|Abstract:||An important characteristic of the GPS constellation is that the same satellite appears in the same part of the sky with a period of approximately 4 minutes less than one day. During this period a GPS satellite completes exactly two orbits in inertial space whereas the Earth completes one revolution. This brings the same ray path geometry when looking to the same satellite from a location on Earth. This repetition is known to be used in mitigating local multipath noises in the received signals. In the present study we found that this repetition can be successfully used for predicting TEC along a receiver-satellite link. We assume that looking to a satellite in the same part of the sky from the same location on Earth brings nearly the same geophysical conditions for link related TEC estimation. Furthermore, assuming a regular ionospheric behaviour usually justified when geomagnetic conditions are quiet, the TEC can be assumed to be dependent only on the solar activity level during two consecutive days. However, the solar radiation varies every day and influences the level of the total ionization. We found that during quiet ionospheric condition our approach can predict slant TEC at a mid-latitude station with mean and standard deviations from reference values of about 0 and 1.5 TECU (1 TECU = 1.e+16 el/m2), respectively. During perturbed condition the mean and standard deviations are found as about 0 and 3.9 TECU, respectively. We found that our new approach can successfully predict slant TEC several hours in advance if severe ionospheric storms are excluded.|
Proceedings of the 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016)
September 12 - 16, 2016
Oregon Convention Center
|Pages:||1649 - 1656|
|Cite this article:||
Hoque, M.M., Jakowski, N., Berdermann, J., "A New Approach for Ionospheric TEC Prediction at a GPS Station," Proceedings of the 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016), Portland, Oregon, September 2016, pp. 1649-1656.
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