MIDN 1/C Christopher D. Jellen - 13th Company
A Machine-Learning Model for Prediction of Optical Turbulence in Near-Maritime Environments
Advisers: Associate Professor John Burkhardt, Professor Cody J. Brownell, Mechanical Engineering Department, Assistant Professor Charles Nelson, Electrical and Computer Engineering DepartmentMajor: Mechanical and Nuclear Engineering Department
Description:
Laser based weapons and communication systems employed by the Navy are subject to atmospheric effects which limit their effectiveness. As a beam propagates it is subject to fluctuations in the refractive index of air. These effects can be modeled as optical turbulence, a phenomenon which can significantly reduce the operational effectiveness of naval laser systems. The current study uses one year of field measurements collected along a scintillometer link over water, as well as corresponding measurements of environmental parameters. Fully data-driven models were trained and tested to enhance prediction accuracy and better understand the underlying physical relationships which affect optical turbulence in the near-maritime environment.