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Information content of data measured with a multiple-field-of-view lidar

机译:使用多视场激光雷达测量的数据的信息内容

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摘要

Lidars with multiple fields of view (MFOVs) are promising tools for gaining information on cloud particle size. We perform a study of the information content of MFOV lidar data with the use of eigenvalue analysis. The approach we have developed permits an understanding of the main features of MFOV lidars and provides a way to relate the accuracy of particle size estimation with the measurement uncertainty and the scattering geometry such as the cloud-base height and the lidar sounding depth. Second-order scattering computations are performed for an extended range of particle sizes and for a wide range of lidar fields of view (FOVs). The results obtained allow us to specify the areas of possible applications of these lidars in cloud studies. Comparison of results obtained with polarized and cross-polarized scattered components demonstrate that the cross-polarized signal should provide a more stable retrieval and is preferable when double scattering is highly dominant. Our analysis allows for the estimation of the optimal number of FOVs in the system and their angular distribution, so this work can be a useful tool for practical MFOV lidar design.
机译:具有多个视场(MFOV)的激光雷达是获得有关云粒子大小信息的有前途的工具。我们使用特征值分析对MFOV激光雷达数据的信息内容进行了研究。我们开发的方法可以理解MFOV激光雷达的主要特征,并提供一种将粒度估计的准确性与测量不确定性和散射几何关系(例如云基高度和激光雷达探测深度)联系起来的方法。对于较大范围的粒径和较大的激光雷达视场(FOV),执行二阶散射计算。获得的结果使我们能够指定这些激光雷达在云计算研究中可能的应用领域。用偏振和交叉偏振散射分量获得的结果的比较表明,交叉偏振信号应提供更稳定的恢复,并且在双重散射占主导地位时更可取。我们的分析允许估计系统中FOV的最佳数量及其角度分布,因此,这项工作对于实际MFOV激光雷达设计可以是有用的工具。

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