Automated Polarization-Discrimination Technique to Minimize LIDAR Detected Skylight Background Noise, Part I

Much research has been done on lidar Signal-to-Noise Ratio (SNR) improvements, particularly for lidar daytime operations. Skylight background noise confines lidar daytime operations and disturbs the measurement sensitivity. Polarization selective lidar systems have, formerly, been used mostly for separating and analyzing polarization of lidar returns for a variety of purposes. In our previous work, we devised in the remote sensing laboratory at the City College of New York a polarization discrimination technique 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). This tracking technique was achieved by rotating, manually, a combination of polarizer and analyzer on both the lidar transmitter and receiver subsystems, respectively. The polarization orientation at which the minimum BGS occurs, follows the solar azimuth angle, even for high aerosol loading. This has been confirmed both theoretically, assuming single scattering theory, and experimentally. In this article, a design to automate the polarization discrimination technique by real time tracking of the azimuth angle to attain the maximum lidar SNR is presented. With 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 produced results. Analytical results for New York City are summarized and an approach for applying the proposed design globally is investigated.