Date of Award:
12-2021
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Mathematics and Statistics
Committee Chair(s)
Kevin R. Moon
Committee
Kevin R. Moon
Committee
John R. Stevens
Committee
Todd K. Moon
Committee
Randy Christensen
Abstract
Unmanned aerial vehicles (UAV) often rely on GPS for navigation. GPS signals, however, are very low in power and easily jammed or otherwise disrupted. This paper presents a method for determining the navigation errors present at the beginning of a GPS-denied period utilizing data from a synthetic aperture radar (SAR) system. This is accomplished by comparing an online-generated SAR image with a reference image obtained a priori. The distortions relative to the reference image are learned and exploited with a convolutional neural network to recover the initial navigational errors, which can be used to recover the true flight trajectory throughout the synthetic aperture. The proposed neural network approach is able to learn to predict the initial errors on both simulated and real SAR image data.
Checksum
b35993b384a8b79670c813e1b877f1e7
Recommended Citation
White, Teresa, "GPS-Denied Navigation Using Synthetic Aperture Radar Images and Neural Networks" (2021). All Graduate Theses and Dissertations, Spring 1920 to Summer 2023. 8228.
https://digitalcommons.usu.edu/etd/8228
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