## 1 Introduction
The UAV continuously sends telemetry data to the GCS and it includes the following information:  
* Altitude, speed, and heading information. * Battery status and remaining flight time. * Sensor data such as temperature, humidity, or camera feed. * GPS coordinates for position tracking. From the GCS, it is possible to choose between different flight modes, such as the following:  
* Manual. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Class**} & \multirow{2}{*}{**Category**} & **Operating Altitude** & **Range** & **Payload** \\  & & **(ft)** & **(km)** & **(kg)** \\ \hline I & Micro (\textless{2 kg}) & \textless{3000} & 5 & 0.2–0.5 \\ I & Mini (2–20 kg) & \textless{3000} & 25 & 0.5–10 \\ II & Small (\textless{150 kg}) & \textless{5000} & 50–150 & 5–50 \\ III & Tactical & \textless{10,000} & \textless{200} & 25–200 \\  & Medium-Altitude & & & \\ IV & Long-Endurance & \textless{18,000} & \textgreater{1000} & \textgreater{200} \\  & (MALE) & & & \\  & High-Altitude & & & \\ V & Long-Endurance & \textgreater{18,000} & \textgreater{1000} & \textgreater{200} \\  & (HALE) & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: UAV classification [7]. * Altitude hold. * Loiter mode. * Autonomous (pre-programmed missions). To ensure safe take off, flight, and landing, these vehicles are equipped with multiple onboard sensors [9], such as environmental sensors (barometers and humidity sensors), imaging sensors (RGB or hyperspectral cameras), Light Detection and Ranging (LIDAR), and navigation systems like GPS and Inertial Navigation Systems (INS), which combine GPS data with INS data for accurate and reliable position information. The localization of fixed-wing UAVs is a challenging task [10]. To carry out missions autonomously, it is crucial to accurately determine the state of the UAV, including its position and heading. Typically, GPS and IMU data are used for this purpose. However, GPS signals may be obstructed by buildings or subject to intentional or unintentional jamming [11]. This study focuses on estimating the geographical position of the UAV when it flies in GPS-denied zones. Problem StatementGPS signals are vital for achieving autonomy. Unfortunately, these signals can be affected by natural obstructions: buildings, mountains, dense forests, and other physical structures can block or reflect GPS signals, leading to poor reception or complete signal loss in those areas [12; 13; 14]. Additionally, GPS signals can be intentionally blocked or disrupted in certain zones, including secure facilities, prisons, or by criminals [15]. There are multiple ways in which GPS signals are intentionally restricted. For example, GPS jamming involves broadcasting radio signals on the same frequencies used by GPS satellites, overpowering the weaker GPS signals. GPS spoofing is another method to restrict GPS. In this case, a fake GPS signal that mimics legitimate signals is broadcast, tricking GPS receivers into calculating incorrect position or velocity values. Detecting GPS spoofing can be challenging, but several methods and technologies can help identify if a GPS signal is being spoofed. Although the identification of spoofing is beyond the scope of this study, some techniques include cross-correlation methods where false signals overlay and overpower true signals [16; 17; 18], fusion of inertial navigation sensors [19; 20], information fusion from multiple antennas [21], or using artificial intelligence [22]. Regardless of how the GPS signal is compromised, the mission may fail, since no other onboard sensor, like the Inertial Measurement Unit (IMU), is able to provide the reliable position, velocity, and altitude of the UAV since the state estimation drifts in time and becomes unusable after few minutes [23; 24; 25; 26]. As a result, the UAV will take action depending on the flight mode or if the human pilot has visual contact with the vehicle. For instance, if there is no visual contact, most UAVs have an automated routine to return home, preventing them from completing its task.