Anomaly Detection and Improving Predictability of GNSS Timing Signal Quality
2025
Olkkonen, Martta-Kaisa | Kotilainen, Mikko | Kaasalainen, Sanna | Ometov, Alexandr | Nurmi, Jari | Lohan, Elena Simona | Benedetto, Francesco | Maanmittauslaitos | National Land Survey of Finland | 0000-0002-5302-081X | 0000-0001-6628-418X
This paper reports work-in-progress in analyzing possible effects in satellite signal quality, especially using CGGTTS data. CGGTTS is currently used by over 70 laboratories [1] to compute the Coordinated Universal Time (UTC) together with Precise Point Positioning [2]. The fundamental method was presented in [3], which was based on REASON (Resilience and security of geospatial data for critical infrastructures) project [4]. REASON was funded by the Research Council of Finland and was focusing on resilience of the timing signal achieved from GNSS. In January 2025, a new project started at Finnish Geospatial Research Institute (FGI) funded by the Research Council of Finland, SURI - Supercomputing GNSS data for Navigation Resilience against Ionospheric Interference [5]. In SURI, our aim is to investigate the effect of ionosphere on the GNSS signal quality, not limited to the timing, but in any application of position, navigation and timing (PNT). We will use in the course of the project the Finnish supercomputer LUMI to have a computationally powerful way to extract from GNSS signal the effect of ionosphere, and separate intentional interference from this. We discuss in this paper some precursors to delving into ionospheric effects on PNT. We discuss in this paper: • how bias and slope of the measurements can be used in prediction of satellite reliability? • effect of satellite position in the sky • effect of satellite aging on predictability of error
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