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Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS)

ISSN:2141-7016

Article Title: Regional Assessment of the GPS Tropospheric Delay Models on the African GNSS Network
by Dodo, J. D. and Idowu, T. O

Abstract:
Recently, considerable interest has been generated in the use of the Global Positioning System (GPS) for meteorological application leading to what is now called GPS Meteorology. A major source of error in the measurements, for GPS meteorology, is the propagation delay of the GPS signal caused by the two main layers of the atmosphere. These are the ionosphere and troposphere. The ionospheric effects can be mitigated by the use of double difference ionosphere-free linear combination. The tropospheric effects, on the other hand, are reduced to the barest minimum using the global tropospheric models, derived experimentally and based on the available radiosonde data. In order to determine a suitable tropospheric model for African GNSS network, an investigation on the reliability of the different standard tropospheric models is needed. Therefore, it is the objective of this paper to assess the reliability of the three standard tropospheric models for the reduction of topospheric effect in GPS observations. The models used are the refined Saastamoinen model, the modified Hopfield model and Neil model. The results show that there are insignificant differences in the performance of the three models at significance level of 0.05. However, the refined Saastamoinen model seems to produce a better mitigation of the tropospheric effect with an average percentage of 33.6% while Neil and modified Hopfield models have 13.8% and 12.5% percentages respectively. The result further indicates that the refined Saastamoinen model has the lowest mean average zenith tropospheric delay (ZTD) of 2.1m with RMS of 0.0051m. This suggests that the refined Saastamoinen model has better performance than Hopfield and Neil models.
Keywords: African GNSS, tropospheric delay, refined saastamoinen model, neil model and modified hopfield model.
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ISSN: 2141-7016

Editor in Chief.

Prof. Gui Yun Tian
Professor of Sensor Technologies
School of Electrical, Electronic and Computer Engineering
University of Newcastle
United Kingdom

 

 

Copyright © Journal of Emerging Trends in Engineering and Applied Sciences 2010