[ES] Para proporcionar un entorno de tráfico vial más seguro y eficiente, los sistemas ITS o Sistemas Inteligentes de Transporte representan como una solución dotada de avances tecnológicos de vanguardia. La integración de elementos de transporte como automóviles junto con elementos de infraestructura como RoadSide Units (RSUs) ubicados a lo largo de la vía de comunicación permiten ofrecer un entorno de red conectado con múltiples servicios, incluida conectividad a Internet. Esta integración se conoce con el término C-ITS o Sistemas Inteligentes de Transporte Cooperativos. La conexión de automóviles con dispositivos de infraestructura permite crear redes vehiculares conectadas (V2X) vehículo a dispositivos, que ofrecen la posibilidad de nuevos despliegues en aplicaciones C-ITS como las relacionadas con la seguridad. Hoy en día, con el uso masivo de teléfonos inteligentes y debido a su flexibilidad y movilidad, existen varios esfuerzos para integrarlos con los automóviles. De hecho, con el soporte adecuado de unidad a bordo (OBU), los teléfonos inteligentes se pueden integrar perfectamente con las redes vehiculares, permitiendo a los conductores usar sus teléfonos inteligentes como dispositivos de bordo a que participan en los servicios C-ITS, con el objeto de mejorar la seguridad al volante entre otros. Tópico este, que hoy día representa un tema relevante de investigación. Un problema a solucionar surge cuando las comunicaciones vehiculares sufren inferencias y bloqueos de la señal debidos al escenario. De hecho, el impacto de la vegetación y los edificios, ya sea en áreas urbanas y rurales, puede afectar a la calidad de la señal. Algunas estrategias para mejorar la comunicación vehicular en este tipo de entorno consiste en desplegar UAVs o vehículo aéreo no tripulado (drones), los cuales actúan como enlaces de comunicación entre vehículos. De hecho, UAV ofrece importantes ventajas de implementación, ya que tienen una gran flexibilidad en términos de movilidad, además de un rango de comunicaciones mejorado. Para evaluar la calidad de las comunicaciones, debe realizarse un conjunto de mediciones. Sin embargo, debido al costo de las implementaciones reales de UAV y automóviles, los experimentos reales podrían no ser factibles para actividades de investigación con recursos limitados. Por lo tanto, los experimentos de simulación se convierten en la opción preferida para evaluar las comunicaciones entre UAV y vehículos terrestres. Lograr modelos de propagación de señal correctos y representativos que puedan importarse a los entornos de simulación se vuelve crucial para obtener un mayor grado de realismo, especialmente para simulaciones que involucran el movimiento de UAVs en cualquier lugar del espacio 3D. En particular, la información de elevación del terreno debe tenerse en cuenta al intentar caracterizar los efectos de propagación de la señal. En esta tesis doctoral, proponemos nuevos enfoques tanto teóricos como empíricos para estudiar la integración de redes vehiculares que combinan automóviles y UAVs, así mismo el impacto del entorno en la calidad de las comunicaciones. Esta tesis presenta una aplicación, una metodología de medición en escenarios reales y un nuevo modelo de simulación, los cuales contribuyen a modelar, desarrollar e implementar servicios C-ITS. Más específicamente, proponemos un modelo de simulación que tiene en cuenta las características del terreno en 3D, para lograr resultados confiables de comunicación entre UAV y vehículos terrestres. / [CAT] Per a proporcionar un entorn de trànsit viari més segur i eficient, els sistemes ITS o Sistemes Intel·ligents de Transport representen una solució dotada d'avanços tecnològics d'avantguarda. La integració d'elements de transport com auto móvils juntament amb elements d'infraestructura com Road Side Units (RSUs) situats al llarg de lav via de comunicació permeten oferir un entorn de xarxa connectat amb multiples serveis, inclusa connectivitat a Internet. Aquesta integració es connex amb el terme C-ITS o Sistemes Intel·ligents de Transport Cooperatius , com ara els automòbils, amb elements d'infraestructura, com ara les road side units (RSU) o pals situats al llarg de la carretera, per a aconseguir un entorn de xarxa que oferisca nous serveis a més de connectivitat a Internet. Aquesta integració s'expressa amb el terme C-ITS, o sistemes intel·ligents de transport cooperatius. La connexió d'automòbils amb dispositius d'infraestructura permet crear xarxes vehiculars connectades (V2X) vehicle a dispositiu, que ofreixen la possibilitat de nous desplegaments en aplicacions C-ITS, com ara les relacionades amb la seguretat. Avui dia, amb l'ús massiu dels telèfons intel·ligents, i a causa de la flexibilitat i mobilitat que presenten, es fan esforços per integrar-los amb els automòbils. De fet, amb el suport adequat d'unitat a bord (OBU), els telèfons intel·ligents es poden integrar perfectament amb les xarxes vehiculars, permetent als conductors usar els seus telèfons intel·ligents com a dispositius per a participar en els serveis de C-ITS, a fi de millorar la seguretat al volant entre altres. Tòpic est, que hui dia representa un tema rellevant d'investigació. Un problema a solucionar sorgeix quan les comunicacions vehiculars ateixen inferències i bloquejos del senyal deguts a l'escenari. De fet, l'impacte de la vegetació i els edificis, tant en àrees urbanes com rurals, pot afectar la qualitat del senyal. Algunes estratègies de millorar la comunicació vehicular en aquest tipus d'entorn consisteix a desplegar UAVs o vehicles aeris no tripulats (drones), els quals actuen com a enllaços de comunicació entre vehicles. De fet, l'ús d'UAVs ofereix importants avantatges d'implementació, ja que tenen una gran flexibilitat en termes de mobilitat, a més d'un rang de comunicacions millorat. Per a avaluar la qualitat de les comunicacions, s'han de realitzar mesures en escenaris reals. No obstant això, a causa del cost de les implementacions i desplegaments reals d'UAV i el seu ús combinat amb vehicles, aquests experiments reals podrien no ser factibles per a activitats d'investigació amb recursos limitats. Per tant, la metodologia basada en simulació es converteixen en l'opció preferida entre els investigadors per a avaluar les comunicacions entre UAV i vehicles terrestres. Aconseguir models de propagació de senyal correctes i representatius que puguen importar-se als entorns de simulació resulta crucial per a obtenir un major grau de realisme, especialment per a simulacions que involucren el moviment d'UAV en qualsevol lloc de l'espai 3D. En particular, cal tenir en compte la informació d'elevació del terreny per a intentar caracteritzar els efectes de propagació del senyal. En aquesta tesi doctoral proposem enfocaments tant teòrics com empírics per a estudiar la integració de xarxes vehiculars que combinen automòbils i UAV, així com l'impacte de l'entorn en la qualitat de les comunicacions. Aquesta tesi presenta una aplicació, una metodología de mesurament en escenaris reals i un nou model de simulació, els quals contribueixen a modelar, desenvolupar i implementar serveis C-ITS. Més específicament, proposem un model de simulació que té en compte les característiques del terreny en 3D, per a aconseguir resultats fiables de comunicació entre UAV i vehicles terrestres. / [EN] To provide a safer road traffic environment and make it more convenient, Intelligent Transport Systems (ITSs) are proposed as a solution endowed with cutting-edge technological advances. The integration of transportation elements like cars together with infrastructure elements like Road Side Units to achieve a networking environment offers new services in addition to Internet connectivity. This integration comes under the term Cooperative Intelligent Transport System (C-ITS). Connecting cars with surrounding devices forming vehicular networks in Vehicle-to-Everything (V2X) open new deployments in C-ITS applications like safety-related ones. With the massive use of smartphones nowadays, and due to their flexibility and mobility, several efforts exist to integrate them with cars. In fact, with the right support from the vehicle's On-Board Unit (OBU), smartphones can be seamlessly integrated with vehicular networks. Hence, drivers can use their smartphones as a device to participate in C-ITS services for safety purposes, among others, which is a quite interesting research topic. A significant problem arises when vehicular communications face signal obstructions caused by the environment. In fact, the impact of vegetation and buildings, whether in urban and rural areas, can result in a lower signal quality. One way to enhance vehicular communication networks is to deploy Unmanned Aerial Vehicles (UAVs) to act as relays for communication between cars, or ground vehicles. In fact, UAVs offer important deployment advantages, as they offer great flexibility in terms of mobility, in addition to an enhanced communications range. To assess the quality of the communications, a set of measurements must take place. However, due to the cost of real deployments of UAVs and cars, real experiments might not be feasible for research activities with limited resources. Hence, simulation experiments become the preferred option to assess UAV-to- car communications. Achieving correct and representative signal propagation models that can be imported to the simulation environments becomes crucial to obtain a higher degree of realism, especially for simulations involving UAVs moving anywhere throughout the 3D space. In particular, terrain elevation information must be taken into account when attempting to characterize signal propagation effects. In this research work, we propose both theoretical and empirical approaches to study the integration of vehicular networks combining cars and UAVs, and we study the impact of the surrounding environment on the communications quality. An application, a measurement framework, and a simulation model are presented in this thesis in an effort to model, develop, and deploy C-ITS services. More specifically, we propose a simulation model that takes into account 3D terrain features to achieve reliable UAV-to-car communication results. / I want to thank the Spanish government through the Ministry of Economy and Competitiveness (MINECO) and the European Union Commission through the European Social Fund (ESF) for co-financing and granting me the fellowship to fund my studies in Spain and my research stay in Russia. In addition, I would to thank the National Institute of Informatics for granting me the internship fund and the Japanese government through the Japan Society for the Promotion of Science (JSPS) for supporting my research work in Japan. / Hadiwardoyo, SA. (2019). Modelling and Real Deployment of C-ITS by Integrating Ground Vehicles and Unmanned Aerial Vehicles [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/118796 / TESIS

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<div>With the constant advancement of modern radio technology, the safety of radio communication has become a growing concern for us. Communication has become an essential component, particularly in the application of modern technology such as unmanned aerial vehicle (UAV). As a result, it is critical to ensure that a drone can fly safely and reliably while completing duties. Simultaneously, machine learning (ML) is rapidly developing in the twenty-first century. For example, ML is currently being used in social media and digital marking for predicting and addressing users' varies interests. This also serves as the impetus for this thesis. The goal of this thesis is to combine ML and radio communication to identify and classify UAV interference with high accuracy.</div><div>In this work, a ML approach is explored for detecting and classifying jamming attacks against orthogonal frequency division multiplexing (OFDM) receivers, with applicability to UAVs. Four types of jamming attacks, including barrage, protocol-aware, single-tone, and successive-pulse jamming, are launched and analyzed using software-defined radio (SDR). The jamming range, launch complexity, and attack severity are all considered qualitatively when evaluating each type. Then, a systematic testing procedure is established, where a SDR is placed in the vicinity of a drone to extract radiometric features before and after a jamming attack is launched. Traditional ML methods are used to create classification models with numerical features such as signal-to-noise ratio (SNR), energy threshold, and important OFDM parameters. Furthermore, deep learning method (i.e., convolutional neural networks) are used to develop classification models trained with spectrogram images filling in it. Quantitative indicators such as detection and false alarm rates are used to evaluate the performance of both methods. The spectrogram-based model correctly classifies jamming with a precision of 99.79% and a false-alarm rate of 0.03%, compared to 92.20% and 1.35% for the feature-based counterpart.</div>

Measurements of root zone soil moisture play large roles in our understanding of the water cycle, weather, climate, land-heat exchanges, drought forecasting, and agriculture. Current measurements are made using a combination of ground-based sampling and active and passive microwave remote sensing. Signals of Opportunity (SoOp) has emerged as a promising method for sensing soil moisture, using satellite communication signals to make bi-static reflectometry measurements. The current combination of ground and satellite-based measurements for soil moisture results in a gap of useful spatial and temporal resolutions, as well as limited soil penetration depth. This thesis developed and constructed an Unmanned Aerial Vehicle (UAV) mountable, I-band SoOp instrument with calibration capabilities, along with supporting specular point mapping and mission planning software. This work advances the creation of a compact, mobile, root zone soil moisture (RZSM) remote sensing system.

[ES] Aquesta tesi presenta els resultats de la feina de recerca dut a terme sobre el modelatge i el disseny de controladors per a micro-aeronaus no tripulades mitjançant tècniques d'optimització multi-objectiu. Dos principals camps d'estudi estan presents al llarg d'ella. D'una banda, l'estudi de com modelar i controlar plataformes aèries de petita envergadura. I, de l'altra, l'estudi sobre l'ús de tècniques heurístiques d'optimització multi-objectiu per aplicar en el procés de parametrització de models i controladors en micro-aeronaus no tripulades. S'obtenen com a resultat principal una sèrie d'eines que permeten prescindir d'experiments en túnels de vent o de sensòrica d'alt cost, passant directament a la utilització de dades de vol experimental a la identificació paramètrica de models dinàmics. A més, es demostra com la utilització d'eines d'optimització multi-objectiu en diferents fases de desenvolupament de controladors ajuda a augmentar el coneixement sobre la plataforma a controlar i augmenta la fiabilitat i robustesa dels controladors desenvolupats, disminuint el risc de passar de les fases prèvies de el disseny a la validació en vol real. / [CA] Esta tesis presenta los resultados del trabajo de investigación llevado a cabo sobre el modelado y el diseño de controladores para micro-aeronaves no tripuladas mediante técnicas de optimización multi-objetivo. Dos principales campos de estudio están presentes a lo largo de ella. Por un lado, el estudio de cómo modelar y controlar plataformas aéreas de pequeña envergadura. Y, por otro, el estudio sobre el empleo de técnicas heurísticas de optimización multi-objetivo para aplicar en el proceso de parametrización de modelos y controladores en micro-aeronaves no tripuladas. Se obtienen como resultado principal una serie de herramientas que permiten prescindir de experimentos en túneles de viento o de sensórica de alto coste, pasando directamente a la utilización de datos de vuelo experimental en la identificación paramétrica de modelos dinámicos. Además, se demuestra como la utilización de herramientas de optimización multi-objetivo en diferentes fases del desarrollo de controladores ayuda a aumentar el conocimiento sobre la plataforma a controlar y aumenta la fiabilidad y robustez de los controladores desarrollados, disminuyendo el riesgo de pasar de las fases previas del diseño a la validación en vuelo real. / [EN] This thesis presents the results of the research work carried out on the modelling and design of controllers for micro-unmanned aerial vehicles by means of multi-objective optimization techniques. Two main fields of study are present throughout it. On one hand, the study of how to model and control small aerial platforms. And, on the other, the study on the use of heuristic multi-objective optimization techniques to apply in the process of models and controllers parameterization in micro-unmanned aerial vehicles. The main result is a series of tools that make it possible manage without wind tunnel experiments or high-cost air-data sensors, going directly to the use of experimental flight data in the parametric identification of dynamic models. In addition, a demonstration is given on how the use of multi-objective optimization tools in different phases of controller development helps to increase knowledge about the platform to be controlled and increases the reliability and robustness of the controllers developed, reducing the risk of hoping from the initial design phases to validation in real flight. / Velasco Carrau, J. (2020). Unmanned Aerial Vehicles Modelling and Control Design. A Multi-Objective Optimization Approach [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/156034 / TESIS

<p>Unmanned aerial vehicles (UAVs) equipped with imaging systems and integrated global navigation satellite system/inertial navigation system (GNSS/INS) are used for a variety of applications. Disaster relief, infrastructure monitoring, precision agriculture, and ecological forestry growth monitoring are among some of the applications that utilize UAV imaging systems. For most applications, accurate 3D spatial information from the UAV imaging system is required. Deriving reliable 3D coordinates is conditioned on accurate geometric calibration. Geometric calibration entails both spatial and temporal calibration. Spatial calibration consists of obtaining accurate internal characteristics of the imaging sensor as well as estimating the mounting parameters between the imaging and the GNSS/INS units. Temporal calibration ensures that there is little to no time delay between the image timestamps and corresponding GNSS/INS position and orientation timestamps. Manual and automated spatial calibration have been successfully accomplished on a variety of platforms and sensors including UAVs equipped with frame and push-broom line cameras. However, manual and automated temporal calibration has not been demonstrated on both frame and line camera systems without the use of ground control points (GCPs). This research focuses on manual and automated spatial and temporal system calibration for UAVs equipped with GNSS/INS frame and line camera systems. For frame cameras, the research introduces two approaches (direct and indirect) to correct for time delay between GNSS/INS recorded event markers and actual time of image exposures. To ensure the best estimates of system parameters without the use of ground control points, an optimal flight configuration for system calibration while estimating time delay is rigorously derived. For line camera systems, this research presents the direct approach to estimate system calibration parameters including time delay during the bundle block adjustment. The optimal flight configuration is also rigorously derived for line camera systems and the bias impact analysis is concluded. This shows that the indirect approach is not a feasible solution for push-broom line cameras onboard UAVs due to the limited ability of line cameras to decouple system parameters and is confirmed with experimental results. Lastly, this research demonstrates that for frame and line camera systems, the direct approach can be fully-automated by incorporating structure from motion (SfM) based tie point features. Methods for feature detection and matching for frame and line camera systems are presented. This research also presents the necessary changes in the bundle adjustment with self-calibration to successfully incorporate a large amount of automatically-derived tie points. For frame cameras, the results show that the direct and indirect approach is capable of estimating and correcting this time delay. When a time delay exists and the direct or indirect approach is applied, horizontal accuracy of 1–3 times the ground sampling distance (GSD) can be achieved without the use of any ground control points (GCPs). For line camera systems, the direct results show that when a time delay exists and spatial and temporal calibration is performed, vertical and horizontal accuracy are approximately that of the ground sample distance (GSD) of the sensor. Furthermore, when a large artificial time delay is introduced for line camera systems, the direct approach still achieves accuracy less than the GSD of the system and performs 2.5-8 times better in the horizontal components and up to 18 times better in the vertical component than when temporal calibration is not performed. Lastly, the results show that automated tie points can be successfully extracted for frame and line camera systems and that those tie point features can be incorporated into a fully-automated bundle adjustment with self-calibration including time delay estimation. The results show that this fully-automated calibration accurately estimates system parameters and demonstrates absolute accuracy similar to that of manually-measured tie/checkpoints without the use of GCPs.</p>

Unmanned Aerial Vehicles, often called drones or abbreviated as UAVs, have been popularised and used by civilians for recreational use since the early 2000s. A majority of the entry- level commercial drones on the market are based on a WiFi connection with a controller, usually a smart phone. This makes them vulnerable to various WiFi attacks, which are evaluated and tested in this thesis, specifically on the Ryze Tello drone. Several threats were identified through threat modelling, in which a set of them was selected for penetration testing. This is done in order to answer the research question: How vulnerable is the Ryze Tello drone against WiFi based attacks? The answer to the research question is that the Ryze Tello drone is relatively safe, with the exception of it not having a default password for the network. A password was set for the network, however it was still exploited through a dictionary attack. This enabled attacks such as injecting flight instructions as well as the ability to gain access to the video feed of the drone while simultaneously controlling it through commands in terminal. / Drönare, eller UAV från engelskans Unmanned Aerial Vehicle, har ökat i popularitet bland privatpersoner sedan tidigt 2000tal. En majoritet av drönare för nybörjare är baserade på WiFi och styrs med en kontroll som vanligtvis är en smart phone. Detta innebär att dessa drönare kan vara sårbara för olika typer av attacker på nätverket, vilket utvärderas och testas i denna rapport på drönaren Ryze Tello. Flera hot identifierades med hotmodellering och ett flertal valdes ut för penetrationtest. Detta genomförs med syftet att svara på forskningsfrågan: Hur sårbar är Ryze Tello mot WiFi baserade attacker? Svaret på forskningsfrågan är att drönaren Ryze Tello är relativt säker, med undantaget att den inte har ett standardlösenord. Ett lösenord sattes på nätverket, men lösenordet knäcktes ändå med en ordboksattack. Detta möjliggjorde attacker så som instruktionsinjicering och förmågan att se videoströmmen från drönaren samtidigt som den kan kontrolleras via kommandon i terminalen.

<p>Safety Management Systems (SMS) in the aviation industry is increasingly an essential aspect of identifying hazards and managing the associated risks. While SMS has become commonplace and is often a regulatory requirement for air carriers, it remains voluntary for many other aviation service providers such as airports. Over the past decade, commercial UAS operations have significantly increased, leading to safety and economic challenges for airports. This research studied the current state of SMS and commercial UAS operations at airports. This research utilized a mix of quantitative and qualitative methods, which included an extensive literature review, interviews, and a survey of airport stakeholders. The literature review confirmed an increase in UAS hazards and risks within the airport operating area coupled with immature SMS practices that address these UAS operations. To build on the findings from the review of literature, a survey instrument was developed, distributed to airport stakeholders, and the responses were statistically analyzed. To gain greater insight into these findings, researchers interviewed three airport subject matter experts. The study compared the airports current state of SMS with UAS operations, the airport stakeholder’s level of familiarity with related policies, and their need for additional UAS SMS guidance material or training. Research results suggest a need for further development and adoption of robust SMS practices at airports along with education and training. This study may assist airport stakeholders, UAS operators, and regulators to further develop robust safety and risk management practices that support safe UAS operations within the airport operating area.</p>

The Micro Aerial Vehicless (MAVs) are gaining attention in numerous applications asthese platforms are cheap and can do complex maneuvers. Moreover, most of the commer-cially available MAVs are equipped with a mono-camera. Currently, there is an increasinginterest to deploy autonomous mono-camera MAVs with obstacle avoidance capabilitiesin various complex application areas. Some of the application areas have moving obstaclesas well as stationary, which makes it more challenging for collision avoidance schemes.This master thesis set out to investigate the possibility to avoid moving and station-ary obstacles with a single camera as the only sensor gathering information from thesurrounding environment.One concept to perform autonomous obstacle avoidance is to predict the time near-collision based on a Convolution Neural Network (CNN) architecture that uses the videofeed from a mono-camera. In this way, the heading of the MAV is regulated to maximizethe time to a collision, resulting in the avoidance maneuver. Moreover, another interestingperspective is when due to multiple dynamic obstacles in the environment there aremultiple time predictions for different parts of the Field of View (FoV). The method ismaximizing time to a collision by choosing the part with the largest time to collision.However, this is a complicated task and this thesis provides an overview of it whilediscussing the challenges and possible future directions. One of the main reason was thatthe available data set was not reliable and was not provide enough information for theCNN to produce any acceptable predictions.Moreover, this thesis looks into another approach for avoiding collisions, using objectdetection method You Only Lock Once (YOLO) with the mono-camera video feed. YOLOis a state-of-the-art network that can detect objects and produce bounding boxes in real-time. Because of YOLOs high success rate and speed were it chosen to be used in thisthesis. When YOLO detects an obstacle it is telling where in the image the object is,the obstacle pixel coordinates. By utilizing the images FoV and trigonometry can pixelcoordinates be transformed to an angle, assuming the lens does not distort the image.This position information can then be used to avoid obstacles. The method is evaluated insimulation environment Gazebo and experimental verification with commercial availableMAV Parrot Bebop 2. While the obtained results show the efficiency of the method. To bemore specific, the proposed method is capable to avoid dynamic and stationary obstacles.Future works will be the evaluation of this method in more complex environments with multiple dynamic obstacles for autonomous navigation of a team of MAVs. A video ofthe experiments can be viewed at:https://youtu.be/g_zL6eVqgVM.

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