Internal anisotropy of the turbulent scintillations

Mikhail Charnotskii

doi:10.1117/12.2053339

9 June 2014 Internal anisotropy of the turbulent scintillations

Mikhail Charnotskii

Proceedings Volume 9080, Laser Radar Technology and Applications XIX; and Atmospheric Propagation XI; 908014 (2014) https://doi.org/10.1117/12.2053339
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

We introduce a new concept of the Internal Anisotropy (IA) for the homogeneous and isotropic random fields. IA reflects the hidden structures that can exist in the samples of the random field, and are not revealed by the simplest, single and two-point statistical moments. There is presently no established theory of the IA, and no quantitative metrics of IA are available. It is understood, however, that IA cannot be present in any stationary isotropic Gaussian random field, or any single-point transformations of it. We illustrate the IA concept on a simple toy model of two-dimensional random field, and show that IA can affect the third and higher-order multipoint statistical moments. We generate samples of the random irradiance distributions for the plane wave passed through a phase screen with the quasi- Kolmogorov statistics. Visual evaluation suggests the presence of the IA in the irradiance samples. The statistical analysis reveals that the three-point third moment of irradiance exhibit the features consistent with the IA, especially in the focusing conditions. Conditional probabilities of the irradiance gradient components also proved to be sensitive to the IA. We discuss the role of the IA for optimal placement of the multiple receivers of the FSO system using the spatial diversity for fade mitigation.

Citation Download Citation

Mikhail Charnotskii "Internal anisotropy of the turbulent scintillations", Proc. SPIE 9080, Laser Radar Technology and Applications XIX; and Atmospheric Propagation XI, 908014 (9 June 2014); https://doi.org/10.1117/12.2053339

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KEYWORDS

Scintillation

Receivers

Anisotropy

Turbulence

Visualization

Statistical analysis

Statistical modeling

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