The applicability of neural networks to ionospheric modeling in support of relocatable over-the-horizon radar
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Authors
Pinkepank, James Alan
Subjects
NA
Advisors
Collins, Daniel Joseph
Date of Issue
1994-09
Date
September 1994
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
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 flrst 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.
Type
Thesis
Description
Series/Report No
Department
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
41 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.