GNSS avionics-based Integrity augmentation for RPAS detect-and-avoid applications

摘要

Taking the move from our recent research on GNSS Avionics Based Integrity Augmentation (ABIA), this article investigates the synergies of ABIA with a novel Detect-and-Avoid (DAA) architecture for Remotely Piloted Aircraft System (RPAS). Based on simulation and experimental data collected on a variety of manned and unmanned aircraft, it was observed that the integration of ABIA with DAA has the potential to provide an integrity-augmented DAA for both cooperative and non-cooperative applications. The candidate DAA system uses various Forward-Looking Sensors (FLS) for the non-cooperative case and Automatic Dependent Surveillance- Broadcast (ADS-B) in addition to TCAS/ASAS for the cooperative case. 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 manoeuvre 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 RPAS platform dynamics and GNSS constellation satellite elevation angles, preventing degradation or losses of navigation data during the whole DAA 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). Cooperative and non-cooperative simulation case studies were accomplished to evaluate the performance of this Integrity-Augmented DAA (IAS) architecture.