提出了一种基于遗传算法进行频谱估计的相干多普勒测风激光雷达三维风场反演方法。该方法无需对视向风速进行计算,可以直接从多方位频谱密度中提取三维风场信息,能够提高弱信噪比情况下的数据反演精度。采用的遗传算法为针对相干激光雷达改进的遗传算法,能够准确、快速、并行地反演出风矢量解。对算法进行了仿真,结果显示,改进后的遗传算法在收敛速度以及全局寻优能力方面相对于传统遗传算法都有着明显提升,并且在低信噪比信号仿真对比中,此方法风场反演结果优于传统非线性最小二乘法反演结果。将该方法应用于实际雷达系统中,在激光雷达与探空气球实测数据对比中,两者水平风速均方根误差小于0.7 m/s,水平风向标准偏差小于6°,这些结果验证了风场反演结果的精确性。将采用所提方法得到的结果与实测数据最小二乘法风场反演结果进行对比,发现在当时的大气条件下,频谱估计法约有12.3%的探测距离的增大。仿真和实测数据对比结果充分证明了此方法反演三维风场的能力和有效性。

A three-dimensional (3D) wind field inversion method of a coherent Doppler wind lidar based on genetic algorithm for spectrum estimation is proposed. The method can obtain 3D wind vectors directly from the multi-directional power spectral density without estimating the radial wind velocities, which can improve the data inversion accuracy in the case of low signal-to-noise ratio (SNR). The genetic algorithm adopted is an improved genetic algorithm for the coherent lidar, which can accurately, quickly, and parallelly retrieve the wind vector. Simulation is performed by the proposed genetic algorithm, and results show that the improved genetic algorithm has a significant improvement in convergence speed and global optimization ability compared to the traditional genetic algorithm. In the low SNR signal simulation comparison, the wind field inversion result of this method is better than that of the traditional nonlinear least squares method. The method has been applied to actual lidar systems. In the comparison of the measured data of the lidar and sounding balloons, the root mean square error of the horizonal wind speed is less than 0.7 m/s, and the standard deviation of the horizontal wind direction is less than 6°. The accuracy of the wind field inversion results is verified. By comparing the results of the proposed method with the results of the least squares wind field inversion of the measured data, we find that under the atmosphere conditions at that time, the proposed method increases the detection range by about 12.3%. The comparison between simulation and measured data fully proves the ability and effectiveness of the proposed method to retrieve the 3D wind field.