## 1 Introduction  
The satellite systems act as relay stations and make up a critical part of the common wireless communications substructure. These systems are employed in most civilian and military implementations, such as the global positioning system (GPS), remote sensing, digital video broadcasting (DVB), high definition video, amateurish radio communications, broadband Internet, weather forecasting, environment surveillance, Global Navigation Systems (GNS), and in several other applications [1, 2, 3, 4]. Consequently, the number of Global Navigation Satellite Systems (GNSS) receivers installed on the Unmanned Aerial Vehicles (UAVs) board has increased recently. In general, the aeronautical field is categorized as Manned Aircraft Vehicles (MAVs) and Unmanned Aircraft Vehicles (UAVs). The MAV category requires the presence of a human pilot on the aircraft board, while the UAV category does not require the presence of a human pilot on the aircraft board, and it is controlled remotely over a control room. The number of UAVs, commonly known as drones, has been rapidly increasing in the last decade, and there is an industry analysis that the drone market worldwide will increase by more than 50 billion dollars in 2025 [5]. Based on the market report referred by the GNSS Supervisory Authority (GSA), the number of drones equipped with GNSS receivers is estimated to be almost 70 million and for other applications, more than twice the number of GNSS receivers required [5,6]. Overcrowding in wireless communication systems may affect these applications and produce Radio Frequency Interference (RFI). The RFI can be classified into two types: unintentional interference, of which over 95% of the satellite communications are suffering, and intentional interference, less than 5% of satellite communication systems are suffering from this kind of interference [7]. RFI may influence these systems, where the source of that interference is required. The RFI sources could be fixed or movable stations on the ground or in the air, such as drones, which are used in military or civilian systems. Figure 1 illustrates the most common interference that may occur in SatCom and GNSS systems. To secure and protect all wireless and satellite systems from interference or jamming, it is necessary to establish organization for monitoring the wanted signals. The main  
Figure 1: Examples of RFI scenarios that may occur in satellite applications. two required approaches in this organization are geolocation and emitter tracking. These approaches are required in military and civilian applications, including aerial maneuvers, airspace monitoring, autonomous vehicles, and robots. In addition, these approaches are mainly related to inferring the navigation of an RF emitter, which is assumed to be a random variable, by observing it. Numerous studies and researches have focused on navigation and positioning issues. Therefore, many useful algorithms have been proposed in the literature [8, 9, 10, 11]. The geolocation technique is a measurement making it possible to know if the position of an emitter source is from a fixed station or the initial position of the emitter is dynamic. Various techniques of geolocation measurements can be implemented. For example: Angle of Arrival (AOA), Time of Arrival (TOA), Time Difference of Arrival (TDOA), Received Signal Strength (RSS), Power Difference of Arrival (PDOA), Frequency Difference of Arrival (FDOA), and Differential Doppler Rate (DDR) are the most popular types of measurements. In addition, the accuracy of the emitter geolocation measurement can be improved by combining two or more techniques in one approach, such as hybrid TDOA/FDOA, TDOA/AOA, TDOA/PDOA, and TDOA/FDOA/DDR. Various geolocation measurement techniques and methods have been exhibited in [12,13]. In general, the RF emitter geolocation is not concluded geometrically, but it is estimated by a set of non-linear equations created by the conventional geolocation measurements with the knowledge of the geometry parameters of the sensors used.