Probability density function of the intensity of a laser beam propagating in the maritime environment

Abstract

A number of field experiments measuring the fluctuating intensity of a laser beam propagating along horizontal paths in the maritime environment is performed over sub-kilometer distances at the United States Naval Academy. Both above the ground and over the water links are explored. Two different detection schemes, one photographing the beam on a white board, and the other capturing the beam directly using a ccd sensor, gave consistent results. The probability density function (pdf) of the fluctuating intensity is reconstructed with the help of two theoretical models: the Gamma-Gamma and the Gamma-Laguerre, and compared with the intensity's histograms. It is found that the on-ground experimental results are in good agreement with theoretical predictions. The results obtained above the water paths lead to appreciable discrepancies, especially in the case of the Gamma-Gamma model. These discrepancies are attributed to the presence of the various scatterers along the path of the beam, such as water droplets, aerosols and other airborne particles. Our paper's main contribution is providing a methodology for computing the pdf function of the laser beam intensity in the maritime environment using field measurements.

Probability density function estimation of laser light scintillation via Bayesian mixtures

“…Each run consisted of 3636 frames, taken using a Ophir-Spiricon CCD Laser Beam Profiler, Model BG-USB-SP620, operating at 30 Hz, from which we computed the average hot pixel and extracted our time series from that location. For consistency with previous work, we normalized the data as in [13] and [14] by first subtracting the minimum intensity of the dataset and then dividing by the mean. As in [14], we choose to model the average hot pixel.…”

“…For consistency with previous work, we normalized the data as in [13] and [14] by first subtracting the minimum intensity of the dataset and then dividing by the mean. As in [14], we choose to model the average hot pixel. We acknowledge that other methods of averaging or aggregation exist.…”

“…That is, it does not assume that the PDF of the observed data must follow a basic functional form of the PDF, but instead creates highly flexible PDFs by modulating a gamma distribution using weighted Laguerre polynomials. This approach has been used recently in [14].…”

“…Second, the approach is highly sensitive to outliers in the higher order moments, meaning that the number of moments considered is usually driven by computational considerations [15]. This sensitivity to outliers also causes significant oscillations of the PDF [14,17]. Finally, the number of moments considered has a significant effect on the resultant shape of the PDF [13].…”

Average Polarization of Electromagnetic Gaussian Schell-Model Beams through Anisotropic Non-Kolmogorov Turbulence

“…Korotkova et al providing a methodology for computing the probability density function of the laser beam intensity in the maritime environment using field measurements [16] and Cui et al [17] derived a new analytic expression of the MTF to describe the degrading effects of marine atmospheric turbulence on an optical imaging system. The polarization fluctuation model of GSM beams propagating through the anisotropic non-Kolmogorov turbulence of marine/terrene-atmosphere was obtained under the restrain of turbulence with the Prandtl number Pr = 0.72 and the Obukhov-Corrsin coefficient β = 0.72 in the narrow range of the spectral index of nonKolmogorov turbulence 3.47 < α < 3.87 [18].…”