## 3 System Description
It composed by a mobile phone and two applications: one to collect data and another to format it. It will be integrated as part of the hardware used as the UAV base station. 3. Graphical User Interface (GUI): this is a software program required to visualize the information that is shown to the end user. 4. Galileo GNSS: this is used as a pivotal part for this proposal, as it offers location features that are more accurate than the most widely used equivalent GNSS systems. This subsystem is taken for granted, as Galileo is already built and precedes the inception of the proposed system described in this paper. It was shown in [23] how the received Galileo signal (the one that will be used for the measurements) can be described in its Intermediate Frequency (IF) as: \[Y_{k_{GAL-IF}}=(w_{k}e_{1B_{k}}sub_{B}-e_{1C_{k}}sub_{C})\ cos\left(2\pi f_{IF}t_ {k}+\theta_{k}\right)+N_{k}\] (1) \[sub_{B}=\alpha SC_{E1B_{ak}}+\beta SC_{E1B_{kk}}\] (2) \[sub_{C}=\alpha SC_{E1C_{ak}}+\beta SC_{E1C_{kk}}\] (3)  
In this set of equations, \(w_{k}\) is an estimation of the Non-Return-to-Zero (NRZ) unpredictable symbol. \(e_{1B_{k}}\) is the NRZ pseudo-random (PRN) sequence for the Galileo E1B Signal, whereas \(e_{1C_{k}}\) is the NRZ pseudo-random (PRN) sequence for the Galileo E1C one. At the same time, \(\alpha=\sqrt{\frac{10}{11}}\) and \(\beta=\sqrt{\frac{1}{11}}\) and the \(SC_{E1A}|B,a|b_{k}\). Finally, \(N_{k}\) is the Additive White Gaussian Noise (AWGN) at the input of the receiver. Figure 1 shows how the subsystems interact with each other and what kind of interfaces are used to transfer information from one subsystem to another. It must be noted that, despite the differentiations outlined in the figure, the subsystems have been integrated in a seamless manner. Furthermore, it can be seen how the MDAS is integrated as part of the UAV, as it will be implemented as a piece of hardware capable of sensing the data regarding mobile network signalling. The three subsystems that have been previously mentioned as the ones used to build the proposed model (UAV, MDAS, GUI) interact with each other, as shown in the diagram displayed in Figure 2. The drone has been represented at the leftmost part of the diagram, with its most prominent parts displayed: wireless receptor (WIFI), Galileo receptor used by the autopilot for precise positioning (GNSS RX) and the MDAS equipment (radio frequency sensor measuring program and the mobile phone that is used for its installation and operation). It must be noted that the drone can connect to both the base station (composed by the radio transmitter for guided flight and the computer running the GUI used for data visualization) with its wireless module and to the Galileo GNSS via Navio2, which is the autopilot device used for flight control. Figure 1: Components used in the proposed system. Figure 2: Relations and communication among major components of the system. used for measurement accuracy. Note that a quadcopter has been chosen to represent the UAV structure. Lastly, security features must also be considered for this development, as there are several threats that could be potentially exploited for cyberattacks that might result in an unwanted behaviour of the system, ranging from tampering with the collected data, from losing the UAV to some spurious third party. The attacks that could take place in the proposed development are as follows:  
1. Base station monitoring: credentials used to access the base station could be leaked, or there could be other privacy failures that enable a spurious third party to monitor what kind of flight the UAV is carrying out. 2. UAV command spoofing: this attack is related to the previous one in the sense that it will require accessing the base station. Once the spurious party has managed to do so, it can alter the commands sent to the UAV to follow a different pattern or perform actions that could potentially lead to damaging the UAV to a greater or lesser extent. 3.