Plane wave parameter estimation using gps estimates of total electron content in a neural network
Smith, Aaron David
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https://hdl.handle.net/2142/101095
Description
Title
Plane wave parameter estimation using gps estimates of total electron content in a neural network
Author(s)
Smith, Aaron David
Issue Date
2018-04-26
Director of Research (if dissertation) or Advisor (if thesis)
Makela, Jonathan J.
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
GPS
Global Positioning System
Neural Network
Total Electron Content
TEC
TID
Traveling Ionospheric Disturbance
Plane Wave
Estimation
Doppler
Tohoku
Pierce Point
Abstract
Global Positioning System (GPS) signals provide us with a unique opportunity to continually monitor the free electron density in the ionosphere. Physical phenomena, such as tsunamis, have been shown to create wave features in the free electron density. The parameterization of these waves is of interest to the scientific community. Here, we investigate the application of neural networks as our parameter estimator. In this study, we provide a background on the use of GPS signals, as used to quantify the total number of free electrons between a satellite and a receiver. Following this, we provide an analysis of the neural network, starting from a basic neuron, and discuss the means by which a network is able to perform both classification and regression. We then describe in detail the methodology we use to construct a network which utilizes Doppler frequency and velocity information to estimate the waveheading, wavelength, and frequency of a plane wave. After an evaluation of our simulated environment, we apply our network to GPS data captured during the 11 March 2011 Tohoku tsunami.
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