DECONVOLUTION ALGORITHM IN LIDAR SENSING WITH COMPLEX LASER PULSE SHAPING
Authors:
1.
Institut optiki atmosfery im. V.E. Zueva SO RAN
2.
Institut optiki atmosfery im. V.E. Zueva SO RAN
3.
Pukyong National University
4.
Hanbat National University
5.
Pukyong National University
Type:
Сonference article
Pages:
from 368
to 371
Published:
17.08.2026
Subject area:
UDC 544.032.65
UDC 520.874.7
UDC 520.874.7
Language:
Russian
Keywords:
remote sensing, low clouds, deconvolution
Funding:
The work was carried out within the framework of a state assignment of the V.E. Zuev Institute of Atmospheric Optics of the Siberian Branch of the Russian Academy of Sciences.
Abstract:
Low-level cloud formations are of significant interest to researchers. These cloud structures frequently exhibit minimal optical thickness, typically around 0.2 or less. Ground-based lidar systems are preferentially employed for probing such cloud types. A fiber-optic lidar system utilizing a Q-switched laser proves effective for this application. During the preliminary data processing stage, it is imperative to account for the complex pulse shape of the Q-switched laser emission; thus, signal deconvolution techniques are applied to the lidar sounding data. This study elucidates an optimal deconvolution algorithm for lidar sounding signals characterized by a complex laser pulse shape. The research outcomes demonstrate the potential of the selected direction in lidar sensing development.
Low-level cloud formations are of significant interest to researchers. These cloud structures frequently exhibit minimal optical thickness, typically around 0.2 or less. Ground-based lidar systems are preferentially employed for probing such cloud types. A fiber-optic lidar system utilizing a Q-switched laser proves effective for this application. During the preliminary data processing stage, it is imperative to account for the complex pulse shape of the Q-switched laser emission; thus, signal deconvolution techniques are applied to the lidar sounding data. This study elucidates an optimal deconvolution algorithm for lidar sounding signals characterized by a complex laser pulse shape. The research outcomes demonstrate the potential of the selected direction in lidar sensing development.
Keywords:
remote sensing, low clouds, deconvolution
remote sensing, low clouds, deconvolution
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