The aim of this paper is to show time-de pendent baseline variation between GPS stations situated in South-East Poland. This study was based on daily data analysis of selected GPS stations: WROC, GOPE, MOPI, KRAW and KATO. The start date o f the analysis is linked at every station with the beginning of its operation and the closing date of the operation is in 2006. The multiresolution signal decomposition method has been used to analyze the periodic terms of the time series of the above. The estimated trends enable further coordinate analysis as well as determination of site displacements at the study area., Mariusz Figurski, Krzysztof Kroszczyński, Paweł Kamiński and Marcin Gałuszkiewicz., and Obsahuje bibliografické odkazy
This paper presents the results of the application of wavelet decomposition to processing data from the GGP sites (The Global Geodynamics Project). The GGP is an international project within which the Earth's gravity field changes are recorded with high accuracy at a number of stations worldwide using superconducting gravimeters. Data with a 5-second sampling interval from Wettzell and Bad Homburg were used for the research. The wavelet transform enables the investigation of the temporal changes of the oscillation amplitudes or the decomposition of the time series for the analysis of the required frequencies. The wavelet decomposition was performed using the regular orthogonal symmetric Meyer wavelet. The research concerned data from an earthquake period recorded at various locations and a quiet period when the gravimeters worked without any disturbances. The decomposition was followed by the Fast Fourier Transform for signal frequency components and then by correlation analyses of corresponding frequency components (for periods from 10 to 60 000 seconds) for all sensor combinations, for the quiet and the earthquake periods separately. Frequency components defining long term changes for all sensor combinations, as well as combinations between two sensors at the same site for the quiet days are characterised by high correlation coefficients. For the time of the earthquake, the Wettzell site data proved strong correlation for all frequency components, while the Bad Homburg site data showed an unexpected decrease of correlation for the majority of frequency components. The authors also showed that wavelet decomposition can be a good method of data interpolation, especially from the time of earthquakes. Moreover, it is a very useful tool for filtering the data and removing the noises., Janusz Bogusz, Anna Klos and Wieslaw Kosek., and Obsahuje bibliografii