Avionics-Based GNSS Integrity Augmentation for Unmanned Aerial Systems Sense-and-Avoid

TLDR: Simulation results show that the proposed IAS architecture is an excellent candidate to perform high-integrity Collision Detection and Resolution (CD&R) utilizing GNSS as the primary source of navigation data, providing solid foundation for future research and developments in this domain.

Abstract: This paper investigates the synergies between a GNSS Avionics Based Integrity Augmentation (ABIA) system and a novel Unmanned Aerial System (UAS) Sense-and-Avoid (SAA) architecture for cooperative and non-cooperative scenarios. The integration of ABIA with SAA has the potential to provide an integrity-augmented SAA solution that will allow the safe and unrestricted access of UAS to commercial airspace. The candidate SAA system uses Forward-Looking Sensors (FLS) for the non-cooperative case and Automatic Dependent Surveillance-Broadcast (ADS-B) for the cooperative case. In the non-cooperative scenario, the system employs navigation-based image stabilization with image morphology operations and a multi-branch Viterbi filter for obstacle detection, which allows heading estimation. The system utilizes a Track-to-Track (T3) algorithm for data fusion that allows combining data from different tracks obtained with FLS and/or ADS-B depending on the scenario. Successively, it utilizes an Interacting Multiple Model (IMM) algorithm to estimate the state vector allowing a prediction of the intruder trajectory over a specified time horizon. Both in the cooperative and non-cooperative cases, the risk of collision is evaluated by setting a threshold on the Probability Density Function (PDF) of a Near Mid-Air Collision (NMAC) event over the separation area. So, if the specified threshold is exceeded, an avoidance manoeuver is performed based on a heading-based Differential Geometry (DG) algorithm and optimized utilizing a cost function with minimum time constraints and fuel penalty criteria weighted as a function of separation distance. Additionally, the optimised avoidance trajectory considers the constraints imposed by the ABIA in terms of GNSS constellation satellite elevation angles, preventing degradation or losses of navigation data during the whole SAA loop. This integration scheme allows real-time trajectory corrections to re-establish the Required Navigation Performance (RNP) when actual GNSS accuracy degradations and/or data losses take place (e.g., due to aircraft-satellite relative geometry, GNSS receiver tracking, interference, jamming or other external factors). Various simulation case studies were accomplished to evaluate the performance of this Integrity-Augmented SAA (IAS) architecture. The selected host platform was the AEROSONDE Unmanned Aerial Vehicle (UAV) and the simulation cases addressed a variety of cooperative and non-cooperative scenarios in a representative cross-section of the AEROSONDE operational flight envelope. The simulation results show that the proposed IAS architecture is an excellent candidate to perform high-integrity Collision Detection and Resolution (CD&R) utilizing GNSS as the primary source of navigation data, providing solid foundation for future research and developments in this domain.