Navigation Using High-Frequency Ground Beacons and Ionosphere Model Corrections

Abstract

This thesis defines and analyzes a navigation concept that relies on passive one-way ranging using pseudorange and beat carrier phase measurements of High-Frequency (HF) beacon signals that travel along non-line-of-sight paths via ionosphere refraction. The concept is being considered as a possible alternative to GNSS positioning and timing services. The proposed system uses an array of ground stations that are placed at known, predetermined locations. HF signals are simultaneously transmitted from these ground-based beacons, and received at an unknown single receiver location. If the set of signals that reaches the user equipment receiver has sufficient geometric diversity, then the position and the clock offset of the receiver can be determined uniquely. A significant challenge arises from ionospheric modeling uncertainties that cause errors in the determination of signal ray paths. Erroneous signal paths result in errors in the estimated user equipment position and clock offset. This challenge is addressed by estimating corrections to a parametric model of the ionosphere as part of the navigation solution. The coupled estimation problem is solved with a batch filter that simultaneously estimates the user equipment position, the clock offset, and corrections to an a priori ionosphere model. The first part of this dissertation includes a theoretical background review, derivation of mathematical models, and descriptions of the structures of the developed batch filters. It considers two filter versions of this study that rely on two different physical models for the propagating HF signals. The second part of the dissertation is dedicated to a system performance analysis and an assessment of algorithm functionality. This analysis is based on using data from a truth-model simulation. This is followed by a discussion that assesses performance sensitivities to setup characteristics. A follow-on effort to this study is proposed, one in which algorithm functionality and performance would be examined with actual recorded data for input and signal processing. This proposed work is beyond the scope of this dissertation.