Reliable Communication and Accurate Sensing for UAV Traffic Management

In recent years, the number of Unmanned Aerial Vehicles (a.k.a. drones) in our skies increased dramatically. Drones are used in many civil and, sadly, military applications. Typical civil applications are environmental and structural monitoring of difficult-to-reach zones, filming for the TV and the Cinema, taking spectacular panoramic photos, and also surveillance and search and rescue operations by the police, the forest guard, and the fire brigade. Delivery companies and big online retail companies are also experimenting with the use of drones for package delivery, which can be very convenient in certain areas with sparse populations. It is also evident how drones can greatly impact conflicts, such as the horrendous war between Russia and Ukraine (2022). The higher the number of drones flying in our skies, the higher the probability of accidents. The Single European Sky ATM Research 3 Joint Undertaking, together with EASA, took into its hands the responsibility of developing a framework to safely integrate drone traffic into the standard air traffic management system. This framework is called U-Space, and it comprises a multitude of projects to develop the technology and the operational procedures to safely operate drones in civil airspace. This thesis work spans two distinct projects, PercEvite and Electrosense, and exposes our findings in the context of drone-to-drone communications for safety applications. In our vision, drones should be able to interact and coordinate with each other autonomously and reliably for U-Space to happen. Drone-to-drone communication is thus an essential component to flying safely, with total autonomy, and with minimal pilot intervention. After an introductory chapter which expands on the concepts of U-Space and drone communications, the thesis is split into two parts. The first part, covering the PercEvite project, is composed of Chapters 2 and 3. The second part, covering the Electrosense project, is composed of Chapters 4 and 5.

Chapter 2 is about unifying the terminologies of air traffic control and communication engineering, especially concerning the definition of terms such as "safe separation" and "conflict management". The chapter also explains the architecture of a drone traffic management system and how different communication systems can be adapted for different use cases in the context of traffic management. Chapter 3 illustrates the design, simulation and implementation of a communication system for drones. The system exploits the small embedded Wi-Fi modules present in many small commercial drones which allows its deployment on already existing hardware. Chapter 4 is about RF interference, and how it can affect aerial communications at different altitudes. The chapter presents the design of a probe for highaltitude measurements, based on a software-defined radio and an embedded computer. It also shows simulation results to roughly quantify the impact of interference on conflict management algorithms. Chapter 5 explains in detail how to calibrate software-defined radios to accurately measure RF power which is crucial to quantify interference levels and spectrum occupancy. As a test case to show the potential and pitfalls of software-defined radios, a measurement of the electric field generated by a 5G base station is discussed. Finally, Chapter 6 summarises the most important findings of this thesis and proposes future lines of research and potential work to answer the new research questions and improve the findings obtained during my PhD program.