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

TLDR: In this article, the Levinson recursion algorithm-based Wiener filter over an original lidar signal was proposed to convert an analog signal to virtual count. And the proposed algorithm can be applied to any ground-based lidar system for an accurate profiling of the lower atmospheric compositions.

Abstract: 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.