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Dst Index as a Potential Indicator of Approaching GNSS Performance Deterioration

Published online by Cambridge University Press:  10 July 2012

Renato Filjar*
Affiliation:
(GNSS Space Weather Laboratory, Faculty of Maritime Studies, University of Rijeka, Croatia)
Serdjo Kos
Affiliation:
(GNSS Space Weather Laboratory, Faculty of Maritime Studies, University of Rijeka, Croatia)
Siniša Krajnovic
Affiliation:
(LM Ericsson, Stockholm, Sweden)
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Abstract

Space weather disturbances cause considerable effects on Global Navigation Satellite Systems (GNSS) performance and operation, affecting society and the economy due to the growing reliance on GNSS, especially in densely populated mid-latitudes. Recent studies hypothesised potential utilisation of the Disturbance storm-time (Dst) index for indication of an approaching ionospheric storm and possible deterioration of the GNSS positioning performance. We challenged the hypothesis in the case of the Halloween 2003 event in an attempt to confirm the direct correlation between the Dst index dynamics and the Global Positioning System (GPS) positioning performance in the mid-latitude Mediterranean area. Our results provide no evidence of the direct Dst-GNSS performance correlation for the observed event.

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Forum
Copyright
Copyright © The Royal Institute of Navigation 2012
Figure 0

Figure 1. The large ionospheric storm occurred in the period between 27 October 2003 (day 300) and 1 November 2003 (day 305), a phenomenon known as the Halloween 2003 event.

Figure 1

Figure 2. Northing error observed at the reference station Medicina, Italy during the Halloween 2003 event.

Figure 2

Figure 3. Easting error observed at the reference station Medicina, Italy during the Halloween 2003 event.

Figure 3

Figure 4. Height error observed at the reference station Medicina, Italy during the Halloween 2003 event.

Figure 4

Figure 5. Cross-correlation between time series of hourly Dst observations and GPS positioning northing errors.

Figure 5

Figure 6. Cross-correlation between time series of hourly Dst observations and GPS positioning easting errors.

Figure 6

Figure 7. Cross-correlation between time series of hourly Dst observations and GPS positioning height errors.

Figure 7

Figure 8. Simple Moving Average (SMA) smoothed time series of northing error observations.

Figure 8

Figure 9. Decomposition of northing error time series.

Figure 9

Figure 10. Simple Moving Average (SMA) smoothed time series of easting error observations.

Figure 10

Figure 11. Decomposition of easting error time series.

Figure 11

Figure 12. Simple Moving Average (SMA) smoothed time series of height error observations.

Figure 12

Figure 13. Decomposition of height error time series.