@article{Sikirica_Hedji_MikÅAa_BrĨic_Cirikovic_Filjar_2025,
	author = {Sikirica, Nenad and Hedji, Ivan and MikÅAa, Marko and BrĨic, David and Cirikovic, Enes and Filjar, Renato},
	title = {An Assessment of Long-term Spatial Agnosticism of GNSS Positioning Degradation Risks Due to Ionospheric Conditions},
	journal = {TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation},
	volume = {19},
	number = {1},
	pages = {85-89},
	year = {2025},
	url = {./Article_An_Assessment_of_Long-term_Spatial_Sikirica,73,1481.html},
	abstract = {The Global Navigations Satellite Systems (GNSS) have been evolved into an essential infrastructure of modern civilisation, a public goods, and enabler of rapidly growing number of technology and socio-economic applications. However, GNSS applications often lack fundamental details on GNSS Positioning, Navigation, and Timing (PNT services performance to define and determine their Quality of Service (QoS). The lack of alignment with the core GNSS PNT deprives GNSS applications of assessing the risks of the GNSS PNT utilisation, thus leaving GNSS applications unable to prepare alternatives and mitigate the causes of GNSS PNT performance disruptions. Here we contributed to solution of the problem with the introduction and long-term performance assessment of the risk model of ionospheric-caused GNSS positioning degradation. Called the Probability of Occurrence (PoO), our team defined the risk model of GNSS positioning degradation caused by ionospheric conditions based on the long term observations of occurrences of degraded GNSS positioning performance. In the process of the GNSS risk model validation, the long-term PoO risk models are developed using the annual 2014 stationary GNSS horizontal positioning error observations derived from the GNSS pseudoranges collected at the International GNSS Service (IGS) reference stations situated in polar (Iqaluit, Canada) and sub-equatorial regions (Darwin, Australia). Two GNSS risk models are compared for similarity using statistical methods of Hausdorff distance and CramĆ©rā€“von Mises statistical test. Research results show that two GNSS risk models are spatially agnostic, since no significant difference in two long-term GNSS risk models is found. The research results supports the conclusion of generality of the PoO GNSS risk model, and its ability to serve GNSS applications developers, operators, and users in determination of the QoS of particular GNSS applications.},
	doi = {10.12716/1001.19.01.11},
	issn = {2083-6473},
	publisher = {Gdynia Maritime University, Faculty of Navigation},
	keywords = {Risk Assessment, Accuracy, Positioning, Navigation and Timing (PNT), GNSS, Positioning, Statistical Analysis, Ionosphere, Space Weather}
}