Dubins-Based Autolanding Procedure for Fixed-Wing UAS

Unmanned aerial systems are quickly growing in both military and civilian applications. The exponential growth unmanned aerial systems have provided many new opportunities such as urban air mobility. With the imminent entrance of unmanned aerial systems to the national airspace aircraft will be flying at lower heights over people and properties and will be landing in spatially constraint landing fields. This paper introduces cognitive autolanding algorithms, where the standard landing stages of flare, glideslope, and approach, are employed to land the aircraft safely and within time, spatial, and aircraft dynamic constraints. The use of Dubins paths during the approach stage is explored and employed in this work showing how the algorithms can be used to direct the aircraft towards any landing field from adverse initial headings and positions. The autolanding generated path is then flown in a six-degrees-of-freedom simulation environment. The robustness of this cognitive autolanding algorithm is validated through Monte Carlo analysis.