Document Type
Article
Publication Date
7-2020
Abstract
We advance the benefits of previously reported four-dimensional (4-D) weather cubes toward the creation of high-fidelity cloud-free line-of-sight (CFLOS) beam propagation for realistic assessment of autotracked/dynamically routed free-space optical (FSO) communication datalink concepts. The weather cubes accrue parameterization of optical effects and custom atmospheric resolution through implementation of numerical weather prediction data in the Laser Environmental Effects Definition and Reference atmospheric characterization and radiative transfer code. 4-D weather cube analyses have recently been expanded to accurately assess system performance (probabilistic climatologies and performance forecasts) at any wavelength/frequency or spectral band in the absence of field tests and employment data. The 4-D weather cubes initialize an engineering propagation code; which provides the basis for comparative percentile performance binning of FSO communication bit error rates (BERs) as a function of wide-ranging azimuth/elevation; earth-to-space uplinks. The aggregated; comparative BER binning analyzes for different regions; times of day; and seasons applying a full year of 4-D weather cubes data provided numerous occasions of clouds; fogs; and precipitation events. The analysis demonstrated the utility of 4-D weather cubes for adroit management of CFLOS opportunities to enhance performance analyses of point-to-point as well as evolving multilayer wireless network concepts.
Source Publication
Optical Engineering
Recommended Citation
Steven T. Fiorino, Santasri R. Bose-Pillai, Jaclyn Schmidt, Brannon Elmore, and Kevin Keefer "Implications of four-dimensional weather cubes for improved cloud-free line-of-sight assessments of free-space optical communications link performance," Optical Engineering 59(8), 081808 (17 July 2020). https://doi.org/10.1117/1.OE.59.8.081808
Comments
© The Author(s). Published by SPIE under a Creative Commons Attribution 4.0 Unported License. (CC BY 4.0) Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
At time of publication, Jaclyn Schmidt, Brannon Elmore, and Kevin J. Keefer were also research staff contractors in the Department of Engineering Physics at AFIT.
Funding note: This work was supported by the DoD High Performance Computing Modernization Program (HPCMP) and their Workforce Development HPC Internship Program (HIP) initiative. The authors would like to acknowledge Josiah Bills, a 2018 HIP intern, for his significant contributions to this study.