Thesis (Ph. D.)--Civil and Environmental Engineering, Georgia Institute of Technology, 2006. / Dr. William Bachman, Committee Member ; Dr. Peter P. Parsonson, Committee Member ; Dr. Kwok-Leung Tsui, Committee Member ; Dr. John D. Leonard II, Committee Member ; Dr. Karen Dixon, Committee Chair.

Thesis (M.S.)--Ohio University, November, 2005. / Title from PDF t.p. Includes bibliographical references (p. 111-118)

Thesis (M.S.)--Ohio University, June, 2004. / Title from PDF t.p. Includes bibliographical references (p. 131-133)

Thesis (Ph.D.)--Ohio University, August, 2004. / Title from PDF t.p. Includes bibliographical references (p. 177-183)

Thesis (M.S.)--Ohio University, June, 2005. / Title from PDF t.p. Includes bibliographical references (p. 85-86)

Thesis (Ph. D.)--Georgia Institute of Technology, 2006. / Includes bibliographical references (p. 177-183). Also available online via the Georgia Tech ETD Database website (http://etd.gatech.edu/).

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 135-153). Available also in a digital version from Dissertation Abstracts.

Global navigation satellite systems (GNSS), such as the Global Positioning System (GPS) have been increasingly used in navigation and tracking of vehicles. Using GPS, certain positioning errors and limitations, such as multipath effects and the geometric position of the satellites (DOP) or signal obstructions by high buildings, trees and terrain, have to be considered. Generally travel on road or footpath, map-matching algorithms can be used to correlate the computed system location with a digital map network. Map Matched GPS (MMGPS) is a test-bed simulator for researching algorithms and techniques to reduce the error in position provided by a low cost stand-alone GPS receiver. In order to correctly map-match the GPS positions, a decision about the correct road can be difficult, especially at road junctions, slip roads or almost parallel roads. Investigations into the use of artificial neural networks (ANNs) for reliability and accuracy improvement of map-matched GPS positioning was initiated in previous research [Winter, 2002]. However, there are generally strong interference effects that lead to slow learning and poor generalization when a single ANN is trained to perform different subtasks on different occasions [Jacobs et al., 1991], e.g. correct transport network (TN) segment selection considering different TN geometry. Interference can be reduced by training a system composed of several different "expert" ANNs using a TN geometry indicator to decide which of the experts should be used for each training case. An aim of this research was the design, development and implementation of such a modular neural network (MNN). This work uses a new measure for indicating TN geometry, directly derived from GPS positions in MMGPS. An improvement of more than 50% to traditional map-matching techniques was achieved using the proposed MNN approach, when the correct road could not be uniquely identified by map-matching.

The primary aim of this research is to develop and assess the innovative methods and techniques which are used to augment GPS using a variety of digital spatial data. It is well known that the use of GPS can be severely compromised by various error sources such as signal obstructions, multipath and poor satellite geometry etc., especially in highly built-up areas. In order to improve the accuracy and reliability of GPS, complementary data is often combined with GPS data for enhancing the performance of a standalone GPS receiver. Spatial data is one type of complementary data that can be used to augment GPS. However, the potential of using various types of existing and newly acquired spatial data for enhancing GPS performance has not been fully realised. This is particularly true due to the fact that higher accuracy digital surface models (DSMs), which include buildings and vegetation, and digital maps, have only been made widely available in recent years. This thesis will report on a number of experiments that used spatial data of various complexity and accuracy for enhancing GPS performance. These experiments include height aiding with different scale digital terrain models (DTMs); map-matching using odometer data, DTM and road centrelines; modelling and prediction of GPS satellite visibility using DSMs; and prediction of GPS multipath effect using DSMs and building footprints. These experiments are closely related to each other in the sense that GPS and spatial data are combined to provide value-added information for improved modelling and prediction of GPS positioning accuracy and reliability, for applications such as transport navigation and tracking ... Extensive fieldwork has been carried out to verify the developed techniques and methods. The results show that the accuracy of a standalone GPS receiver can be improved by height aiding using a higher resolution DTM and map-matching especially when the satellite geometry is poor. The mean error of single receiver GPS positioning for one particular dataset, on which the described map-matching algorithm was developed, is 8.8m compared with 53.7m for GPS alone. This work was carried out in collaboration with London Transport. In terms of satellite visibility analysis, the results obtained from the fieldwork indicate that greater modelling accuracy has been achieved when using higher resolution DSMs. Furthermore, a ray tracing model was implemented in a 3D GIS environment in order to model reflected and diffracted GPS signals. The Double Differencing (DD) residuals were used to give an indication of the magnitude of the possible pseudorange multipath error caused by diffraction. A single-knife diffraction model was first implemented on 1m Light Detection And Ranging (LiDAR) DSMs, and verified by post-processing (i.e. large DD residuals occurred when the satellites are partially masked and unmasked by buildings), which indicate that GPS multipath prediction with LiDAR data and building footprints is feasible, and has the potential to offer greater modelling accuracy.

Thesis submitted in partial fulfilment of the requirements for the degree Master of Technology: Electrical Engineering in the Faculty of Engineering at the Cape Peninsula University of Technology 2015 / Space-borne GPS receivers designed for nano-satellites are faced with various challenges. This research is undertaken to address the problems of inefficiency and high-costs associated with space-borne GPS receivers. The problem of inefficiency relates to poor performances of the GPS receiver in terms of the algorithmic models, execution speed, memory usage and errors proness. The problem of high-costs relates to the spacegrade hardware cost, implementation complexity, development time, as well as the manufacturing, production and the testing processes involved. The research objectives are to i) establish an efficient high-dynamics software-defined GPS receiver, ii) demonstrate a firmware approach and then iii) postulate a low-cost hardware implementation roadmap. The research methodology employed to address the problems and to attain the objectives is based-on using Matlab computing platform to i) implement a software-defined GPS receiver using free open-source GPS receiver algorithms, ii) further develop the software GPS receiver and lastly iii) convert the improved GPS receiver algorithms to firmware. The GPS receiver was successfully implemented in Matlab floating-point algorithms with a ±100kHz Doppler search bins and was used to post-process a pre-captured real GPS L1 C/A signal dataset. The pre-captured GPS signal was acquired, tracked, decoded and post-processed to extract the navigation message; use to compute the GPS receiver position, UTC date and time. Attempt to convert the entire Matlab floating-point GPS receiver algorithms to equivalent VHDL implementations failed; however, three of the Matlab floating-point algorithms (check_t.m, deg2dms.m and findUtmZone.m), were successfully converted to equivalent fixed-point formats in Matlab, Simulink and finally VHDL. These three algorithms, now created and optimised to fixed-point formats (efficient and enable implementation unto a low-cost microcontroller), set the basis for the firmware implementation. They were simulated and verified in Matlab, Simulink and VHDL using the Matlab HDL Coder workflow. Altera Quartus II software was then used to compile (synthesise, place & route and generate programming files) the three converted generic VHDL algorithms to embedded firmware, suitable for a FPGA programming. The Matlab HDL Coder workflow used in this research is feasible and can be used to accurately design and implement an improved GPS receiver and furthermore achieve it in three equivalent algorithms. This conclusion was drawn and the proposed recommendations are to address the conversion issues in the other Matlab floating-point GPS receiver algorithms that failed in the conversion process and to further develop and implement the GPS receiver as a fully functional unit, based-on the Xilinx space-grade, radiation hardened and low-cost Virtex 5QV FPGA.