A Unified Analytical Framework for Aircraft Separation Assurance and UAS Sense-and-Avoid

A novel analytical framework is presented addressing the need for a unified approach to aircraft separation assurance and Unmanned Aircraft System (UAS) Sense-and-Avoid (SAA). A brief review of the state-of-research in Separation Assurance and Collision Avoidance (SA&CA) technologies is included to highlight the benefits offered by the unified approach. In this approach, the employment of Adaptive Boolean Decision Logics (ABDL) allows automated selection of sensors/systems including passive and active Forward Looking Sensors (FLS), Traffic Collision Avoidance System (TCAS) and Automatic Dependent Surveillance - Broadcast (ADS-B). This system performance based selection approach supports trusted autonomous operations during all flight phases. After describing a SA&CA reference architecture, the mathematical models employed in the unified approach to compute the overall uncertainty volume in the airspace surrounding an intruder/obstacle are described. The algorithms support the translation of navigation errors affecting the host aircraft platform and tracking errors affecting the intruder sensor measurements to unified range and bearing uncertainty descriptors. Simulation case studies are presented to evaluate the performance of the unified approach on a representative UAS host platform and a number of intruder platforms in both cooperative and non-cooperative scenarios. The results confirm the validity of the proposed unified methodology in providing a pathway for certification of SA&CA systems. The significance of this approach is also discussed in the Communication, Navigation and Surveillance/Air Traffic Management and Avionics (CNS + A) context, with a focus on the evolving UAS Traffic Management (UTM) requirements.