瑞利散射多普勒激光雷达风场反演方法

Wind retrieval algorithm of Rayleigh Doppler lidar

介绍了瑞利散射多普勒激光雷达的风场探测原理和系统结构.给出了Fabry-Perot(FP)标准具透过率曲线的校准方法.指出对透过率采用Lorentz或Voigt拟合会产生较大误差,特别是采用Lorentz拟合最大将引起8%的误差.提出了采用非线性最小二乘法拟合标准具的透过率函数,该方法可以有效消除拟合误差,提高风速测量精度.考虑到温度不确定度在风场反演过程中的主导影响,提出了同时反演风速和大气温度的非线性迭代算法.风场反演仿真试验结果表明:在不考虑米散射信号的影响下,该反演算法与传统的反演方法相比能够有效提高风场反演精度;在考虑了米散射信号的影响下,该方法反演精度会降低,但仍优于传统的风速反演方法.

The wind measurement principle and the structure of Rayleigh Doppler lidar are introduced. The method for FabryPerot（FP） etalon transmission curve calibration is given. The problem is pointed out that to fit the transmission curve by using Lorentz or Voigt function may induce large error： the relative error would be up to 8% by Lorentz fitting especially. A least-square nonlinear fitting procedure is proposed, which can eliminate the fitting error and improve the wind precision. After the dominant role that the temperature uncertainty plays in wind retrieval process is considered, a nonlinear iterative algorithm is proposed, which can retrieve both wind temperature and atmospheric temperature. Simulation results show that the algorithm proposed can improve wind retrieval accuracy effectively compared with the traditional method without the Mie-induced effect, and the wind retrieval accuracy of the algorithm proposed will be degraded with Mie-induced effect but still better than that of traditional method.