed that for horizontal components (North, East) changes occur in the phase shift between coordinates, and the Earth’s crust deformations signals are accelerated or delayed each other (-150 to 200 days). This article shows new methods of iLSE (iteration Least Square Estimation) to determine periodic signals in the time series. Additionally, we compared the values of estimated amplitudes for GNSS and deformation time series.
Inne
System-identifier
PX-5b14e670d5ded09bcbe7816f
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