Deep echo state neural network model for light propagation through strong atmospheric turbulence

Michael D. DeAntonio; Steven Sandoval

doi:10.1117/12.2586517

12 April 2021 Deep echo state neural network model for light propagation through strong atmospheric turbulence

Proceedings Volume 11740, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXII; 117400G (2021) https://doi.org/10.1117/12.2586517
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

A Deep Echo State Neural Network is used to predict total intensity at a detector, standard deviation of intensity over the area of a detector, and center-of-intensity for a deep turbulence example. A short description of the reason for choosing a Deep Echo State Network, as well as a full description of the network optimization and an example using 30 seconds of data is given. Specifically, indications are that this type of network can handle the nonstationary and nonlinear aspects of laser propagation through long distance deep atmospheric turbulence. The network shows a remarkable ability to predict future signals. At this time, more work needs to be done on optimizing the network to achieve even better results.

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Citation Download Citation

Michael D. DeAntonio and Steven Sandoval "Deep echo state neural network model for light propagation through strong atmospheric turbulence", Proc. SPIE 11740, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXII, 117400G (12 April 2021); https://doi.org/10.1117/12.2586517

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