Implementation of a Sensor Guided Flight Algorithm for Target Tracking by Small UAS

Small fixed-wing UAS (SUAS) such as Raven and Unicorn have limited power, speed, and maneuverability. Their missions can be dramatically hindered by environmental conditions (wind, terrain), obstructions (buildings, trees) blocking clear line of sight to a target, and/or sensor hardware limitations (fixed stare, limited gimbal motion, lack of zoom). Toyon's Sensor Guided Flight (SGF) algorithm was designed to account for SUAS hardware shortcomings and enable long-term tracking of maneuvering targets by maintaining persistent eyes-on-target. SGF was successfully tested in simulation with high-fidelity UAS, sensor, and environment models, but real world flight testing with 60 Unicorn UAS revealed surprising second order challenges that were not highlighted by the simulations. This paper describes the SGF algorithm, our first round simulation results, our second order discoveries from flight testing, and subsequent improvements that were made to the algorithm