The Applicability of Neural Networks to Ionospheric Modeling in Support of Relocatable Over-The-Horizon Radar

Abstract

Ionospheric models have been developed to interpret Relocatable Over- the-Horizon Radar data. This thesis examines the applicability of neural networks to ionospheric modeling in support of Relocatable Over-the-Horizon Radar. Two neural networks were used for this investigation. The first network was trained and tested on experimental ionospheric sounding data. Results showed neural networks are excellent at modeling ionospheric data for a given day. The second network was trained on ionospheric models and tested on experimental data. Results showed neural networks are able to learn many ionospheric models and the modeling network generally agreed with the experimental data. Ionosphere research, Ionospheric forecasting, Ionospheric radio wave propagation, Neural networks, Over-the-horizon radar.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1994
Accession Number
ADA286114

Entities

People

  • James A. Pinkepank

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Aeronautics
  • Algorithms
  • Atmospheres
  • Computers
  • Diurnal Variations
  • Experimental Data
  • Information Processing
  • Information Systems
  • Ionosondes
  • Ionosphere
  • Ionospheric Models
  • Neural Networks
  • Operating Systems
  • Processing Equipment
  • Radio Waves
  • Uss Carl Vinson
  • Wave Propagation

Fields of Study

  • Environmental science

Readers

  • Computational Modeling and Simulation
  • Radar Systems Engineering.
  • Space/Atmospheric Physics.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks