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Investigation on the performance of Levinson recursion algorithm-based Wiener filter in gluing ground-based lidar signals

机译：基于Levinson递归算法的维纳滤波器在粘合地基激光雷达信号中的性能研究

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摘要

The ground-based lidar is an active remote sensing instrument to profile the lower atmosphere effectively. In general, a lidar receives an analog signal from a lower altitude, a photon count from a higher altitude, and glues them in order to profile the atmosphere effectively. We propose the Levinson recursion algorithm-based Wiener filter over an original lidar signal to convert an analog signal to virtual count. This count is further glued with photon counting through mean square error method, and the results are compared with the linear regression algorithm. It is found that the proposed algorithm enhances the scaled analog from 152 to 8780 MHz in 355 nm, 131 to 3591 MHz in 387 nm, and 79 to 2956 MHz in 408 nm wavelengths. Furthermore, the improvement in correlation coefficients is found to be 0.9899, 0.9942, and 0.9807 for 355,387, and 408 nm wavelengths, respectively. The proposed algorithm can be applied to any ground-based lidar system for an accurate profiling of the lower atmospheric compositions.
机译：基于地面的LIDAR是一种有效的遥感仪器，可有效地进行较低的大气。通常，LIDAR接收来自较低海拔的模拟信号，从更高的高度的光子计数，并粘附它们以有效地介绍气氛。我们在原始LIDAR信号上提出基于Levinson递归算法的维纳滤波器，以将模拟信号转换为虚拟计数。该计数进一步用光子计数通过均方误差方法进行胶合，并将结果与​​线性回归算法进行比较。发现该算法在387nm中，在355nm，131至3591MHz的355nm，131至3591MHz中的缩放模拟增强了355nm，79至2956 MHz。此外，对于355,387和408nm波长，相关系数的改善分别为0.9899,0.9942和0.9807。该算法可以应用于任何基于地基的激光雷达系统，用于较低大气组合物的精确分析。

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