Abstract

A deep neural network (DNN) model designed for the refractive index structure parameter ${\text{C}}_{\text{n}}^2$ prediction based on processing of pupil and focal plane laser beam intensity patterns was used for analysis of turbulence inner and outer scale impact on spatial features of intensity and wavefront phase. Wave-optics numerical simulations were used to generate large datasets of short-exposure intensity distributions in an optical receiver pupil and focal planes for a remotely (7 km) located Gaussian laser beacon under various turbulence distributions and turbulence inner and outer scales. These datasets were used for DNN model training, validation, and inference.

© 2023 The Author(s)