Development of improvements in UAS for difficult access environments

The objective of this document is to study and verify the development and improvements in Unmanned Aircraft Systems (UAS) for difficult access environments since this matter is a critical area of research and innovation. As the use of UAS in various applications continues to expand, the need for these systems to operate in challenging environments such as mountainous terrain, dense forests, or urban areas with high-rise structures is increasing. The main motivation to start developing this project was the challenge exposed in the Xprize Rainforest Competition. The $10M XPRIZE Rainforest is a five-year competition to enhance the understanding of the rainforest ecosystem. I am part of the semifinalist team, Providence Plus, a multidisciplinary team composed by scientists from UPC, CSIC, MIT, and TUDelf. The purpose of this challenge is to obtain the maximum amount of information on biodiversity in the rainforest, using drone technology in this type of environment, with all the difficulties inherent in this environment that must be overcome and that are also the subject of analysis in this work, to propose and compare the different solutions and technologies to achieve the objectives of said challenge. As resources for competing in Xprize Challenge are limited and the final solution shall be scalable, the technologies evaluated must be cost efficient and practical. The first difficulty in this kind of environments is the signal strength and signal quality, not only for the drone commands but for the video and telemetry data. In this work, different solutions will be compared since analogic to digital technology. The second difficulty is autonomy, in terms of energetic supply. Taking into account the Rainforest environment and environmental policies, the most suitable technology available is batteries. There are several types of batteries that are suitable for drones, depending on the size, weight, and specifications of the drone. There will be a comparison between the most popular ones. Apart from that, an analysis of different propulsion configurations (ideal motors and propellers) will be carried out in order to achieve an optimal flight time without compromising the structural integrity of the drone. The third difficulty is reducing noise levels, in order to avoid disturbing the wildlife and with the goal in mind of having the best images possible, a study of different propellers will be carried out. Finally, durability and weather resistance: Rainforests are characterized by high humidity, heavy rainfall, and extreme heat. Drones used in this environment must be built to withstand these conditions and be weather-resistant. This may involve using materials that can withstand moisture, designing waterproof housing for sensitive components, and installing heat dissipation systems to prevent overheating.Objectius de Desenvolupament Sostenible::15 - Vida d'Ecosistemes TerrestresObjectius de Desenvolupament Sostenible::13 - Acció per al Clim

UAV based GNSS reflectometry

This project combines GNSS-R technology and UAVs in the context of the aerial remote sensing field, from the design of the assembly of the UAVs and GNSS-R to the execution of the different tests, as well as the data collection and analysis. As it will be seen in the document, this analysis has allowed to improve the original design of the system. The remote sensing technology based on GNSS reflected signals is simply called GNSS-R, and the greatest advantage of UAV as a mounting platform is the low cost, high system availability, and fast installation. Thus the main task of this project is to experimentally verify the possibility of CTTC's own developed GNSS-R working with UAVs. In this report, first I explain some basic principles of GNSS and GNSS-R, as they are important technical backgrounds for the whole project. Secondly, I describe the application of the RTKPOST software, which is an important processing and analyzing tool in the entire project, mainly describing the positioning methods used in the different processing modes in RTKPOST, also the parameter needed for analysis. Then, the design of the UAV-GNSS-R assembly is discussed, with different options based on the characteristics of the UAV, such as weight, payload space, and so on. The whole experimental process is also explained, and all the test data are analyzed and processed by using the Static mode or Kinematic mode in RTKPOST, and the data results are analyzed and compared in terms of satellite visibility, signal-to-noise ratio, elevation angle, Standard Deviation and Root Mean Square. The experimental process is roughly divided into three parts. The initial verification test is used to collect signal data as a basis, through which it is found that drone interferes with GNSS-R to a greater extent, and that the reflector antenna cannot receive the signal if the drone is placed too close to the ground. The second part of the experiment is a stationary test, where the UAV is placed on a tripod, and it's found that there is a difference in accuracy when the UAV is working on different land surfaces, which a higher accuracy can be obtained on rock than on grassy field. It is also found that the interference problem can be mitigated when the receiver is placed farther away from the UAV body. In the last part of the flight test, the optimization of the interference problem is further confirmed by the comparison of the two flight tests, and the positioning error is reduced from about 50m to 6m. At the end of the report, suggestions are given for the future development of this project, as it is clear that the meter-level accuracy does not meet the needs of many applications, and that the integration of the UAS and GNSS-R needs to be further optimized to reduce interference problems and thus achieve higher accuracy positioning.Objectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats Sostenible

Система автоматизованого проектування мобільного комплексу дистанційного забезпечення примусового сходу снігових лавин

Робота публікується згідно наказу Ректора НАУ від 27.05.2021 р. №311/од "Про розміщення кваліфікаційних робіт здобувачів вищої освіти в репозиторії університету". Керівник роботи: к.т.н., професор кафедри авіаційних комп’ютерно-інтегрованих комплексів, Аблесімов Олександр КостянтиновичEffective use of cannons for avalanche control is limited by their small ranges of 1000-1500m of firing with a low probability of P = 0.15 of hitting the designated area. In this case, the noise created by the gun shot can cause the ascent of other avalanches not provided by the plan. However, for safety reasons, it is necessary to ensure reliable (Р = 0.9) forced avalanches from large distances with minimal damage to the rest of the territory. This task can be solved by the use of mobile high-precision complexes for remote support of forced avalanches. Since the composition and technical design of the basic components of such complexes can be very different, it is advisable to use automated systems in their design. Design automation is understood as optimization of decisions, i.e. achievement of the specified indicators of the designed object with limited expenditure of available resources. The structure of the computer-aided design system is a set of subsystems that should include technical, mathematical and information tools, united by a common objective function. A design procedure in the processes of computer-aided design is called typical if it is intended for repeated use in the design of a given object. Mathematical support of computer aided design system serves to provide the designer with a wide range of services on design technology. The computer aided design system software is made taking into account the skeleton computers, which are equipped with the designed system.Ефективність використання гармат для ліквідації лавин обмежується їх невеликими дальностями стрільби 1000-1500 м з низькою ймовірністю ураження P = 0,15 у визначену місцевість. У цьому випадку створюваний пострілом шум може викликати сходження інших лавин, не передбачених планом. Однак з міркувань безпеки це необхідно забезпечити надійне (Р = 0,9) форсування лавин з великих відстаней з мінімальним пошкодженням решти території. Це завдання може бути вирішене використанням мобільних високоточних комплексів дистанційного супроводу сходження лавин. Оскільки склад і технічне виконання основних вузлів таких комплексів можуть бути дуже різними, при їх проектуванні доцільно використовувати автоматизовані системи. Під автоматизацією проектування розуміється оптимізація рішень, тобто досягнення заданих показників проектованого об'єкта при обмежених витратах наявних ресурсів. Структура системи автоматизованого проектування – це сукупність підсистем, яка повинна включати технічні, математичні та інформаційні засоби, об’єднані спільною цільовою функцією. Процедура проектування в процесах автоматизованого проектування називається типовою, якщо вона призначена для багаторазового використання при проектуванні даного об'єкта. Математичне забезпечення системи автоматизованого проектування служить для надання проектувальнику широкого спектру послуг з технології проектування. Програмне забезпечення системи автоматизованого проектування виконано з урахуванням каркаса комп'ютерів, які оснащені розробленою системою

Improvement of detection and tracking techniques in multistatic passive radar systems. (Mejora de técnicas de detección y seguimiento en sistemas radar pasivos multiestáticos)

Esta tesis doctoral es el resultado de una intensa actividad investigadora centrada en los sensores radar pasivos para la mejora de las capacidades de detección y seguimiento en escenarios complejos con blancos terrestres y pequeños drones. El trabajo de investigación se ha llevado a cabo en el grupo de investigación coordinado por la Dra. María Pilar Jarabo Amores, dentro del marco diferentes proyectos: IDEPAR (“Improved DEtection techniques for PAssive Radars”), MASTERSAT (“MultichAnnel paSsive radar receiver exploiting TERrestrial and SATellite Illuminators”) y KRIPTON (“A Knowledge based appRoach to passIve radar detection using wideband sPace adapTive prOcessiNg”) financiados por el Ministerio de Economía y Competitividad de España; MAPIS (Multichannel passive ISAR imaging for military applications) y JAMPAR (“JAMmer-based PAssive Radar”), financiados por la Agencia Europea de Defensa (EDA) . El objetivo principal es la mejora de las técnicas de detección y seguimiento en radares pasivos con configuraciones biestáticas y multiestaticas. En el documento se desarrollan algoritmos para el aprovechamiento de señales procedentes de distintos iluminadores de oportunidad (transmisores DVB-T, satélites DVB-S y señales GPS). Las soluciones propuestas han sido integradas en el demostrador tecnológico IDEPAR, desarrollado y actualizado bajo los proyectos mencionados, y validadas en escenarios reales declarados de interés por potenciales usuarios finales (Direccion general de armamento y material, instituto nacional de tecnología aeroespacial y la armada española). Para el desarrollo y evaluación de cadenas de las cadenas de procesado, se plantean dos casos de estudio: blancos terrestres en escenarios semiurbanos edificios y pequeños blancos aéreos en escenarios rurales y costeros. Las principales contribuciones se pueden resumir en los siguientes puntos: • Diseño de técnicas de seguimiento 2D en el espacio de trabajo rango biestático-frecuencia Doppler: se desarrollan técnicas de seguimiento para los dos casos de estudio, localización de blancos terrestres y pequeños drones. Para es último se implementan técnicas capaces de seguir tanto el movimiento del dron como su firma Doppler, lo que permite implementar técnicas de clasificación de blancos. • Diseño de técnicas de seguimiento de blancos capaces de integrar información en el espacio 3D (rango, Doppler y acimut): se diseñan técnicas basadas en procesado en dos etapas, una primera con seguimiento en 2D para el filtrado de falsas alarmas y la segunda para el seguimiento en 3D y la conversión de coordenadas a un plano local cartesiano. Se comparan soluciones basadas en filtros de Kalman para sistemas tanto lineales como no lineales. • Diseño de cadenas de procesado para sistemas multiestáticos: la información estimada del blanco sobre múltiples geometrías biestáticas es utilizada para incremento de las capacidades de localización del blanco en el plano cartesiano local. Se presentan soluciones basadas en filtros de Kalman para sistemas no lineales explotando diferentes medidas biestáticas en el proceso de transformación de coordenadas, analizando las mejoras de precisión en la localización del blanco. • Diseño de etapas de procesado para radares pasivos basados en señales satelitales de las constelaciones GPS DVB-S. Se estudian las características de las señales satelitales identificando sus inconvenientes y proponiendo cadenas de procesado que permitan su utilización para la detección y seguimiento de blancos terrestres. • Estudio del uso de señales DVB-T multicanal con gaps de transmisión entre los diferentes canales en sistemas radares pasivos. Con ello se incrementa la resolución del sistema, y las capacidades de detección, seguimiento y localización. Se estudia el modelo de señal multicanal, sus efectos sobre el procesado coherente y se proponen cadenas de procesado para paliar los efectos adversos de este tipo de señales

Evaluation of remain well clear and collision avoidance for drones

One of the cornerstones that should enable inserting unmanned aircraft into the airspace is the development of Detect and Avoid (DAA) systems. DAA systems will improve the Remote Pilot (RP) situational awareness by means of electronic conspicuity devices, providing them with the necessary means to Remain Well Clear (RWC) from other traffic and, if necessary, avoid Mid-Air collisions (MAC). DAA systems will compensate for the loss of a pilot on board, which drastically reduces the capacity to keep a safe separation from traffic, making current Rules of the Air very challenging to achieve. Given the growing popularity of drone operations for commercial and recreational purposes, new standards should include them in the not-too-distant future. Since current DAA standards and algorithms (DO-365 and ED-258) are being developed targeting large, mostly military Remotely Piloted Aircraft Systems (RPAS), this project proposes a new set of detection volumes and alert thresholds for U-Space users according to an aircraft type classification. This will allow adapting the existing DAA algorithms to small drones, complying with the new European framework of services and applications for drones (U-Space). Because testing new safety nets (such as new DAA algorithms) on real aircraft would be dangerous and inadequate, radar reports and computer-based simulations allow for a risk-free and faster evaluation of safety net performances. Due to the current lack of real drone radar tracks, this project has developed a multi-rotor drone encounter generator tool (called DEG). This software is able to generate a large number of synthetic pairwise quadcopter drone conflict tracks, simulating the instant prior to a MAC. The way trajectories are generated by DEG strongly depends on the type of operation being flown (inspection/surveillance flights and logistic flights) and the aircraft type (including a DJI F450 and a faster version called DJI F450 FAST). The results of this project include a drone conflict trajectory example generated with DEG and an investigation of the performance and effectiveness of the DEG tool using a tailored existing DAA algorithm (DAIDALUS).Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructur

Design of autonomous sustainable unmanned aerial vehicle - A novel approach to its dynamic wireless power transfer

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.Electric UAVs are presently being used widely in civilian duties such as security, surveillance, and disaster relief. The use of Unmanned Aerial Vehicle (UAV) has increased dramatically over the past years in different areas/fields such as marines, mountains, wild environments. Nowadays, there are many electric UAVs development with fast computational speed and autonomous flying has been a reality by fusing many sensors such as camera tracking sensor, obstacle avoiding sensor, radar sensor, etc. But there is one main problem still not able to overcome which is power requirement for continuous autonomous operation. When the operation needs more power, but batteries can only give for 20 to 30 mins of flight time. These types of system are not reliable for long term civilian operation because we need to recharge or replace batteries by landing the craft every time when we want to continue the operation. The large batteries also take more loads on the UAV which is also not a reliable system. To eliminate these obstacles, there should a recharging wireless power station in ground which can transmit power to these small UAVs wirelessly for long term operation. There will be camera attached in the drone to detect and hover above the Wireless Power Transfer device which got receiving and transmitting station can be use with deep learning and sensor fusion techniques for more reliable flight operations. This thesis explores the use of dynamic wireless power to transfer energy using novel rotating WPT charging technique to the UAV with improved range, endurance, and average speed by giving extra hours in the air. The hypothesis that was created has a broad application beyond UAVs. The drone autonomous charging was mostly done by detecting a rotating WPT receiver connected to main power outlet that served as a recharging platform using deep neural vision capabilities. It was the purpose of the thesis to provide an alternative to traditional self-charging systems that relies purely on static WPT method and requires little distance between the vehicle and receiver. When the UAV camera detect the WPT receiving station, it will try to align and hover using onboard sensors for best power transfer efficiency. Since this strategy relied on traditional automatic drone landing technique, but the target is rotating all the time which needs smart approaches like deep learning and sensor fusion. The simulation environment was created and tested using robot operating system on a Linux operating system using a model of the custom-made drone. Experiments on the charging of the drone confirmed that the intelligent dynamic wireless power transfer (DWPT) method worked successfully while flying on air

Terrified by Technology: How Systemic Bias Distorts U.S. Legal and Regulatory Responses to Emerging Technology

Americans are becoming increasingly aware of the systemic biases we possess and how those biases preclude us from collectively living out the true meaning of our national creed. But to fully understand systemic bias we must acknowledge that it is pervasive and extends beyond the contexts of race, privilege, and economic status. Understanding all forms of systemic bias helps us to better understand ourselves and our shortcomings. At first glance, a human bias against emerging technology caused by systemic risk misperception might seem uninteresting or unimportant. But this Article demonstrates how the presence of systemic bias anywhere, even in an area as unexpected as technology regulation, creates inefficiencies and inequalities that exact heavy costs in the form of human lives, standards of living, and lost economic opportunities. The decision to regulate or implement an emerging technology, like any other complex decision, naturally involves some form of cost-benefit or risk-reward analysis. However, in the context of emerging technology, that analysis is biased by systemic risk misperception. Immutable characteristics existing in emerging technology combine with interrelated characteristics in human decisionmakers and regulators to inflate perceptions of risks and depress perceptions of benefits. This artificial shifting of cost-benefit curves results in suboptimal legislative and regulatory responses to emerging technology, and ultimately, in the loss of American lives

The Development of Digital Forensics Workforce Competency on the Example of Estonian Defence League

03.07.2014 kehtestati Vabariigi Valitsuse määrus nr. 108, mis reguleerib Kaitseliidu kaasamise tingimusi ja korda küberjulgeoleku tagamisel. Seega võivad Kaitseliidu küberkaitse üksuse (KL KKÜ edaspidi KKÜ) kutsuda olukorda toetama erinevad asutused: näiteks Riigi Infosüsteemide amet (RIA), infosüsteemi järelevalveasutus või kaitseministeerium või selle valitsemisala ametiasutused oma ülesannete raames. KKÜ-d saab kaasata info- ja sidetehnoloogia infrastruktuuri järjepidevuse tagamisel, turvaintsidentide kontrollimisel ja lahendamisel, rakendades nii aktiivseid kui passiivseid meetmeid. KKÜ ülesannete kaardistamisel täheldati, et KKÜ partnerasutused / organisatsioonid ei ole kaardistanud oma spetsialistide olemasolevaid pädevusi ja sellele lisaks puudub ülevaade digitaalse ekspertiisi kogukonnas vajaolevatest pädevustest. Leitut arvesse võttes seati ülesandeks vajadustest ja piirangutest (võttes arvesse digitaalse ekspertiisi kogukonda kujundavaid standardeid) ülevaatliku pildi loomine, et töötada välja digitaalse ekspertiisi kompetentsipõhine raamistik, mis toetab KKÜ spetsialistide arendamist palkamisest pensionini. Selleks uurisime KKÜ ja nende olemasolevate koolitusprogrammide hetkeolukorda ning otsustasime milliseid omadusi peab edasise arengu tarbeks uurima ja kaaluma. Võrreldavate tulemuste saa-miseks ja eesmärgi täitmiseks pidi koostatav mudel olema suuteline lahendama 5-t järgnevat ülesannet: 1. Oskuste kaardistamine, 2. Eesmärkide seadmine ja ümberhindamine, 3. Koolituskava planeerimine, 4. Värbamisprotsessi kiirendamine ning 5. Spetsialistide kestva arengu soodustamine. Raamistiku väljatöötamiseks võeti aluseks National Initiative for Cybersecurity Education (NICE) Cybersecurity Workforce Framework (NICE Framework) pädevusraamistik mida parendati digitaalse ekspertiisi spetsialistide, ja käesoleval juhul ka KKÜ, vajadusi silmas pidades. Täiendusi lisati nii tasemete, spetsialiseerumise kui ka ülesannete kirjelduste kujul. Parenduste lisamisel võeti arvesse töös tutvustatud digitaalse ekspertiisi piiranguid ja standardeid, mille lõpptulemusena esitati KKÜ-le Digitaalse Ekspertiisi Pädevuse ontoloogia, KKÜ struktuuri muudatuse ettepanek, soovitatavad õpetamisstrateegiad digitaalse ekspertiisi kasutamiseks (muudetud Bloomi taksonoomia tasemetega), uus digitaalse ekspertiisi standardi alajaotus – Mehitamata Süsteemide ekspertiis ja Digitaalse Ekspertiisi Pädevuse Mudeli Raamistik. Ülesannete ja oskuste loetelu koostati rahvusvaheliselt tunnustatud sertifitseerimis-organisatsioonide ja erialast pädevust pakkuvate õppekavade abil. Kavandatava mudeli hindamiseks kasutati mini-Delphi ehk Estimate-Talk-Estimate (ETE) tehnikat. Esialgne prognoos vajaduste ja prioriteetidega anti KKÜ partnerasutustele saamaks tehtud töö kohta ekspertarvamusi. Kogu tagasisidet silmas pidades tehti mudelisse korrektuurid ja KKÜ-le sai vormistatud ettepanek ühes edasise tööplaaniga. Üldiselt kirjeldab väljapakutud pädevusraamistik KKÜ spetsialistilt ooda-tavat pädevuse ulatust KKÜ-s, et suurendada nende rolli kiirreageerimisrühmana. Raamistik aitab määratleda digitaalse ekspertiisi eeldatavaid pädevusi ja võimekusi praktikas ning juhendab eksperte spetsialiseerumise valikul. Kavandatud mudeli juures on arvestatud pikaajalise mõjuga (palkamisest pensionini). Tulenevalt mudeli komplekssusest, on raamistikul pikk rakendusfaas – organisatsiooni arengule maksimaalse mõju saavutamiseks on prognoositud ajakava maksimaalselt 5 aastat. Antud ettepanekud on käesolevaks hetkeks KKÜ poolt heaks kiidetud ning planeeritud kava rakendati esmakordselt 2019 aasta aprillikuus.In 03.07.2014 Regulation No. 108 was introduced which regulates the conditions and pro-cedure of the involvement of the Estonian Defence League (EDL) Cyber Defence Unit (CDU) in ensuring cyber security. This means that EDL can be brought in by the Information System Authority, Ministry of Defence or the authorities of its area of government within the scope of either of their tasks e.g. ensuring the continuity of information and communication technology infrastructure and in handling and solving cyber security incidents while applying both active and passive measures. In January 2018 EDL CDU’s Digi-tal Evidence Handling Group had to be re-organized and, thus, presented a proposal for internal curriculum in order to further instruct Digital Evidence specialists. While describing the CDU's tasks, it was noted that the CDU's partner institutions / organizations have not mapped out their specialists’ current competencies. With this in mind, we set out to create a comprehensive list of needs and constraints (taking into account the community standards of DF) to develop a DF-based competence framework that supports the devel-opment of CDU professionals. Hence, we studied the current situation of CDU, their existing training program, and contemplated which features we need to consider and ex-plore for further development. In order to assemble comparable results and to achieve the goal the model had to be able to solve the 5 following tasks: 1. Competency mapping, 2. Goal setting and reassessment, 3. Scheduling the training plan, 4. Accelerating the recruitment process, and 5. Promoting the continuous development of professionals. The frame-work was developed on the basis of the National Initiative for Cybersecurity Education (NICE) Cybersecurity Workforce Framework (NICE Framework), which was revised to meet the needs of DF specialists, including EDL CDU. Additions were supplemented in terms of levels, specialization, and job descriptions. The proposals included the DF limitations and standards introduced in the work, which ultimately resulted in a proposal for a Digital Forensics Competency ontology, EDL CDU structure change, Suggested Instruc-tional Strategies for Digital Forensics Use With Each Level of revised Bloom's Taxonomy, a new DF standard subdivision – Unmanned Systems Forensics, and Digital Forensic Competency Model Framework. The list of tasks and skills were compiled from international certification distribution organizations and curricula, and their focus on DF Special-ist Competencies. Mini-Delphi or Estimate-Talk-Estimate (ETE) techniques were applied to evaluate the proposed model. An initial estimation of competencies and priorities were given to the EDL CDU partner institutions for expert advice and evaluation. Considering the feedback, improvements were made to the model and a proposal was put forward to the CDU with a future work plan. In general, the proposed competence framework describes the expected scope of competence of an DF specialist in the EDL CDU to enhance their role as a rapid response team. The framework helps in defining the expected compe-tencies and capabilities of digital forensics in practice and offers guidance to the experts in the choice of specialization. The proposed model takes into account the long-term effect (hire-to-retire). Due to the complexity of the model, the framework has a long implementation phase — the maximum time frame for achieving the full effect for the organization is expected to be 5 years. These proposals were approved by EDL CDU and the proposed plan was first launched in April 2019

Hypersonic drone design: A multidisciplinary experience

Efforts were focused on design problems of an unmanned hypersonic vehicle. It is felt that a scaled hypersonic drone is necessary to bridge the gap between present theory on hypersonics and the future reality of the National Aerospace Plane (NASP) for two reasons: to fulfill a need for experimental data in the hypersonic regime, and to provide a testbed for the scramjet engine which is to be the primary mode of propulsion for the NASP. Three areas of great concern to NASP design were examined: propulsion, thermal management, and flight systems. Problem solving in these areas was directed towards design of the drone with the idea that the same design techniques could be applied to the NASP. A seventy degree swept double delta wing configuration, developed in the 70's at NASA Langley, was chosen as the aerodynamic and geometric model for the drone. This vehicle would be air-launched from a B-1 at Mach 0.8 and 48,000 feet, rocket boosted by two internal engines to Mach 10 and 100,000 feet, and allowed to cruise under power of the scramjet engine until burnout. It would then return to base for an unpowered landing. Preliminary energy calculations based upon the flight requirements give the drone a gross launch weight of 134,000 lb. and an overall length of 85 feet