Elastic-lidar signal statistics and sensing efficiency depending on the laser radiation wavelength

Abstract

In the present work, Poisson-fluctuating lidar profiles are modeled statistically as obtained from clear and hazy atmospheres containing Sharan-dust-like layers. The shot-noise fluctuations are simulated in fact induced by the useful signal itself, the optical background, and the dark current in the photon detector. The profiles obtained for UV, VIS and NIR sensing radiations are compared and analyzed. It is shown that the best lidar images of Saharan dust layers are obtainable by using NIR sensing radiation. They are characterized by higher contrast and clarity. The images obtained by using UV or VIS radiation may be entirely masked by shot-noise and even by multiple-scattering due parasitic (bias and random) noise. To clarify the images obtained in this case, by lowering the random noise level, one should average, as shown, the lidar profiles over a series of laser shots and/or smooth them along the lidar line of sight. Certainly, this lowers the temporal and/or spatial resolution of sensing by UV and VIS radiation. Thus, the results obtained confirm and illustrate the advantages of the NIR wavelength range, when sensing dense compact aerosol objects, predicted previously by the mean profiles investigated of the lidar signal strength and signal-to-noise ratio.