Saudi Cultural Missions Theses & Dissertations
Permanent URI for this communityhttps://drepo.sdl.edu.sa/handle/20.500.14154/10
Browse
5 results
Search Results
Item Restricted C-Band Air to Ground Communication System for UAV(Florida Institute of Technology, 2025) Alghamdi, Mubark; Kostanic, IvicaC band spectrum 5030-5091 MHz is allocated for command-and-control commu- nication services with unmanned aircraft systems. This document evaluates the possibility of using 3GPP 5G standards for provisioning of such services. Chan- nelization of the spectrum and major system parameters are proposed. The performance of the proposed system in channel fading environment is evaluated using MATLAB based simulations. The evaluations examine SINR, and aver- age throughput of the proposed system at different altitudes of the unmanned aircraft system. MATLAB simulations are used to evaluate system performance in free-space environments. Signal-to-Interference-plus-Noise Ratio (SINR) and Reference Signal Received Power (RSRP) are predicted at different UAS heights. The performance of the system is accessed for different types of antenna arrays on the aircraft. Cases ranging from a single antenna to a 10 by 10 array are con- sidered. The study uses a 20 MHz channel and considers a system load of 50 percent.24 0Item Restricted Autonomous Flight Control System for Engine Testing(Cranfield University, 2025) Al Thafer, Mohammad; Lawson, Craig; Souanef, ToufikThis research presents the development of an Autonomous Flight Control System (AFCS) for the Kestrel, a fixed-wing unmanned aerial vehicle designed by Greenjets as a flying test bench for engine performance evaluation. A Six-Degrees of Freedom (6DoF) model was developed to simulate the Kestrel’s motion, incorporating aerodynamic forces, stability derivatives, and thrust effects. Aerodynamic and stability coefficients were extracted by the vortex lattice method using OpenVSP simulations, forming the foundation for modelling and control design. A Flight Control System (FCS) was implemented using a three-loop nested architecture: an inner loop for pitch and roll rate stabilisation, a middle loop for attitude and airspeed regulation, and closing with an outer loop for course angle and altitude control. Simulations demonstrated the system’s capability to achieve stable responses of commanded flight inputs, with coordinated use of ailerons and elevons in the absence of yaw control. Results reveal the effectiveness of the developed model and control system in enabling autonomous flight, providing a structured foundation for future integration with real-world testing and higherfidelity validation.25 0Item Restricted Machine Learning for Intrusion Detection into Unmanned Aerial System 6G Networks(Embry Riddle Aeronautical University, 2024) Alrefae, Faisal; Babeacinu, Radu; Song, HoubingProgress in the development of wireless network technology has played a crucial role in the evolution of societies and provided remarkable services over the past decades. It remotely offers the ability to execute critical missions and effective services that meet the user's needs. This advanced technology integrates cyber and physical layers to form cyber-physical systems (CPS), such as the Unmanned Aerial System (UAS), which consists of an Unanned Aerial Vehicle (UAV), ground network infrastructure, communication link, etc. Furthermore, it plays a crucial role in connecting objects to create and develop the Internet of Things (IoT) technology. Therefore, the emergence of the CPS and IoT technologies provided many connected devices, generating an enormous amount of data. Consequently, the innovation of 6G technology is an urgent issue in the coming years. The 6G network architecture is an integration of the satellite network, aerial networks, terrestrial networks, and marine networks. These integrated network layers will provide new enabling technologies, for example, air interfaces and transmission technology. Therefore, integrating heterogeneous network layers guarantees an expansion strategy in the capacity that leads to low latency, ultra-high throughput, and high data rates. In the 6G network, Unmanned Aerial Vehicles (UAVs) are expected to densely occupy aerial spaces as UAV flying base stations (UAV-FBS) that comprise the aerial network layer to offer ubiquitous connectivity and enhance the terrestrial network in remote areas where it is challenging to deploy traditional infrastructure, for example, mountain, ocean deserts, and forest. Although the aerial network layer offers benefits to facilitate governmental and commercial missions, adversaries exploit network vulnerabilities to block intercommunication among nodes by jamming attacks and violating integrity through executing spoofing attacks. This work offers a practical IDS onboard UAV intrusion detection system to detect unintentional interference, intentional interference jamming, and spoofing attacks. Integrating time series data with machine learning models is the main part of the suggested IDF to detect anomalies accurately. This integration will improve the accuracy and effectiveness of the model. The 6G network is expected to handle a high volume of data where non-malicious interference and congestion in the channel are similar to a jamming attack. Therefore, an efficient anomaly detection technique must distinguish behaviors in the drone's wireless network as normal or abnormal behavior. Our suggested model comprises two layers. The first layer has the algorithm to detect the anomaly during transmission. Then it will send the initial decision to the second layer in the model, including two separated algorithms, confirming the initial decision separately (nonintentional interference such as congestion in the channel, intentional interference jamming attack, and classify the type of jamming attack, and the second algorithm confirms spoofing attack. A jamming attack is a stealthy attack that aims to exhaust battery level or block communication to make wireless UAV networks unavailable. Therefore, the UAV forcibly relies on GPS signals. In this case, the adversary triggers a spoofing attack by manipulating the Global Navigation Satellite System (GNSS) signal and sending a fake signal to make UAVs estimate incorrect positions and deviate from their planning path to malicious zones. Hackers can start their malicious action either from malicious UAV nodes or the terrestrial malicious node; therefore, this work will enhance security and pave the way to start thinking about leveraging the benefit of the 6G network to design robust detection techniques for detecting multiple attacks that happen separately or simultaneously.34 0Item Restricted Drone-Assisted Stockpile Volume Estimation in Open and Confined Spaces(The University of Manchester, 2024-05-06) Alsayed, Ahmad A; Nabawy, MostafaThis thesis aims to develop unmanned aerial system solutions for stockpile volume estimation in both open and confined spaces. It starts with a comprehensive literature review that examines both traditional and recent stockpile volume estimation techniques employed in various environments. It was found that recently emerging aerial methods, such as drone-borne LiDAR sensors, can enable notable advantages including speed, safety, occlusion elimination, and enhanced accuracy compared to current typical industrial solutions. However, there is still a notable gap in research represented in the underdevelopment of cost-effective aerial solutions for safe and precise volume estimation within confined spaces. The research in this thesis starts with a detailed investigation of the state-of-the-art in utilising drones for operations within treacherous conditions, particularly within industrial confined spaces. It was found that existing studies have not thoroughly examined drone missions under operational constraints such as absence of GPS signals, dust-laden air, and poor/lack of visibility. These limitations defined the way for a relatively novel application where drones could be deployed to enhance inspection while augmenting safety measures. Following the establishment of this fresh perspective, mission planning, instrument development, and implementation of control and navigation strategies were assessed across diverse confined spaces and for various stockpile volume estimation missions in both simulated and real-world scenarios. A thorough cost-benefit analysis elucidated that drone-based solutions for stockpile volume estimation within confined spaces achieve a high Cost-Benefit Priority Factor (CPF) of 133-200. Moreover, this approach surpasses traditional industrial fixed sensor systems in flexibility, initial cost savings, and ability to serve multiple sites. Advancing further, a low-cost, yet effective approach was proposed that relies on actuating a single-point light detecting and ranging (1D LiDAR) sensor using a micro servo motor onboard of a drone. The collected LiDAR ranges were converted to a point cloud that allows the reconstruction of 3D stockpiles. The proposed approach was assessed via simulations of a wide range of mission operating conditions. The influences from modulating the drone flight trajectory, servo motion waveform, flight speed, and yawing speed on the mapping performance were all investigated. Comparing the volumetric error values, the average error from the proposed actuated 1D LiDAR system was 0.9% as opposed to 1% and 0.8% from the 2D and 3D LiDAR options, respectively. That said, compared to 2D and 3D LiDARs, the proposed system requires less scanning speed for data acquisition, is much lighter, and allows a substantial reduction in cost. Experimental tests on drone-based solutions for scanning a reference stockpile were conducted with either single or multiple drones equipped with 1D LiDAR sensors, achieving an average volumetric error of 2%. In contrast, the actuated single-point LiDAR system exhibited a higher volumetric error of 5% due to the significant number of outlier points involved. Finally, as the previously presented solutions required an external localisation system for their operation within confined spaces, this thesis paved the way to get rid of such requirement via applying an ICP (Iterative Closest Point) algorithm that can operate independently of such systems. The proposed algorithm uniquely employed a low-rate, low-dense LiDAR scan, specifically focusing on the horizontal layer of a 3D LiDAR for localisation and scan matching. Furthermore, a wall-following navigation strategy was employed for indoor navigation and path-planning to further streamline the mapping process. It was shown that the estimated volume of the reconstructed stockpiles has an average volumetric error of 3.7%, but this figure was enhanced to 0.4% when applying loop closure. Moreover, mapping using an actuated single-point LiDAR approach was processed using the ICP localisation method, resulting in a 1.4% volumetric error.31 0Item Restricted Performance Evaluation of Physical Layer Security in sub-THz band for UAV Communications(Saudi Digital Library, 2023-08-30) Alali, Abdulaziz; Rawat, DandaWireless communication systems anticipate a surge in demand for higher data rates due to the increased number of interconnected devices, which is expected to double approximately every 18 months. However, the current data rates still fall short of the 100 Gbps rate required for various applications such as immersive virtual reality and high-quality video streaming. While millimeter wave has provided a larger bandwidth compared to microwave frequencies, it remains inadequate. Therefore, the Terahertz (THz) band has emerged as an essential component in dealing with the ever-increasing volume of data traffic and meeting the growing need for broader coverage and higher data rates in the 6G and future wireless networks. Its potential impact is tremendous, as it can greatly enhance a diverse range of applications such as Internet of Everything (IoE) and Unmanned aerial vehicles (UAVs). UAV-enabled THz technology is expected to play a major role in next generation wireless communications. However, the obstacles to utilize THz communication for UAV are challenging due to THz limitations and the mobility of UAVs. For example, increasing the transmission range of a signal in sub-Terahertz (0.1-10 THz) frequency band has been a challenge due to its vapor loss and molecular absorption. It is more challenging in UAV communications because of dynamic network topology and weather conditions. The focus of this dissertation is to improve physical layer security and minimizing path loss in THz-enabled UAV communication systems. A channel model is established specifically for THz-enabled UAVs. Additionally, UM-MIMO is evaluated across three distinct frequency bands (0.06, 0.3, and 1 THz). We have proposed an optimization problem that maximizes the secrecy rate of UAVs in the sub-THz band by optimizing their trajectories and transmit power jointly. To solve this optimization problem, we have designed an iteration algorithm based on Successive Convex Approximation. To enhance the achievable average secrecy rate for UAV ground communications, we have utilized UM-MIMO and a cooperative UAV jamming strategy. Furthermore, we studied THz channel model for line-of-sight (LoS) and non-line of sight (NLoS) for UAV communication and examined its physical layer security under different scenarios. Additionally, we investigated UAV trajectories in sub-THz band and its effect on the secrecy rate of the UAVs communication. Moreover, we present a novel secure UAV-assisted mobile relaying system operating at THz bands for a cognitive relay network. We have developed a PUF-based mutual authentication solution that exploits the physical-layer properties of communication links. We leverage the growing popularity of MIMO in wireless communication. This approach incorporates hardware-based security primitives, namely physically unclonable functions (PUFs), and physical-layer communication mechanism (MIMO). This protocol allows a UAV and a ground user to authenticate each in a distributed manner.43 0