使用拉曼-米激光雷达在南京北郊进行常规性检测, 通过分析激光雷达回波信号, 借助气溶胶质量浓度的线性模型和指数模型进行气溶胶质量浓度空间垂直分布反演。为提高反演的精确度, 对米散射信号进行近场修正, 消除重叠因子的影响, 拉曼散射信号进行小波分析等去噪方法处理。处理过的米散射信号用来反演0~3 km大气的气溶胶质量浓度, 拉曼散射信号用来反演3 km~10 km大气的气溶胶质量浓度, 然后通过2个信号拼接反演中低层气溶胶质量浓度。实验结果: 2种模型反演的气溶胶质量浓度在不同时刻的相关性系数为0.991和0.973 6, 具有一定的可信度。

Routine tests were conducted by using Raman-Mie lidar in the northern suburb of Nanjing.Through the analysis of the lidar echo sinal,aerosol mass concentration profile was inversed with the aid of aerosol mass concentration of linear model and exponential model.In order to improve the accuracy of the inversion,first of all,the Mie scattering signal near field was corrected,eliminating the influence of overlap factor.And denoising methods were used to deal with Raman scattering signal such as wavelet analysis.Secondly the Mie scattering signal was used to inverse the 0~3 km atmospheric aerosol mass concentration,the Raman scattering signal was used to inverse the 3 km~10 km atmospheric aerosol mass concentration,and then the two signals were spliced.Experimental results show that the correlation coefficient of aerosol mass concentration in different time is 0.991 and 0.973 6 inversed with two kinds of models, which is reliable.