## 3 The Basic of GNSS
### System Architecture
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Multi-Sensor Architecture** & **Reference** & **Description** \\ \hline Kalman-based filtering recursion & [41] & Multi-sensor system that collects data from various sensors installed in the vehicle (in particular IMU and GPS) and performs Kalman-based filtering recursion \\ \hline Adaptive multi-sensor data fusion technique & [42] & Precise evaluation of train position and speed based on three on-board sensors—longitudinal accelerometer, odometer, and GPS receiver \\ \hline Fusion of tachometer and IMU & [44] & Improved performance in terms of accuracy of speed and position estimation by applying Kalman filtering theory \\ \hline Particle filter & [45,46] & Integration of odometry with inertial measurements, laser scans, and image data, resulting in track maps, motion model, and perception model to implement 1D estimation \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Characteristics of systems with multi-sensor architecture. A different architecture possible is to combine a GNSS receiver with capability signals and three-dimensional (3D) map matching techniques. An electronic track map is designed, generated, and stored as a static data source representing the railway lines of an area. As the most important part, track data are the basic elements that populate the database and describe practical rail lines at various scales. If GNSS signals fail, alternative signals such as Wi-Fi can be used to estimate the position of the train. The location of additional access points, such as in tunnels, will need to be determined to maintain position accuracy. Three-dimensional map matching will support position estimation in urban areas and can help determine the track on which the train is traveling. The map can also be used as a positioning aid and provide train heading information based on track location. This system has the advantage of being independent of the systems installed on the train. However, in accordance with the above-described risk regarding potential errors arising during the digital map stage, there may be a situation in which a positioning system based on the presented architecture fails to achieve the required level of reliability estimated under the RAMS criteria. Given the potential risks arising from the use of a digital map-based architecture, the use of an architecture whose topology would consist of a combination of the aforementioned GNSS/INS architecture and 3D map matching should be considered. The use of additional sensors, which are subject to certification in rail applications, could result in a significant increase in system reliability [63; 64]. In the case of the development of the architecture described above, it should be borne in mind that it will be characterized by a complex topology of dependencies between the various elements of such an architecture. Increasing the number of devices, thus expanding the network of dependencies between each of them, may contribute to potential errors in the functioning of the system itself, and--as should also be borne in mind in the conception and design of such systems--will generate additional costs [65; 66]. An example of the topology of the described architecture is shown in Figures 5 and 6.