The velocities of the Global Positioning System (GPS) stations are widely employed for numerous geodynamical studies. The aim of this paper is to investigate the reliability of station velocities and to draw reader’s attention that for proper estimates of velocity, we need to consider the optimal character of noise. We focus on a set of 115 European GPS stations which contributed to the newest release of the International Terrestrial Reference Frame (ITRF), i.e. ITRF2014. Based on stacked Power Spectral Densities (PSDs), we show that amplitudes o f seasonal signals are significant for nine harmonics of tropical year (365.25 days) and two harmonics of draconitic year (351.60 days). The amplitudes of tropical annual signal fall between 0.1-8.4 mm and are much higher for vertical component than for horizontal. Draconitic annual signal reaches the maximum amplitudes of 1.2 and 0.9 mm for North and East, respectively, whereas is slightly higher for the Up component with a maximum of 3.1 mm. We performed a noise analysis with Maximum Like lihood Estimation (MLE) and found that stations in Central and Northern Europe are characterized by spectral index between flicker and random-walk noise, while stations in Southern and Western Europe: between white and flicker noise. Both amplitudes and spectral indices of power-law noise show a spatial correlation for Up component. We compared the uncertainties of velocities derived in this study with a combination of power-law and white noises to the ones offici ally released in the ITRF2014 with a pure white noise. A ratio of the two estimates is larger than 10 for 13 % and 30 % of stations in horizontal and vertical direction, respectively with medians of 6 and 7. The large differences support the fact that at the velocity determination the proper noise characteristic should be taken into account to avoid any mislead interpretation., Anna Klos and Janusz Bogusz., and Obsahuje bibliografické odkazy
Since October 2011, the Russian GLObal NAvigation Satellite System (GLONASS) has been revitalized and is now fully operational with 24 satellites in orbit. It is critical to assess the benefits and problems of using GLONASS observations (i.e. GLONASS-only or combined Global Positioning System (GPS) and GLONASS) for precise positioning and zenith total delay (ZTD) retrieval on a global scale using precise point positioning (PPP) technique. In this contribution, extensive evaluations are conducted with Global Navigation Satellite System (GNSS) data sets collected from 251 globally distributed stations of the International GNSS Service (IGS) network in July 2016. The stations are divided into 30 groups by antenna/radome types to investigate whether there are ante nna/radome-dependent biases in position and ZTD derived from GLONASS-only PPP. The positioning results do not show obvious antenna/radome-dependent biases except the stations with JAV_RINGANT_G3T/NONE. For these stations, the averaged biases in horizontal component, especially in the north component, can achieve as high as -9.0 mm. The standard de viation (STD) and root mean square (RMS) are used as indicators of positioning repeatability and accuracy, respectively. The averaged horizontal STD and RMS of GLONASS-only PPP are comparable to GPS-only PPP, while in vertical component, those for GLONASS-only P PP are larger. Furthermore, the STD and RMS of GPS+GLONASS combined PPP solutions are the smallest in horizontal and vertical components, indicating that adding GLONASS observations can achieve better positioning performance than GPS-only PPP. With the IGS final ZTD as reference, we find that ZTD biases and accuracy of GLONASS-only are latitude - and antenna/radome-independent. The ZTD accuracy of GLONASS-only PPP is slightly worse than that of GPS-only PPP. Compared with GPS-only PPP, the ZTD accuracy is only improved by 1.3% from 7.8 to 7.7 mm by adding GLONASS observations., Feng Zhou, Shengfeng Gu, Wen Chen and Danan Dong., and Obsahuje bibliografické odkazy
The Institute of the Rock Structure and Mechanics AS CR operates the GEONAS network that now consists of 17 perm anent GPS observatories. The outliers and in consistencies occur within the time series observed in the winter season 200 5/2006 for the position of the GNSS antennas of the observatories SNEC and BISK located high in the m ountains, at th e Sněžka Mt. (1602 m, the Giant Mts.) and the Biskupská kupa Mt. (890 m, the Jeseníky Mts.) respectively. Therefore web cameras and meteorological sensors were in stalled at GEONAS observatories located in the mountain regions. The snow coverage and other meteorological influences affecti ng the antennas monitoring GPS signals at these observatories were estimated. The individual photos were analyzed and compared to variations in the time series to obtain the time series for winter seasons reducing the snow coverage effects., Milada Grácová, František Mantlík, Vladimír Schenk and Zdeňka Schenková., and Obsahuje bibliografické odkazy
We estimated the common seasonal signal (annual oscillation) included in the Global Positioning System (GPS) vertical position time series by using Multichannel Singular Spectrum Analysis (MSSA). We employed time series from 24 International GNSS Service (IGS) stations located in Europe which contributed to the newest ITRF 2014 (International Terrestrial Reference Frame). The MSSA method has an advantage over the traditional modelling of seasonal signals by the Least-Squares Estimation (LSE) and Singular Spectrum Analysis (SSA) approaches because it can extract time-varying and common seasonal oscillations for stations located in the considered area. Having estimated the annual curve with LSE, we may make a misfit of 3 mm when a peak-to-peak variations of seasonal si gnals are to be estimated due to the time-variability of seasonal signal. A variance of data modelled as annual signal with SSA and MSSA differs of 3 % at average what proves that the MSSA-curves contain only time-varying and common seasonal signal and leave the station-specific part, local phenomena and power-law noise intact. In contrast to MSSA, these effects are modelled by SSA. The differences in spectral indices of power-law noise between MSSA and LSE esti mated with Maximum Likelihood Estimation (MLE) are closer to zero than the ones between SSA and LSE, which means that MSSA curves do not contain site-specific noise as much as the SSA curves do., Marta Gruszczynska, Anna Klos, Severine Rosat and Janusz Bogusz., and Obsahuje bibliografické odkazy