MULTI-GNSS PRECISE POINT POSITIONING WITH INTEGER AMBIGUITY RESOLUTION FOR GEOPHYSICAL APPLICATIONS

This thesis presents a multi-year comparative assessment of Precise Point Positioning with Ambiguity Resolution (PPP-AR) using three major scientific GNSS software packages: Bernese GNSS Software 5.4 (BSW54), PRIDE 3.0 (PRIDE), and GipsyX 2.1 (GOA). Using approximately four years of observations from a globally distributed network, the study investigates the precision of daily coordinate estimates obtained from single- and multi-GNSS constellations, with particular focus on GPS-only, Galileo-only, and combined GPS+Galileo solutions. The results show clear distinctions between software packages, most notably in the East component, where PPP-AR consistently provides the largest improvement in precision. PRIDE achieves gains of up to 51% for Galileo-only, 40% for GPS+Galileo, and 36% for GPS-only, while BSW54 attains corresponding improvements of 33%, 20%, and 8%. Enhancements in the North and Up components are more modest and vary between software and constellation choice, reflecting differences in processing strategies and satellite geometry. Ambiguity resolution is shown to yield systematic advantages over float solutions across all software–constellation combinations, offering the greatest benefit in the East component and contributing meaningfully to the stability of the Up component, particularly in the case of PRIDE. To investigate the temporal characteristics of the resulting coordinate time series, a stochastic noise model combining power-law and white-noise processes is applied. This analysis reveals that PRIDE frequently produces stronger low-frequency noise than BSW54, which in turn influences the uncertainty of long-term velocity estimates. The findings highlight the sensitivity of noise behaviour to both the software architecture and the constellation employed. The study also provides a detailed examination of periodic signals affecting GNSS coordinate time series. Multi-GNSS combinations substantially reduce the influence of constellation-specific periodicities, including draconitic harmonics associated with orbital resonances. Power spectral analyses show that GPS-only solutions contain few prominent resonance features; Galileo-only solutions exhibit weaker harmonics; and GLONASS, by contrast, can introduce significant periodic distortions. Combining constellations with differing resonance characteristics clearly improves the temporal stability and spectral clarity of PPP-AR time series. To separate geophysical signals from software- or constellation-specific effects, suitable loading models are applied, including hydrological, atmospheric, and non-tidal oceanic contributions. Geophysical loading information was employed as a diagnostic tool to assess how environmental signals influence PPP-AR coordinate time series across different software and constellation configurations. Strong hydrological forcing at Brazilian stations leads to pronounced Up-component RMS reductions (approximately 13–25 %), whereas Northern European stations show only modest effects, with Central and Southern Europe exhibiting intermediate and station-dependent behaviour that highlights differing sensitivities between processing software. These regional contrasts demonstrate that environmental signal strength and software implementation jointly shape PPP-AR time series characteristics, without implying long-term geophysical correction or interpretation. Overall, the thesis establishes the significant benefits of PPP-AR, particularly when Galileo is incorporated and multi-GNSS strategies are employed, and provides a robust comparative framework for assessing precision, noise behaviour, and periodic variability across different processing software. The combined insights contribute to more reliable GNSS-based geophysical analyses, improved monitoring of displacement, and a clearer understanding of how software, constellation specific, and geophysical processes collectively influence GNSS time series.