Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-28T22:48:57.014Z Has data issue: false hasContentIssue false
  • English
  • Français

Klobuchar-Like Local Model of Quiet Space Weather GPS Ionospheric Delay for Northern Adriatic

Published online by Cambridge University Press:  15 June 2009

Renato Filjar ,
Tomislav Kos  and
Serdjo Kos
Renato Filjar*
Affiliation:
(The Royal Institute of Navigation Croatian Branch)
Tomislav Kos
Affiliation:
(Faculty of Electrical Engineering and Computing, University of Zagreb)
Serdjo Kos
Affiliation:
(Faculty of Maritime Studies, University of Rijeka)
*
(Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Ionospheric delay is the major source of satellite positioning system performance degradation. Designers of satellite positioning systems attempt to mitigate the impact of the ionospheric delay by deployment of correction models. For instance, the American GPS utilises a global standard (Klobuchar) model, based on the assumption that the daily distribution of GPS ionospheric delay values follows a biased cosine curve during day-time, while during the night-time the GPS ionospheric delay remains constant. Providing a compromise between computational complexity and accuracy, the Klobuchar model is capable of correcting up to 70% of actual ionospheric delay, mainly during quiet space weather conditions. Unfortunately, it provides a very poor performance during severe space weather, geomagnetic and ionospheric disturbances. In addition, a global approach in Klobuchar model development did not take into account particularities of the local ionospheric conditions that can significantly contribute to the general GPS ionospheric delay. Current research activities worldwide are concentrating on a better understanding of the observed GPS ionospheric delay dynamics and the relation to local ionosphere conditions.

Here we present the results of a study addressing daily GPS ionospheric delay dynamics observed at a Croatian coastal area of the northern Adriatic (position ϕ=45°N, λ=15°E) in the periods of quiet space weather in 2007. Daily sets of actual GPS ionospheric delay values were assumed to be the time series of composite signals, consisting of DC, cosine and residual components, respectively. Separate models have been developed that describe components of actual GPS ionospheric delay in the northern Adriatic for summer and winter, respectively. A special emphasis was given to the statistical description of the residual component of the daily distribution of GPS ionospheric delay, obtained by removing DC (bias) and cosine components from the composite GPS ionospheric delay.

Future work will be focused on further evaluation and validation of a quiet space weather GPS ionospheric delay model for the northern Adriatic, transition to a non-Klobuchar model, and on research in local GPS ionospheric delay dynamics during disturbed and severe space weather conditions.

Keywords

satellite navigationGPS ionospheric delayspace weatherclassical decomposition
Type
Research Article
Information
The Journal of Navigation , Volume 62 , Issue 3 , July 2009 , pp. 543 - 554
Copyright
Copyright © The Royal Institute of Navigation 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

AIUB. (2008). CODE Archive of the Astronomical Institute of the University of Bern, Switzerland. Available at: ftp://ftp.unibe.ch/aiub/CODE/, accessed on 11 April 2008.Google Scholar
Brockwell, P J, Davis, R A. (2002). Introduction to Time Series and Forecasting (2nd edition). Springer-Verlag, Inc. New York, NY.CrossRefGoogle Scholar
Davis, K. (1991). Inospheric Radio. Peter Peregrinus Ltd. London, UK.Google Scholar
Falk, M et al. (2006). A First Course on Time Series Analysis: Examples with SAS. Chair of Statistics, University of Wuerzburg, Germany. Available at: http://tinyurl.com/yvvnoh, accessed on 3 April 2008.Google Scholar
Filjar, R. (2008). A Study of Direct Space Weather Effects on GPS Ionospheric Delay. Journal of Navigation, 61, 115–128.CrossRefGoogle Scholar
Filjar, R, Kitarović, J, Lakoš, A. (2007). Extension of Standard GPS Ionospheric Model for Quiet Space Weather Conditions. Proc. of NAV07 Conference (on CD, 2 pages). Westminster, London, UK.Google Scholar
Filjar, R, T, Kos. (2006). GPS Positioning Accuracy in Croatia During the Extreme Space Weather Conditions in September 2005. Proc. of the European Navigation Conference ENC 2006 (on CD, 8 pages). Manchester, UK.Google Scholar
Klobuchar, J. (1987). Ionospheric Time-Delay Algorithm for Single-Frequency GPS Users. IEEE Trans. On Aerospace and Electronic Systems, 23, 325–331.CrossRefGoogle Scholar
Misra, P, P, Enge. (2004). Global Positioning System: Signals, Measurements, and Performance (2nd printing). Ganga-Jamuna Press. Lincoln, MA.Google Scholar
NOAA National Geophysical Data Center (NGDC). (2008). Space Physics Interactive Data Resource. Available at: http://spidr.ngdc.noaa.gov/spidr/home.do, accessed on 7 April 2008.Google Scholar
Parkinson, B W, Spilker, J J Jr. (1996). global Positioning System: Theory and Applications (Vol. I.). AIAA. Washington, DC.Google Scholar
Trauth, M H. (2007). MATLAB© Recipes for Earth Sciences. Springer-Verlag. Berlin and Heidelberg, Germany.CrossRefGoogle Scholar
Williams, G P. (1997). Chaos Theory Tamed. Taylor & Francis. London, UK.CrossRefGoogle Scholar