Plane wave parameter estimation using gps estimates of total electron content in a neural network

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2018

Author dc:creator

• Smith, Aaron David

Contributors dc:contributor

• Makela, Jonathan J.

• GPS
• Global Positioning System
• Neural Network
• Total Electron Content
• TEC
• TID
• Traveling Ionospheric Disturbance
• Plane Wave
• Estimation
• Doppler
• Tohoku
• Pierce Point

Statement dc:rights

• Copyright 2018 Aaron Smith

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/101095

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/101095