Cairo University

MTPR Journal

 

ELASTIC BACKSCATTER LIDAR SIGNAL TO NOISE RATIO IMPROVEMENT FOR DAYLIGHT OPERATIONS: POLARIZATION SELECTION AND AUTOMATION

& doi: https://doi.org/10.1142/9789814317511_0020
YASSER Y. HASSEBO and KHALED ELSAYED
Math/Engineering Dept., LaGuardia Community College of the City University of New York, 31-10 Thomson Ave., Long Island City, NY 11101, USA
Department of Physics, Faculty of Science, Cairo University, Egypt

Vol./Issue: 11 , id: 323

Signal-to-Noise Ratio (SNR) improvements is one of the important issue in lidar measurements, particularly for lidar daytime operations. Skylight background noise precincts lidar daytime operations and disturbs the measurement sensitivity. In the past, polarization selective lidar systems have been used mostly for separating and analyzing polarization of lidar returns for a variety of purposes. A polarization discrimination technique was proposed to maximize lidar detected SNR taking advantage of the natural polarization properties of scattered skylight radiation to track and minimize detected sky background noise (BGS). In our previous work this tracking technique was achieved by rotating, manually, a combination of polarizer and analyzer on both the lidar transmitter and receiver subsystems, respectively. Minimum BGS take place at polarization orientation that follows the solar azimuth angle, even for high aerosol loading. In this article, we report a design to automate the polarization discrimination technique by real time tracking of the azimuth angle to attain the maximum lidar SNR. Using an appropriate control system, it would then be possible to track the minimum BGS by rotating the detector analyzer and the transmission polarizer simultaneously, achieving the same manually obtained results. Analytical results for New York City are summarized and an approach for applying the proposed design globally is investigated.