Traditional anti-icing/de-icing systems, i.e., thermal and pneumatic, in most cases require a power consumption not always allowable in small aircraft. Therefore, the use of passive systems, able to delay the ice formation, or reduce the ice adhesion strength once formed, with no additional energy consumption, can be considered as the most promising solution to solve the problem of the ice formation, most of all, for small aircraft. In some cases, the combination of a traditional icing protection system (electrical, pneumatic, and thermal) and the passive coatings can be considered as a strategic instrument to reduce the energy consumption. The effort of the present work was to develop a superhydrophobic coating, able to reduce the surface free energy (SFE) and the work of adhesion (W_A) of substrates, by a simplified and non-expensive method. The developed coating, applied as a common paint with an aerograph, is able to reduce the SFE of substrates by 99% and the W_A by 94%. The effects of both chemistry and surface morphology on the wettability of surfaces were also studied. In the reference samples, the higher the roughness, the lower the SFE and the W_A. In coated samples with roughness ranging from 0.4 and 3 µm no relevant variations in water contact angle, nor in SFE and W_A were observed.

Collision Detection and Avoidance is one of the critical technologies for fully allowing Unmanned Aerial Systems to fly in civil airspaces. Current methods evaluate only potential conflicts with other aircraft using specific parameters (e.g., time or distance to closest point of approach) that can only be used for pair-wise encounters, not considering the surrounding environment. The present work proposes a new Collision Detection and Avoidance concept to solve short-term conflicts in scenarios characterized by the simultaneous presence of aircraft and other path constraints (i.e., no-fly zones, bad weather areas and terrain) including geo-fencing limitations. Differently from other open literature methods, the proposed algorithm computes two parameters that synthetically describe the conflict hazard level of a given scenario and its possible evolution, independently from the type and the number of surrounding potential threats. Using such indices, a risk evaluation strategy is proposed that detects hazardous situations and generates an optimal maneuver avoiding potential collisions while not causing secondary conflicts. The effectiveness of the proposed algorithm is demonstrated by means of fast-time and real time simulations in some challenging conflict scenarios that cannot be solved by state of the art Detect and Avoid systems.

The full integration of Remotely Piloted unmanned vehicles into civil airspace requires first and foremost the integration of a traffic Detect and Avoid (DAA) system into the vehicle. The DAA system supports remote pilots in performing their task of remaining Well Clear from other aircraft and avoiding collisions. Several studies related to the design of a Remain Well Clear function have been performed that served as input for the development of technical standards applicable to non-European countries. In this paper, a Remain Well Clear implementation is proposed that, using the results of past international projects, fits European airspace needs and specificities and can be acceptable to both remote pilots and air traffic controllers, with only minimal impact on the standard operating procedures used for manned aircraft. The proposed Remain Well Clear software has been successfully validated through real-time simulations with pilots and controllers in the loop considering traffic encounters and mission scenarios typically found in European airspace. The achieved results highlight the appropriate situational awareness provided by the proposed RWC function and its effective support to the remote pilot in making adequate decisions in conflict solving. Real-time simulation tests showed that, in almost all cases, an RWC maneuver is successfully performed, giving the RP sufficient time to assess the conflict, coordinate with the controller, if needed, and execute the maneuver. The fundamental role of the proposed RWC function has been especially evident in uncontrolled airspace classes where the controller does not provide any separation provision. Moreover, its effectiveness has also been tested in encounters with aircraft flying under visual flight rules in controlled airspace, where the controller is not informed or has less information regarding these aircraft. The results from validation tests imply two key potential safety benefits, namely: the mitigation of performing a collision avoidance maneuver and the prevention of potential conflict while not disrupting the traffic flow with possible further consequences of generating other potentially hazardous situations.

A global navigation satellite system (GNSS) for remotely piloted aircraft systems (RPASs) positioning is essential, thanks to the worldwide availability and continuity of this technology in the provision of positioning services. This makes the GNSS technology a critical element as malfunctions impacting on the determination of the position, velocity and timing (PVT) solution could determine safety issues. Such an aspect is particularly challenging in urban air mobility (UAM) scenarios, where low satellite visibility, multipath, radio frequency interference and cyber threats can dangerously affect the PVT solution. So, to meet integrity requirements, GNSS receiver measurements are augmented/fused with other aircraft sensors that can supply position and/or velocity information on the aircraft without relying on any other satellite and/or ground infrastructures. In this framework, in this paper, the algorithms of a hybrid navigation unit (HNU) for UAM applications are detailed, implementing a tightly coupled sensor fusion between a dual-frequency multi-constellation GNSS receiver, an inertial measurements unit and the barometric altitude from an air data computer. The implemented navigation algorithm is integrated with autonomous fault detection and exclusion of GPS/Galileo/BeiDou satellites and the estimation of navigation solution integrity/accuracy (i.e., protection level and figures of merit). In-flight tests were performed to validate the HNU functionalities demonstrating its effectiveness in UAM scenarios even in the presence of cyber threats. In detail, the navigation solution, compared with a real-time kinematic GPS receiver used as the reference centimetre-level position sensor, demonstrated good accuracy, with position errors below 15 m horizontally and 10 m vertically under nominal conditions (i.e., urban scenarios characterized by satellite low visibility and multipath). It continued to provide a valid navigation solution even in the presence of off-nominal events, such as spoofing attacks. The cyber threats were correctly detected and excluded by the system through the indication of the valid/not valid satellite measurements. However, the results indicate a need for fine-tuning the EKF to improve the estimation of figures of merit and protection levels associated to the navigation solution during the cyber-attacks. In contrast, solution accuracy and integrity indicators are well estimated in nominal conditions.

The safety-critical functions of autonomous drones heavily rely on Positioning, Navigation and Timing (PNT) information provided by Global Satellite Navigation Systems (GNSSs). This makes GNSS technology a critical element as the PNT solution can be affected by several threats, mostly in urban and suburban environments. In order to evaluate safe and reliable GNSS-based solutions in Urban Air Mobility (UAM) scenarios, a proper GNSS security impact simulator is needed. In this context, the present work details the design, implementation and testing of a GNSS Threat Simulator (GTS) capable of reproducing typical issues within a GNSS system in a UAM environment, such as satellite visibility (i.e., the actual visibility condition of the receiver’s antenna with respect to terrain and ground obstacle), multipath, electromagnetic interference, cyber threats (i.e., spoofing and jamming) and satellites failures. The GTS elaborates and modifies dual-frequency multi-constellation GNSS observables in order to inject the desired threats. The effectiveness of the proposed simulator has been demonstrated through both fast-time and real-time simulations, in which the GTS was used to validate a hybrid navigation unit installed on a drone operating in a representative urban scenario.

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