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This dissertation explores the realm of high-accuracy localization through the utilization of ranging-based techniques, encompassing a spectrum of signals ranging from low-frequency ultrasound acoustic signals to more intricate high-frequency signals like Wireless Fidelity (Wi-Fi) IEEE 802.11az, 5G New Radio (NR), and 6G. Moreover, another contribution is the conception of a novel timing mechanism and synchronization protocol grounded in tunable quantum photonic oscillators. In general, our primary focus is to facilitate precise indoor localization, where conventional GPS signals are notably absent. To showcase the significance of this innovation, we present two vital use cases at the forefront: drone localization and metaverse user positioning. In the context of indoor drone localization, the spectrum of applications ranges from recreational enthusiasts to critical missions requiring pinpoint accuracy. At the hobbyist level, drones can autonomously navigate intricate indoor courses, enriching the recreational experience. As a finer illustration of a hobbyist application, consider the case of ``follow me drones". These specialized drones are tailored for indoor photography and videography, demanding an exceptionally accurate autonomous flight capability. This precision is essential to ensure the drone can consistently track and capture its designated subject, even as it moves within the confined indoor environment. Moving on from hobby use cases, the technology extends its profound impact to more crucial scenarios, such as search and rescue operations within confined spaces. The ability of drones to localize with high precision enhances their autonomy, allowing them to maneuver seamlessly, even in environments where human intervention proves challenging. Furthermore, the technology holds the potential to revolutionize the metaverse. Within the metaverse, where augmented and virtual realities converge, the importance of high-accuracy localization is amplified. Immersive experiences like Augmented/Virtual/Mixed Reality (AR/VR/MR) gaming rely heavily on precise user positioning to create seamless interactions between digital and physical environments. In entertainment, this innovation sparks innovation in narrative design, enhancing user engagement by aligning virtual elements with real-world surroundings. Beyond entertainment, applications extend to areas like telemedicine, enabling remote medical procedures with virtual guidance that matches physical reality. In light of all these examples, the imperative for an advanced high-accuracy localization system has become increasingly pronounced. The core objective of this dissertation is to address this pressing need by engineering systems endowed with exceptional precision in localization. Among the array of potential techniques suitable for GPS-absent scenarios, we have elected to focus on ranging-based methods. Specifically, our methodologies are built upon the fundamental principles of time of arrival, time difference of arrival, and time of flight measurements. In essence, each of our devised systems harnesses the capabilities of beacons such as ultrasound acoustic sensors, 5G femtocells, or Wi-Fi access points, which function as the pivotal positioning nodes. Through the application of trilateration techniques, based on the calculated distances between these positioning nodes and the integrated sensors on the drone or metaverse user side, we facilitate robust three-dimensional localization. This strategic approach empowers us to realize our ambition of creating localization systems that not only compensate for the absence of GPS signals but also deliver unparalleled accuracy and reliability in complex and dynamic indoor environments. A significant challenge that we confronted during our research pertained to the disparity in z-axis localization performance compared to that of the x-y plane. This nuanced yet pivotal concern often remains overlooked in much of the prevailing state-of-the-art literature, which predominantly emphasizes two-dimensional localization methodologies. Given the demanding context of our work, where drones and metaverse users navigate dynamically across all three dimensions, the imperative for three-dimensional localization became evident. To address this, we embarked on a comprehensive analysis, encompassing mathematical derivations of error bounds for our proposed localization systems. Our investigations unveiled that localization errors trace their origins to two distinct sources: errors induced by ranging-based factors and errors stemming from geometric considerations. The former category is chiefly influenced by factors encompassing the quality of measurement devices, channel quality in which the signal communication between the sensor on the user and the positioning nodes takes place, environmental noise, multipath interference, and more. In contrast, the latter category, involving geometry-induced errors, arises primarily from the spatial configuration of the positioning nodes relative to the user. Throughout our journey, we dedicated efforts to mitigate both sources of error, ensuring the robustness of our system against diverse error origins. Our approach entails a two-fold strategy for each proposed localization system. Firstly, we introduce innovative techniques such as Frequency-Hopping Spread Spectrum (FHSS) and Frequency-Hopping Code Division Multiple Access (FH-CDMA) and incorporate devices such as Reconfigurable Intelligent Surfaces (RIS) and photonic oscillators to fortify the system against errors stemming from ranging-related factors. Secondly, we devised novel evolutionary-based optimization algorithms, adept at addressing the complex NP-Hard challenge of optimal positioning node placement. This strategic placement mitigates the impact of geometry-induced errors on localization accuracy across the entire environmental space. By meticulously addressing both these sources of error, our localization systems stand as a testament to comprehensive robustness and accuracy. Our methodologies not only extend the frontiers of three-dimensional localization but also equip the systems to navigate the intricacies of indoor environments with precision and reliability, effectively fulfilling the evolving demands of drone navigation and metaverse user interaction. / Doctor of Philosophy / In this dissertation, we first explore some promising substitutes for the Global Positioning System (GPS) for the autonomous navigation of drones and metaverse user positioning in indoor spaces. Then, we will make the scope of research more comprehensive and try to explore substitutes to GPS for autonomous navigation of drones in general, both in indoor environments and outdoors. For the first part, we make our small indoor GPS. Similar to GPS, in our system, a receiver onboard the drone or the metaverse user can receive signals from our small semi-satellites in the room, and with that, it can localize itself. The idea is very similar to how the well-known GPS works, with some modifications. Unlike the GPS, we are using acoustic ultrasound signals or some RF signal based on 5G or Wi-Fi for transmission. Also, we have more freedom compared to GPS because, in GPS, they have to transmit signals from far ahead distances, whereas, in our scenario, it is just a room in which we put all of our semi-satellite transmitters. Moreover, we can put them anywhere we want in the room. This is, in fact important, because the positions of these semi-satellites have a huge effect on the accuracy of our system. Also, we can decide how many of them we need to cover every point in the room and not have any blind spots. We propose our novel techniques for finding the optimal placement to improve localization accuracy. In GPS, they propose a technique that is suitable for the case of those satellites and their distance to the targets. Similarly, we offer our novel techniques to have a robust transmission against noise and other factors and guarantee a localization scheme with high accuracy. All being said, our proposed system for indoor localization of drones and metaverse users in three dimensions has considered all the possible sources of error and proposed solutions to conquer them; hence a robust system with high accuracy in three-dimensional space.

In recent years, unmanned aerial vehicles (UAVs) have got a boost in their applications in civilian areas like aerial photography, agriculture, communication, etc. An increasing research effort is being exerted to develop sophisticated trajectory prediction methods for UAVs for collision detection and trajectory planning. The existing techniques suffer from problems such as inadequate uncertainty quantification of predicted trajectories. This work adopts particle filters together with Löwner-John ellipsoid to approximate the highest posterior density region for trajectory prediction and uncertainty quantification. The particle filter is tuned and tested on real-world and simulated data sets and compared with the Kalman filter. A parallel computing approach for particle filter is further proposed. This parallel implementation makes the particle filter faster and more suitable for real-time online applications. / Master of Science / In recent years, unmanned aerial vehicles (UAVs) have got a boost in their applications in civilian areas like aerial photography, agriculture, communication, etc. Over the coming years, the number of UAVs will increase rapidly. As a result, the risk of mid-air collisions grows, leading to property damages and possible loss of life if a UAV collides with manned aircraft. An increasing research effort has been made to develop sophisticated trajectory prediction methods for UAVs for collision detection and trajectory planning. The existing techniques suffer from problems such as inadequate uncertainty quantification of predicted trajectories. This work adopts particle filters, a Bayesian inferencing technique for trajectory prediction. The use of minimum volume enclosing ellipsoid to approximate the highest posterior density region for prediction uncertainty quantification is also investigated. The particle filter is tuned and tested on real-world and simulated data sets and compared with the Kalman filter. A parallel computing approach for particle filter is further proposed. This parallel implementation makes the particle filter faster and more suitable for real-time online applications.

In most man-made flight, vehicle control is achieved by deflecting flaps. However, in nature, morphing surfaces are found on both flying and swimming creatures. Morphing is used in nature because it is a more efficient form of control. This thesis investigates using morphing flaps to control a class of UAVs known as ducted fan vehicles. Specifically, this thesis discusses both the challenges and benefits of using morphing control surfaces. To achieve morphing, a piezoelectric device known as Macro Fiber Composites is used. These devices are embedded in the skin of the vehicles control surface, and when actuated, they cause the control surface to increase or decrease camber. This thesis describes experiments that were performed to investigate the performance of this type of actuator. Specifically, the actuation bandwidth of these devices is presented and compared to a servo. Results show that the morphing control surfaces can actuate at frequencies twice as high as a servo. / Master of Science

<p>Low-cost unmanned aerial vehicles (UAVs) utilizing push-broom hyperspectral scanners are poised to become a popular alternative to conventional remote sensing platforms such as manned aircraft and satellites. In order to employ this emerging technology in fields such as high-throughput phenotyping and precision agriculture, direct georeferencing of hyperspectral data using onboard integrated global navigation satellite systems (GNSS) and inertial navigation systems (INS) is required. Directly deriving the scanner position and orientation requires the spatial and rotational relationship between the coordinate systems of the GNSS/INS unit and hyperspectral scanner to be evaluated. The spatial offset (lever arm) between the scanner and GNSS/INS unit can be measured manually. However, the angular relationship (boresight angles) between the scanner and GNSS/INS coordinate systems, which is more critical for accurate generation of georeferenced products, is difficult to establish. This research presents three alternative calibration approaches to estimate the boresight angles relating hyperspectral push-broom scanner and GNSS/INS coordinate systems. For reliable/practical estimation of the boresight angles, the thesis starts with establishing the optimal/minimal flight and control/tie point configuration through a bias impact analysis starting from the point positioning equation. Then, an approximate calibration procedure utilizing tie points in overlapping scenes is presented after making some assumptions about the flight trajectory and topography of covered terrain. Next, two rigorous approaches are introduced – one using Ground Control Points (GCPs) and one using tie points. The approximate/rigorous approaches are based on enforcing the collinearity and coplanarity of the light rays connecting the perspective centers of the imaging scanner, object point, and the respective image points. To evaluate the accuracy of the proposed approaches, estimated boresight angles are used for ortho-rectification of six hyperspectral UAV datasets acquired over an agricultural field. Qualitative and quantitative evaluations of the results have shown significant improvement in the derived orthophotos to a level equivalent to the Ground Sampling Distance (GSD) of the used scanner (namely, 3-5 cm when flying at 60 m).</p>

Sistemas de Transportes Inteligentes (STIs) englobam um conjuntos de tecnologias (Sensoriamento Remoto, Tecnologia da Informação, Eletrônica, Sistemas de Comunicação de Dados entre outros) que visam oferecer serviços e gerenciamento de tráfego avançado para meios de transporte rodoviário, aéreo e outros. A obtenção de informações a respeito das características e das condições do pavimento das estradas constitui uma parte importante dentro do sensoriamento nesses STIs. Investigar novas técnicas, metodologias e meios de automatizar a obtenção dessas informações é parte deste trabalho. Uma vez que existem diferentes tipos de defeitos em vias pavimentadas, esta tese apresenta a proposta de uma metodologia que permite a obtenção, de forma automática, das condições dos pavimentos asfálticos. A obtenção dos dados foi realizada por meio do Sensoriamento Remoto com uso de Veículos Aéreos Não Tripulados. A utilização de técnicas de Aprendizado de Máquina na detecção automática possibilitou alcançar uma acurácia de 99% na detecção de pavimentos asfálticos flexíveis e 92% na identificação de defeitos em alguns experimentos. Como resultado obteve-se o diagnóstico automático, não só das condições da via, mas de diferentes tipos de defeitos presentes em pavimentos. / Intelligent Transport Systems (ITS) is a set of integrated technologies (Remote Sensing, Information Technology, Electronics, Data Communication Systems among others) that aims to provide services and advanced traffic management for road, air, rail and others transportation systems. Obtaining information about characteristics and road pavement conditions is an important part within the sensing these ITS. Investigating new techniques, methods and means to optimize and automate obtaining these information are part of this work, since there are different types of defects on paved roads. Thus, this thesis proposes a methodology that allows automatically obtain information about the condition of the pavement. Data collection was performed with remote sensing technology using Unmanned Aerial Vehicles. Automatic detection was possible through the use of Machine Learning techniques with 99% of accuracy in pavements and 92% in distress identification. As a result we obtained the self-diagnosis, not just the pavement, but different types of distress present in the pavement.

Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2011. / ENGLISH ABSTRACT: The development of a control allocation system for use as part of a fault-tolerant control (FTC) system in unmanned aerial vehicles (UAVs) is presented. This system plays a vital role in minimising the possibility that a fault will necessitate the reconfiguration of the control, guidance or navigation systems of the aircraft by minimising the difference between the desired and achievable aircraft performance parameters. This is achieved by optimising the allocation of control effort commanded by the virtual actuators to the physical actuators present on the aircraft. A simple general six degree of freedom aircraft model is presented that contains all of the relevant terms needed to find the trim biases of the aircraft actuators and evaluate the performance of the virtual actuators. This model was used to develop a control allocation formulation that optimises the performance of the virtual actuators of the aircraft while minimising adverse effects and avoiding actuator saturation. The resulting problem formulation was formulated as a multi-objective optimisation problem which was solved using the sequential quadratic programming method. The control allocation system was practically implemented and tested. A number of failure categories of varying severity were defined and two aircraft with different levels of actuator redundancy were used to test the system. The control allocation algorithm was evaluated for each failure category, aircraft test case and for a number of differing control allocation system configurations. A number of enhancements were then made to the control allocation system which included adding frequency-based allocation and adapting the algorithm for an unconventional ducted-fan UAV. The control allocation system is shown to be applicable to a number of different conventional aircraft configurations with no alterations as well as being applicable to unconventional aircraft with minor alterations. The control allocation system is shown to be capable of handling both single and multiple actuator failures and the importance of actuator redundancy is highlighted as a factor that influences the effectiveness of control allocation. The control allocation system can be effectively used as part of a FTC system or as a tool that can be used to investigate control allocation and aircraft redundancy. / AFRIKAANSE OPSOMMING: Die ontwikkeling van ’n beheertoekenning sisteem vir gebruik as deel van ’n fout verdraagsame beheersisteem in onbemande lugvaartuie word voorgelê. Hierdie sisteem speel ’n essensiële rol in die vermindering van die moontlikheid dat ’n fout die herkonfigurasie van die beheer, bestuur of navigasiesisteme van die vaartuig tot gevolg sal hê, deur die verskil te verminder tussen die verlangde en bereikbare werkverrigtingsraamwerk van die vaartuig. Dit word bereik deur die optimisering van die toekenning van beheerpoging aangevoer deur die virtuele aktueerders na die fisiese aktueerders teenwoordig op die vaartuig. ’n Eenvoudige algemene ses grade van vryheid lugvaartuig model word voorgestel wat al die relevante terme bevat wat benodig word om die onewewigtigheid verstelling van die vaartuig se aktueerders te vind en die werksverrigting van die virtuele aktueerders te evalueer. Hierdie model is gebruik om ’n beheer toekenning formulering te ontwikkel wat die werkverrigting van die virtuele aktueerders van die vaartuig optimiseer terwyl nadelige gevolge verminder word asook aktueerder versadiging vermy word. Die gevolglike probleem formulering is omskryf as ’n multi-doel optimiserings probleem wat opgelos is deur gebruik van die sekwensiële kwadratiese programmerings metode. Die beheertoekenning sisteem is prakties geïmplementeer en getoets. ’n Aantal fout kategorieë van verskillende grade van erns is gedefinieer en twee vaartuie met verskillende vlakke van aktueerder oortolligheid is gebruik om die sisteem te toets. Die beheer toekenning algoritme is geëvalueer vir elke fout kategorie, vaartuig toetsgeval, asook vir ’n aantal verskillende beheertoekenning sisteem konfigurasies. ’n Aantal verbeterings is aangebring aan die beheertoekenning sisteem, naamlik die toevoeging van frekwensie gebaseerde toekenning en wysiging van die algoritme vir ’n onkonvensionele onbemande geleide waaier lugvaartuig. Die beheertoekenning sisteem is van toepassing op ’n aantal verskillende konvensionele vaartuig konfigurasies met geen verstellings asook van toepassing op onkonvensionele vaartuie met geringe verstellings. Die beheertoekenning sisteem kan beide enkel- en veelvoudige aktueerder tekortkominge hanteer en die belangrikheid van aktueerder oortolligheid is beklemtoon as ’n faktor wat die effektiwiteit van beheertoekenning beïnvloed. Die beheertoekenning sisteem kan effektief geïmplementeer word as deel van ’n fout verdraagsame beheersisteem of as ’n werktuig om beheertoekenning en vaartuig oortolligheid te ondersoek.

Sistemas de Transportes Inteligentes (STIs) englobam um conjuntos de tecnologias (Sensoriamento Remoto, Tecnologia da Informação, Eletrônica, Sistemas de Comunicação de Dados entre outros) que visam oferecer serviços e gerenciamento de tráfego avançado para meios de transporte rodoviário, aéreo e outros. A obtenção de informações a respeito das características e das condições do pavimento das estradas constitui uma parte importante dentro do sensoriamento nesses STIs. Investigar novas técnicas, metodologias e meios de automatizar a obtenção dessas informações é parte deste trabalho. Uma vez que existem diferentes tipos de defeitos em vias pavimentadas, esta tese apresenta a proposta de uma metodologia que permite a obtenção, de forma automática, das condições dos pavimentos asfálticos. A obtenção dos dados foi realizada por meio do Sensoriamento Remoto com uso de Veículos Aéreos Não Tripulados. A utilização de técnicas de Aprendizado de Máquina na detecção automática possibilitou alcançar uma acurácia de 99% na detecção de pavimentos asfálticos flexíveis e 92% na identificação de defeitos em alguns experimentos. Como resultado obteve-se o diagnóstico automático, não só das condições da via, mas de diferentes tipos de defeitos presentes em pavimentos. / Intelligent Transport Systems (ITS) is a set of integrated technologies (Remote Sensing, Information Technology, Electronics, Data Communication Systems among others) that aims to provide services and advanced traffic management for road, air, rail and others transportation systems. Obtaining information about characteristics and road pavement conditions is an important part within the sensing these ITS. Investigating new techniques, methods and means to optimize and automate obtaining these information are part of this work, since there are different types of defects on paved roads. Thus, this thesis proposes a methodology that allows automatically obtain information about the condition of the pavement. Data collection was performed with remote sensing technology using Unmanned Aerial Vehicles. Automatic detection was possible through the use of Machine Learning techniques with 99% of accuracy in pavements and 92% in distress identification. As a result we obtained the self-diagnosis, not just the pavement, but different types of distress present in the pavement.

Conservation of elasmobranch populations is often inhibited by a lack of data, particularly in understudied regions like the Red Sea. Survey efforts in this region have been infrequent and often highly localized. Establishing a broad baseline for elasmobranch diversity and abundance along the Saudi Arabian Red Sea coast could inform both conservation efforts and a nascent ecotourism industry. In this thesis, I describe a pilot study comparing biodiversity data from baited remote underwater video stations (BRUVS), unoccupied aerial vehicle surveys (UAVs), and eDNA sequencing at five islands in the Farasan Banks region of the Saudi Arabian Red Sea. Estimates of relative abundance were also compared between the BRUVS and UAVs. Each method identified species missed by the other two, but all three techniques exhibited clear habitat- and taxa-specific biases. I was able to identify key concerns for each approach that need to be addressed before large-scale implementation. If carefully planned and executed well, a full assessment of the Saudi Arabian coastline could establish a true baseline for shallow water elasmobranchs in the eastern Red Sea. Informing best conservation practices and identifying potential ecological attractions in accordance the environmental and economic goals of Saudi Arabia’s Vision 2030.

[pt] O crescente uso de veículos aéreos não tripulados (VANTs) em diversos setores da sociedade é fruto de avanços da tecnologia. Por sua vez, a ampliação de aplicações de VANTs traz consigo a necessidade de aumento de robustez destes sistemas, especialmente em ambientes compartilhados com o ser humano. A presente dissertação aborda o desenvolvimento de uma plataforma para testes de veículos multicópteros, com o objetivo de contribuir para o processo de desenvolvimento e implementação de drones, permitindo sua movimentação em torno dos seus graus de liberdade de rotação e realizando medições de atitude e força geradas pelo sistema, sem colocar o veículo ou seu operador em risco. Todos os dados adquiridos pela plataforma são transmitidos para um computador, onde foi desenvolvida uma interface virtual para sua visualização em tempo real, além de permitir armazenamento para pós-processamento e análises futuras. Também apresenta-se e discute-se o desenvolvimento do simulador de trajetórias proposto, que mostra o deslocamento do veículo em função da sequência de comandos fornecida, com base nos dados adquiridos pela plataforma. No intuito de se propiciar um melhor entendimento do funcionamento do sistema aqui desenvolvido, é apresentado um estudo detalhado dos subsistemas que compõem um multicóptero, bem como do processo de modelagem dinâmica de um veículo quadricóptero, por meio da técnica de grafos de ligação. A modelagem do veículo é complementada com a identificação de parâmetros fundamentais para a implementação do modelo, sendo discutidos métodos para identificação de parâmetros inerciais do veículo e parâmetros dinâmicos do sistema motopropulsor. / [en] The growing use of unmanned aerial vehicles (UAVs) in various sectors of society is a result of advances in technology. In turn, the expansion of UAV applications brings with it the need to increase the robustness of these systems, especially in environments shared with humans. and comes together with the need for increased robustness due to its use in shared environments with humans. This dissertation approaches the development of a platform for testing multicopter vehicles aiming at assisting the process of developing and implementing drones, allowing movements around their rotational degrees of freedom and making measurements of attitude and forces generated by the system, without putting the vehicle or its operator at risk. All data acquired by the platform is transmitted to a computer, where a virtual interface was developed to provide real time visualization, in addition to allowing data storage for post-processing and future analysis. The development of the proposed trajectory simulator is also presented and discussed, that shows the displacement of the vehicle as a function of the sequence of commands provided, based on the acquired data. Aiming at allowing a better understanding of the functioning of the developed system, a detailed study of the subsystems that compose a multicopter is presented, as well as the process of dynamic modeling of a quadcopter vehicle, by using bond graph technique. The modeling of the vehicle is complemented with the identification of fundamental parameters for the model implementation, such as methods for the identification of inertial parameters of the vehicle and dynamics of the powertrain system.