基于激光强度分布的激光雷达重叠因子计算及其敏感性分析

激光雷达系统是一种功能强大的遥感设备,具有较高的时空分辨率和精度,广泛应用于区域或全球尺度的大气探测。重叠因子是影响激光雷达系统探测近距离大气的一个重要因素,对其进行精确的计算有利于获得准确探测结果。基于激光强度分布的重叠因子计算方法具有简单实用的特点,可应用于任意指定激光强度分布和不同系统参数的激光雷达重叠因子求解。利用该算法对重叠因子进行了计算,并与实验法测量得到的重叠因子进行了对比分析。重点分析了重叠因子对各个参数的敏感性。分析结果为指导激光雷达的系统调试、优化配置和误差控制提供了一定的参考。     

Measurements for profiles of aerosol extinction coefficient,backscatter coefficient,and lidar ratio over Wuhan in China with Raman/Mie lidar

<正>The profiles of aerosol extinction,backscatter coefficient,and lidar ratio in the lower troposphere over Wuhan are measured by a multi-channel Raman/Mie lidar.Using the lidar ratio retrieved by Raman scattering principle,the profiles of aerosol extinction and backscatter coefficients are also retrieved by Mie scattering signals,without a prior assumption about their relation in the traditional pure Mie signals data analyses.The observations by both Raman and Mie are in good agreement with each other.The high coherence shows that the system is reliable,and the Mie and Raman channels are in good adjustment and have the same field of view.     

Comparison of simultaneous signals obtained from a dual-field-of-view lidar and its application to noise reduction based on empirical mode decomposition

Although the empirical mode decomposition (EMD) method is an effective tool for noise reduction in lidar signals, evaluating the effectiveness of the denoising method is difficult. A dual-field-of-view lidar for observing atmospheric aerosols is described. The backscattering signals obtained from two channels have different signal-to-noise ratios (SNRs). The performance of noise reduction can be investigated by comparing the high SNR signal and the denoised low SNR signal without a simulation experiment. With this approach, the signal and noise are extracted to one intrinsic mode function (IMF) by the EMD- based denoising; thus, the threshold method is applied to the IMFs. Experimental results show that the improved threshold method can effectively perform noise reduction while preserving useful sudden-change information.