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Due to limitations in available sensor technology, unmanned aerial vehicles(UAVs) lack an active sensing capability to measure turbulence, gusts, or otherunsteady aerodynamic phenomena. Conventional in situ anemometry techniques failto deliver in the harsh and dynamic multirotor environment due to form factor,resolution, or robustness requirements. To address this capability gap, anovel, fast-response sensor system to measure a wind vector in two dimensionsis introduced and evaluated. This system, known as `MAST' (for MEMS AnemometrySensing Tower), leverages advances in microelectromechanical (MEMS) hot-wiredevices to produce a solid-state, lightweight, and robust flow sensor suitablefor real-time wind estimation onboard a UAV. The MAST uses fivepentagonally-arranged microscale hot-wires to determine the wind vector'sdirection and magnitude. The MAST's performance was evaluated in a wind tunnelat speeds up to 5~m/s and orientations of 0 - 360 degrees. A neural networksensor model was trained from the wind tunnel data to estimate the wind vectorfrom sensor signals. The average error of the sensor is 0.14 m/s for speed and1.6 degrees for direction. Furthermore, 95% of measurements are within 0.36 m/serror for speed and 5.0 degree error for direction. With a bandwidth of 570 Hzdetermined from square-wave testing, the MAST stands to greatly enhance UAVwind estimation capabilities and enable capturing relevant high-frequencyphenomena in flow conditions.

Fast-response hot-wire flow sensors for wind and gust estimation on UAVs