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Dissertation/Thesis Abstract

An algorithm for accurate ionospheric total electron content and receiver bias estimation using GPS measurements
by Bourne, Harrison W., M.S., Colorado State University, 2016, 125; 10138910
Abstract (Summary)

The ionospheric total electron content (TEC) is the integrated electron density across a unit area. TEC is an important property of the ionosphere. Accurate estimation of TEC and TEC spatial distributions are needed for many space-based applications such as precise positioning, navigation, and timing. The Global Positioning System (GPS) provides one of the most versatile methods for measuring the ionosphere TEC, as it has global coverage, high temporal resolution, and relatively high spatial resolution. The objective of this thesis is to develop an algorithm for accurate estimation of the TEC using dual-frequency GPS receiver measurements and simultaneously estimate the receiver hardware bias in order to mitigate its effect on the TEC. This method assumes the TEC in the portion of sky visible to the receiver can be represented as a two dimensional sheet with an absolute value and spacial gradients with respect to latitude and longitude. A code-phase multipath noise estimation algorithm is integrated with the TEC estimation process to mitigate environmental multipath contamination of the measurements. The integrated algorithm produces an approximate map of local TEC using a single dual-frequency receiver while minimizing both multipath induced errors and the receiver hardware bias. The goal of this method is to provide an accurate map of the ionosphere TEC, in the region local to the receiver, without the need for a network of receivers and in the absence of knowledge of the receiver hardware induced bias. This thesis describes the algorithm, its implementation, and attempts to validate the method through comparison with incoherent scatter radar (ISR) data from low, mid, and high latitude locations.

Indexing (document details)
Advisor: Morton, Yu
Commitee: Arabi, Mazdak, Kreidenweis, Sonia, Van Graas, Frank
School: Colorado State University
Department: Electrical and Computer Engineering
School Location: United States -- Colorado
Source: MAI 55/05M(E), Masters Abstracts International
Subjects: Electrical engineering, Remote sensing
Keywords: Electron density, GPS, Ionosphere
Publication Number: 10138910
ISBN: 978-1-339-94466-1
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