Key points are not available for this paper at this time.
Wind is often ignored or only implicitly addressed in design of guidance algorithms. For small UAVs exposed to strong winds, wind has a very signicant nonlinear eect on the guidance algorithm, and strongly aects the spatial orientation and rates of the vehicle. In this work, an autonomous Unmanned Aerial Vehicle (UAV) is commanded to along a path dened by a series of waypoints. The guidance algorithm includes an observer based wind estimator. Based on estimated wind speed and direction, the airspeed and desired course change, a proximity distance is retrieved from a lookup table for each waypoint. This distance allows the aircraft to smoothly converge to each new course, without over/under shoot, in strong wind conditions. This capability is signicant in various tactical maneuvers, e. g. surveying, multi-vehicle operations, target observation, target tracking, avoiding detection, etc. Nomenclature s desired aircraft course n next aircraft course total change in aircraft course during a turn dp waypoint proximity distance
Osborne et al. (Wed,) studied this question.