Abstract
This paper presents new efficient guidance algorithms allowing Unmanned Aircraft Systems (UAS) to avoid a variety of Global Navigation Satellite System (GNSS) continuity and integrity performance threats detected by an Aircraft Based Augmentation System (ABAS). In particular, the UAS guidance problem is formulated as an optimal control-based Multi-Objective Trajectory Optimization (MOTO) problem subject to suitable dynamic and geometric constraints. Direct transcription methods of the global orthogonal collocation (pseudospectral) family are exploited for the solution of the MOTO problem, generating optimal trajectories for curved GNSS approaches in real-time. Three degrees-of-freedom aircraft dynamics models and suitable GNSS satellite visibility models based on Global Positioning System (GPS) constellation ephemeris data are utilised in the MOTO solution algorithm. The performance of the proposed MOTO algorithm is evaluated in representative simulation case studies adopting the JAVELIN UAS as the reference platform. The paper focusses on descent and initial curved GNSS approach phases in a Terminal Maneuvering Area (TMA) scenario, where multiple manned/unmanned aircraft converge on the same short and curved final GNSS approach leg. The results show that the adoption of MOTO based on pseudospectral methods allows an efficient exploitation of ABAS model-predictive augmentation features in online GNSS guidance tasks, supporting the calculation of suitable arrival trajectories in 7 to 16 s using a normal PC.
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Gardi, A., Sabatini, R., Ramasamy, S. et al. Real-Time UAS Guidance for Continuous Curved GNSS Approaches. J Intell Robot Syst 93, 151–162 (2019). https://doi.org/10.1007/s10846-018-0876-7
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DOI: https://doi.org/10.1007/s10846-018-0876-7