Precise Global Navigation Satellite system (GNSS) positioning and navigation in remote areas

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The Global Positioning System (GPS) has become the preeminent method of outdoor positioning and navigation. Research has focused on improvement of receiver (and antenna) design and data processing algorithms, which have driven unpredicted application growth and diversity. Most contemporary high-precision algorithm development has focused on applications spanning localized areas (e.g., few tens of kilometres), utilizing costly GPS infrastructure, particularly reference stations, to reduce systematic measurement errors. The fundamental goal of the proposed research program is to improve positioning and navigation algorithms in remote areas, such as regions of low population density and the coastal offshore that cannot financially or physically support such investments, addressing the question of how to perform centimetre-level positioning hundreds of kilometres from a reference station. Further incentive for this research is coming from GPS constellation upgrades and the development of similar global and regional systems. This Global Navigation Satellite System (GNSS) "evolution" will greatly increase the measurement strength of positioning algorithms and allow for substantial algorithm development. I propose to build on my previous and current novel research in two forms of positioning and navigation algorithms: long-range Real-Time Kinematic (RTK) and Precise Point Positioning (PPP). There are four themes to the proposed research plan: 1) improving long range RTK by utilizing contemporary empirical and physics-based atmospheric refraction models, 2) improving PPP positioning capabilities (accuracy, filter convergence period and integrity) by enhancing algorithms and introducing external noise mitigation data sources, 3) combining RTK and PPP to improve positioning performance and reduce costs, and 4) predicting how GNSS evolution will affect these developed solutions and our remote location positioning abilities. Research results will be used to increase productivity and improve safety-of-life applications across numerous economic sectors, and advance scientific applications, via the dissemination of algorithms and methods through publications, technology transfers and commercialization.