The increasing integration of Uncrewed Aerial Systems (UAS) into controlled airspace presents significant operational and safety challenges, particularly in conflict detection and resolution (CD&R) for Beyond Visual Line of Sight (BVLOS) operations. Ensuring reliable separation management in U-Space requires robust e-conspicuity solutions that address uncertainties in Communication, Navigation, and Surveillance (CNS) systems. This study evaluates the CERTIFLIGHT UTM Box, an e-conspicuity device designed for General Aviation (GA) and UAS operations, incorporating authenticated GNSS tracking, blockchain-based data integrity, and conflict resolution advisory services. Flight validation tests were conducted using a GA aircraft and a UAS to assess the system's effectiveness in detecting and resolving conflicts under realistic operational conditions. The results indicate that while the UTM Box successfully provided conflict advisories, navigation uncertainties and communication delays exceeding five seconds affected its performance. The study highlights the importance of incorporating CNS system uncertainties into CD&R algorithms to ensure safe separation. Future work will focus on refining conflict resolution strategies, integrating advanced filtering techniques to mitigate sensor noise, and enhancing pilot interface design for improved situational awareness and decision support.

With the rapid increase in the use of Unmanned Aerial Systems (UAS) for commercial applications such as medical and parcel delivery, the need for safe airborne separation in airspace has become critical. This paper examines the impact of position uncertainty on autonomous separation methods within U-Space, a European Union initiative for managing drone traffic. The study focuses on evaluating various conflict resolution algorithms—specifically, Modified Voltage Potential (MVP) and Velocity Obstacle (VO) variations—under conditions of navigational uncertainty. Through Monte Carlo simulations using the BlueSky ATM simulator, position uncertainty stemming from Global Navigation Satellite Systems (GNSS) errors is modelled and analysed. The research compares the effectiveness of different conflict resolution strategies in preventing conflicts between UAS, measuring intrusion prevention rates and the closest point of approach during encounters. The results indicate that MVP provides superior performance in handling positional uncertainty, offering more robust conflict resolution capabilities than VO-based methods especially at shallow angles conflict situation. These findings are critical for ensuring the safe integration of UAS into increasingly congested airspace environments, guiding future developments in U-Space operations.