The remote monitoring of atmosphere is designed to obtain information about the state of atmosphere. The principle of the remote monitoring of atmosphere is based on registering and processing of GLONASS/GPS radio signals. Modern networks of active reference stations allow us to solve both practical problems of geodesy, navigation, and purely scientific problems that are important in all geosciences. We propose to explore the existing infrastructure of national networks of active reference GNSS stations for remote sensing of the atmosphere in order to determine the water vapour content in the atmosphere as one of the major factors affecting weather.

The results of the determined ionization identifier TEC (Total Electron Content) for continuously operating reference Global Navigation Satellite Systems (GNSS) stations are analysed. On the one hand, the data reflect the state of the ionosphere during the observation; on the other hand, it is a substantial tool for accuracy improvement and reliable determination of coordinates of the observation place. It was decided to solve a problem of restoring the spatial position of the ionospheric state or its ionization field according to the regular definitions of the TEC identifier, i.e. VTEC (Vertical TEC). We have described one possible way of solving this problem, which is based on mathematical modelling by using degree polynomials and trigonometric Fourier series. Degree polynomials describe the trend of function, whereas the trigonometric Fourier series are used in order to better simulate the fluctuation. The method was tested for network of permanent stations ZAKPOS.

The role of space geodetic techniques combination is becoming increasingly important to calculate the geodetic parameters. It has an intention of using the advantages and complementarity of different techniques to achieve the best solution. Estimation of geodetic parameters from observations mainly was done by least squares adjustment within the Gauss - Markov model. The combination can be done at three different levels: observations, normal equations and parameters. This article analyses the differences between the approaches and discusses the possibility of troposphere parameters calculation from a theoretical point of view.

According to the fast development and distribution of GNSS technologies all over the world, the large numbers of reference GNSS stations have appeared in Ukraine. These stations are included in the state and several private networks. The permanent GNSS observations gathered within these networks are processed and analysed by the Centre of Lviv Polytechnic National University. A cumulative solution (coordinates expressed at the specified epoch and velocities of all stations) was estimated by using the GAMIT-GLOBK software. The authors made several numerous tests using certain configuration of fiducial stations which belong to the EPN A class to transfer ITRF08 frame into Ukraine area and choose the best strategy of alignment of the Ukrainian national GNSS network to the EPN. Three different solutions with cretin tolerance set for Ukrainian GNSS network were estimated and each time the different set of coordinates was obtained. The differences reached several millimetres. Also for verification, our solution was compared with EPN solution. Received coordinates and velocities could have a geophysical interpretation and provide very useful information for local geodesy tasks.

The national geodetic infrastructure of Ukraine has developed rapidly into Ukrainian Coordinate Reference System UCS – 2000, a fully GNSS compatible coordinate reference system, which is realised through networks of active GNSS stations. They provide data for post processing and streamed raw data for real-time network (RTN) solutions. The RTN raw data are currently being used by both Trimble (ZAKPOS Network), Leica Geosystems (System Solutions Network) and Topcon (TNT - TPI Network) to provide independent RTN solutions. This study is the first in the public domain to evaluate the performance of RTN services in Ukraine and it is intended to provide guideline information for geo-spatial practitioners. Based on collecting RTN data at five locations and using standard observing and processing methods, an accuracy of 25 mm ±10 mm with respect to 2D coordinates and 34 mm ±14 mm with respect to the heights was achieved. The three systems were shown to be generally comparable although some initialization problems were experienced. The result has revealed expected ~2-5 cm (95%) precision for the horizontal and vertical components; however, large horizontal and vertical biases were observed, which can be as high as 8 cm.