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Linear approximation of Rayleigh-Brillouin scattering spectra

机译:瑞利-布里渊散射光谱的线性近似

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摘要

Rayleigh-Brillouin scattering is the basis of many remote sensing techniques, including high spectral resolution lidar measurements of aerosols and wind. Rayleigh-Brillouin spectra can be accurately estimated using physics-based models like the so-called Tenti's S6 and Pan's S7 models. Unfortunately, these are computationally expensive and can be the bottleneck for real-time lidar processing and iterative parameter estimation problems. This short article describes a very efficient linear approximation of the Rayleigh-Brillouin spectra based on Principal Component Analysis (PCA). Using PCA, the outputs of the above models can be approximated with very high accuracy using a single matrix multiplication. The described method can be applied to the output of any detailed scattering model, thus it can be used for a wide range of problems, e.g., for scattering from different gases (Air, N-2, O-2, ...) and for different ranges of temperature and pressure. The precision of the approximation can be adapted to the requirements of the studied problem, and can easily exceed the actual accuracy of the reference models. (C) 2016 Optical Society of America
机译:瑞利-布里渊散射是许多遥感技术的基础,包括对气溶胶和风的高光谱分辨率激光雷达测量。瑞利-布里渊光谱可以使用基于物理学的模型(如所谓的Tenti's S6和Pan's S7模型)进行精确估算。不幸的是,这些计算量很大,并且可能成为实时激光雷达处理和迭代参数估计问题的瓶颈。这篇简短的文章描述了基于主成分分析(PCA)的瑞利-布里渊光谱的非常有效的线性近似。使用PCA,可以使用单矩阵乘法以非常高的精度近似上述模型的输出。所描述的方法可以应用于任何详细散射模型的输出,因此可以用于各种问题,例如,用于从不同气体(空气,N-2,O-2,...)和适用于不同的温度和压力范围。逼近的精度可以适应所研究问题的要求,并且可以轻松超过参考模型的实际精度。 (C)2016美国眼镜学会

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