Date of Award
Master of Science
Department of Aeronautics and Astronautics
Paul A. Blue, PhD
The research effort focuses on developing methods to design efficient wind correction algorithms to "piggyback" on current off-the-shelf Unmanned Aerial Vehicle (UAV) autopilots. Autonomous flight is certainly the near future for the aerospace industry and there exists great interest in defining a system that can guide and control aircraft with high levels of accuracy. The primary systems required to command the vehicles are already in place, but with only moderate abilities to adjust for dynamic environments (i.e. wind effects), if at all. The goal of this research is to develop a systematic procedure for implementing efficient and robust wind effects corrections to existing autopilots. The research will investigate the feasibility of an external dynamic environment control algorithm as a means of improving current, off-the-shelf autopilot technology relating to small UAVs. The research then presents three main focuses. First, a determination of the estimated winds utilizing the existing, on-board sensors. Second, the development of code that incorporates simple mathematical principals to counter the 2-Dimensional wind forces acting on the aircraft; and third, the integration of that code into the on-board navigational system. This "piggy-back" algorithm must assimilate smoothly with the current GPS technologies to provide acceptable and safe flight path following. The design procedures developed were demonstrated in simulation and with flight tests on the SiG Rascal 110 UAV. This report builds the framework from which future wind correction research at AFIT and the ANT Center are based.
DTIC Accession Number
Robinson, Brent K., "An Investigation into Robust Wind Correction Algorithms for Off-the Shelf Unmanned Aerial Vehicle Autopilots" (2006). Theses and Dissertations. 3552.