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

Ramdas Makhmanasarov, A. M. Sherstobitov
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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.
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基于风激光雷达锥形扫描数据的平均风估计方法优化
比较了利用圆锥扫描数据估计水平风速的计算时间和误差。目前正在测试直接和滤波正弦波拟合算法的各种实现,以及基于增强决策树(BDT)的机器学习算法。本文从数值模拟和脉冲相干多普勒激光雷达测量的实验数据中介绍了这些算法的优缺点。
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