## 3 The Basic of GNSS
### System Architecture
The study focused on solutions that could be applied to any rail vehicle, regardless of the ground equipment on specific lines. Another study [42] proposed an adaptive multi-sensor data fusion technique to accurately assess train position  
Figure 4: Example architecture of an on-board positioning system using a constellation of GPS/BDS satellites. Prepared on the basis of [28]. Figure 3: Satellite navigation system architecture with signal transmission. Prepared on the basis of [37]. and speed based on three on-board sensors--a longitudinal accelerometer, an odometer, and a GPS receiver. An article [43] presents a rail vehicle localization technique based on the fusion of a tachometer and an IMU to improve performance in terms of speed and position estimation accuracy. This fusion was carried out through Kalman filtering theory. In another paper [44], a particle filter-based approach to localizing a rail-guided robot was presented. The filter was used to integrate odometry with inertial measurements, laser scans, and image data. As a result, a rail map, motion model, and perception model were developed to implement 1D estimation [45,46]. The synthesis of the architecture using multi-sensor systems is shown in Table 3.  
By correlating data from individual sensors, it is possible to obtain more comprehensive coverage regarding the location of a rail vehicle on rail infrastructure. According to the results of previous analysis and research, it is necessary to integrate the map with sensor data to provide information about the environment, such as the track on which the vehicle is traveling, the proximity to dangerous places, the tunnel, etc. In turn, the dynamic data detected by the sensor makes it possible to create a dynamic map with high precision. With the positioning sensor to obtain their position, combined with a precise map, it is easier to depict the traffic situation in the area covered by the system, in order to ensure the safety of railway traffic [47, 48, 49]. The use of multi-sensor solutions and dynamic digital maps requires a data transmission system with a wide bandwidth. A potential future solution is 5G transmission systems, whose high-bandwidth functionality will allow for rail vehicles equipped with multi-sensor systems to share more sensor data or combine them with precise maps for dynamic steering and control of railway traffic [50,51]. Over the past two decades, several projects have been carried out with research aimed at developing solutions to implement GNSSs in railway applications. The first major projects were APOLO [26,52], GADEROS [53], LOCOPROL [54], GaLoROI [25], and 3 inSat [55]. The above projects were implemented in the first decade of the 2000s. All of these projects, even if they did not lead to the commercialization of operational products, certainly helped to introduce GNSS into the railway mentality. The next decade saw the launch of projects such as NGTC (Next-Generation Train Control) [56,57], which aimed to explore how new developments in ERTMS/ETCS for interoperable networks and CBTC (Communication-Based Train Control) systems for urban networks can be mutually leveraged. Satellite positioning is one of the goals of NGTC. Finally, the European Shift2 Rail program [58, 59, 60, 61], in its second innovative program (IP2) [62] on signaling, focuses specifically on reliable train positioning for advanced traffic management and control systems. The list of projects/programs is shown in Table 4.