Optimization of mean wind estimation methods from wind lidar's conical scan data

Ramdas M. Makhmanasarov; Artem M. Sherstobitov

doi:10.1117/12.2644849

7 December 2022 Optimization of mean wind estimation methods from wind lidar's conical scan data

Ramdas M. Makhmanasarov, Artem M. Sherstobitov

Proceedings Volume 12341, 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics; 123412X (2022) https://doi.org/10.1117/12.2644849
Event: 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 2022, Tomsk, Russia

Abstract

The calculation time and the error of the estimates of the horizontal wind velocity from the data of the conical scan are compared. Various implementations of algorithms for direct and filtered sinusoidal wave fitting, and machine learning algorithms based on boosted decision trees (BDT), are being tested. The paper presents the advantages and disadvantages of these algorithms in numerical simulation and experimental data, obtained during measurements with pulse coherent Doppler lidar.

Citation Download Citation

Ramdas M. Makhmanasarov and Artem M. Sherstobitov "Optimization of mean wind estimation methods from wind lidar's conical scan data", Proc. SPIE 12341, 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 123412X (7 December 2022); https://doi.org/10.1117/12.2644849

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