SKYPLOT_DEM: a tool for GNSS planning and simulations

Satellite survey techniques have become commonplace for several applications such as surveying, environmental positioning, and navigation. The possibility of using this technique is strongly dependent on the possibility of receiving data from at least four satellites, as the accuracy is dependent on both the number of visible satellites and on their relative positions in the sky. From a theoretical standpoint, the Global Positioning System (GPS) constellation of satellites was designed to guarantee the continuous visibility of a minimum of four satellites worldwide, but this was based on the major approximation of considering the earth as an ellipsoid. The presence of natural (such as mountains) and anthropic (such as buildings) obstacles reduce sky visibility, in some cases significantly, thereby reducing the position accuracy or the possibility of determining a position (in the case of less than four satellites). The evolution of satellite positioning technologies will result in the possibility that, in the near future, many constellations can be used to determine the position of a receiver. Additionally, the Glonass constellation will be improved, and the new Galileo constellation will be deployed. Starting from digital elevation models (DEM), orbits (broadcast or precise), and the Keplerian parameters of new constellations, an open-source software has been realized with the aim of performing more accurate planning and simulations of the skyplot (the map of the visible satellites) in a point or region for a defined window of time. The software, developed in the C++ language, permits the simulation of the current constellation and the simulation of future scenarios by considering the interoperability between NAVSTAR-GPS, GLONASS, Galileo, COMPASS, and other systems. The simulation, conducted using DEM, permits the definition of a more correct obstacle map for each point. Of course, the DEM is more detailed and accurate, resulting in a more precise obstacle map and thus a more precise simulation (DEMs derived from Lidar data can even be used to account for the blockage caused by buildings). This paper begins with an introduction concerning the approach used to determine the skyplot and the obstacle map derived from a DEM, continues by explaining the logical architecture of the software and then presents simulation results in different conditions (with or without the DEM, using different constellations, and considering either one point or a regional analysis).