Articles | Volume 15, issue 24
Research article
16 Dec 2022
Research article |  | 16 Dec 2022

High-fidelity retrieval from instantaneous line-of-sight returns of nacelle-mounted lidar including supervised machine learning

Kenneth A. Brown and Thomas G. Herges

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Cited articles

Albers, A., Janssen, A., and Mander, J.: German Test Station for Remote Wind Sensing Devices, EWEC, Marseille, (last access: 19 September 2020), 2009. 
Angelou, N., Abari, F. F., Mann, J., Mikkelsen, T., and Sjöholm, M.: Challenges in noise removal from Doppler spectra acquired by a continuous-wave lidar, Proc. 26th Int. Laser Radar Conf., Porto Heli, Greece, 10 pp., 2012. 
Beck, H. and Kühn, M.: Dynamic data filtering of long-range Doppler LiDAR wind speed measurements, Remote Sens., 9, 561,, 2017.  
Benedict, L. and Gould, R.: Towards better uncertainty estimates for turbulence statistics, Exp. Fluids, 22, 129–136,, 1996. 
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The character of the airflow around and within wind farms has a significant impact on the energy output and longevity of the wind turbines in the farm. For both research and control purposes, accurate measurements of the wind speed are required, and these are often accomplished with remote sensing devices. This article pertains to a field experiment of a lidar mounted to a wind turbine and demonstrates three data post-processing techniques with efficacy at extracting useful airflow information.