Skip to main content
Skip to article control options
AIAA 2022-3407
Session: Unmanned Aircraft: Computer Vision and Perception
Published Online:

View Video Presentation:

Operators of Unmanned Air Systems (UAS) lack the physical cues that onboard pilots experience to assess turbulence levels, which means that automated systems are needed onboard the aircraft to identify the turbulence level. To address this need, a Turbulence Recognition And Decision Support for UAS (TRADS-UAS) system was previously developed. This paper focuses on work to validate, through a series of flight tests using a general aviation aircraft as a UAS surrogate, the component of TRADS-UAS that estimates eddy dissipation rate (EDR), a measure of turbulent energy in the atmosphere. To generate EDR estimates, TRADS-UAS uses only standard autopilot sensors expected to be present on any medium to large UAS. TRADS-UAS was run in real-time, onboard the aircraft during tests. The flight crew also recorded manual turbulence estimates during the tests, and a ground-based Doppler Wind Lidar provided independent estimates of EDR for validation. The tests successfully validated the EDR estimation capabilities of TRADS-UAS.