Laser beam atmospheric propagation modelling for aerospace LIDAR applications

Atmospheric effects have a significant impact on the performance of airborne and space laser systems. Traditional methods used to predict propagation effects rely heavily on simplified assumptions of the atmospheric properties and of the interactions with the laser systems. These models need to be continually improved to develop high-resolution predictors of laser performance for applications including LIDAR (light detection and ranging), free-space optical communications, remote sensing, etc. The underlying causes of laser beam attenuation in the atmosphere are examined with particular focus on dominant linear effects: absorption, scattering, turbulence, and non-linear thermal effects such as blooming, kinetic cooling, and bleaching. These phenomena are quantitatively analyzed, highlighting the key assumptions made in the empirical modelling. Absorption and scattering, as the dominant causes of attenuation, are generally well applied in models, but the impact of non-linear phenomena is less well captured and applied as it tends to be application specific. Atmospheric radiative transfer codes, such as MODTRAN, ARTS, etc., and the associated spectral databases, such as HITRAN, are the effective implementation of the total propagative effects on the laser systems. These codes are powerful, widely used tools to analyze performance. However, atmospheric radiative transfer codes make several assumptions that reduce accuracy in favor of faster processing. The key atmospheric radiative transfer models are reviewed highlighting the associated methodologies, assumptions, and application. Empirical models are found to offer a robust analysis of atmospheric propagation, which is particularly well-suited for design, development, test and evaluation (DDT&E) purposes. As such, empirical, semi-empirical, and ensemble methodologies are suggested to compliment and augment the existing atmospheric radiative transfer codes. There is scope to evolve the numerical codes and empirical approaches to better suit aerospace applications, where fast analysis is required over a range of slant paths, incidence angles, altitudes, and atmospheric properties, which are not exhaustively captured in current quantitative performance assessment methods.