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@MALES-project

MALES-project

Machine Learning for Single Star Scidar

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Abstract

Optical satellite communications is a growing research field with bright commercial perspectives. One of the challenges for optical links through the atmosphere is turbulence, which is also apparent by the twinkling of stars. The reduction of the quality can be calculated, but it needs the turbulence strength over the path the optical beam is running. Estimation of the turbulence strength is done at astronomic sites, but not at rural or urban sites. To be able to do this, a simple instrument is required. We want to propose to use a single star Scintillation Detection and Ranging (SCIDAR), which is an instrument that can estimate the turbulence strength, based on the observation of a single star. Here, reliable signal processing of the received images of the star is most challenging. We propose to solve this by Machine Learning.

Resources

Glossary

  • NNs: Neural Networks
  • SCIDAR: Scintillation Detection and Ranging

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