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González-Rocha J, De Wekker SFJ, Ross SD, et al. Wind Profiling in the Lower Atmosphere from Wind-Induced Perturbations to Multirotor UAS. Sensors (Basel). 2020;20(5)doi: 10.3390/s20051341.
González-Rocha, J., De Wekker, S. F. J., Ross, S. D., & Woolsey, C. A. (2020). Wind Profiling in the Lower Atmosphere from Wind-Induced Perturbations to Multirotor UAS. Sensors (Basel, Switzerland), 20(5), . https://doi.org/10.3390/s20051341
González-Rocha, Javier, et al. "Wind Profiling in the Lower Atmosphere from Wind-Induced Perturbations to Multirotor UAS." Sensors (Basel, Switzerland) vol. 20,5 (2020). doi: https://doi.org/10.3390/s20051341
González-Rocha J, De Wekker SFJ, Ross SD, Woolsey CA. Wind Profiling in the Lower Atmosphere from Wind-Induced Perturbations to Multirotor UAS. Sensors (Basel). 2020 Feb 29;20(5). doi: 10.3390/s20051341. PMID: 32121450; PMCID: PMC7085559.
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Sensors (Basel). 2020 Feb 29;20(5). doi: 10.3390/s20051341.

Wind Profiling in the Lower Atmosphere from Wind-Induced Perturbations to Multirotor UAS.

Sensors (Basel, Switzerland)

Javier González-Rocha, Stephan F J De Wekker, Shane D Ross, Craig A Woolsey

Affiliations

  1. Department of Aerospace and Ocean Engineering, Virginia Tech, Blacksburg, VA 24060, USA.
  2. Department of Environmental Sciences, University of Virginia, Charlottesville, VA 22903, USA.

PMID: 32121450 PMCID: PMC7085559 DOI: 10.3390/s20051341

Abstract

We present a model-based approach to estimate the vertical profile of horizontal wind velocity components using motion perturbations of a multirotor unmanned aircraft system (UAS) in both hovering and steady ascending flight. The state estimation framework employed for wind estimation was adapted to a set of closed-loop rigid body models identified for an off-the-shelf quadrotor. The quadrotor models used for wind estimation were characterized for hovering and steady ascending flight conditions ranging between 0 and 2 m/s. The closed-loop models were obtained using system identification algorithms to determine model structures and estimate model parameters. The wind measurement method was validated experimentally above the Virginia Tech Kentland Experimental Aircraft Systems Laboratory by comparing quadrotor and independent sensor measurements from a sonic anemometer and two SoDAR instruments. Comparison results demonstrated quadrotor wind estimation in close agreement with the independent wind velocity measurements. However, horizontal wind velocity profiles were difficult to validate using time-synchronized SoDAR measurements. Analysis of the noise intensity and signal-to-noise ratio of the SoDARs proved that close-proximity quadrotor operations can corrupt wind measurement from SoDARs, which has not previously been reported.

Keywords: atmospheric science; boundary layer meteorology; drone; multi-rotor; system identification; unmanned aircraft systems; wind estimation; wind profile

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