Kalman filter-based algorithms for monitoring the ionosphere and plasmasphere with GPS in near-real time |
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| Authors: | Adela Anghel Charles Carrano Attila Komjathy Adina Astilean Tiberiu Letia |
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| Institution: | 1. Cooperative Institute for Research in Environmental Sciences, University of Colorado, CO, USA;2. Atmospheric and Environmental Research Inc., Lexington, MA, USA;3. NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA;4. Department of Automation and Computer Science, Technical University of Cluj-Napoca, Romania;1. Shanghai Astronomical Observatory, University of Chinese Academy of Sciences, Shanghai, China;2. Key Laboratory of Earthquake Prediction, Institute of Earthquake Science, China Earthquake Administration, Beijing, China;1. Key Laboratory of Earthquake Geodesy, Institute of Seismology, CEA, Wuhan 430071, China;2. COSMIC Program Office, University Corporation for Atmospheric Research, Boulder, CO, USA;1. Institute of Information and Communication Technology, Bulgarian Academy of Sciences, Acad. G. Bonchev str., bl. 25a, Sofia 1113, Bulgaria;2. Haystack Observatory, Massachusetts Institute of Technology, Westford, 01886 MA, USA;3. Bulgarian Academy of Sciences, Acad. G. Bonchev str., bl. 3, Sofia 1113, Bulgaria;1. National Space Science Center, Chinese Academy of Sciences, Beijing 100190, PR China;2. University of Chinese Academy of Sciences, Beijing 100049, PR China;3. Key Laboratory of Science and Technology on Environment Space Situation Awareness, Chinese Academy of Sciences, Beijing 100190, PR China;4. Yunnan University, Kunming, Yunnan 650091, PR China |
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| Abstract: | Data collected from a GPS receiver located at low latitudes in the American sector are used to investigate the performance of the WinTEC algorithm Anghel et al., 2008a, Kalman filter-based algorithm for near realtime monitoring of the ionosphere using dual frequency GPS data. GPS Solutions, accepted for publication; for different ionospheric modeling techniques: the single-shell linear, quadratic, and cubic approaches, and the multi-shell linear approach. Our results indicate that the quadratic and cubic approaches perform much better than the single-shell and multi-shell linear approaches in terms of post-fit residuals. The performance of the algorithm for the cubic approach is then further tested by comparing the vertical TEC predicted by WinTEC and USTEC Spencer et al., 2004. Ionospheric data assimilation methods for geodetic applications. In: Proceedings of IEEE PLANS, Monterey, CA, 26–29 April, pp. 510–517] at five North American stations. In addition, since the GPS-derived total electron content (TEC) contains contributions from both ionospheric and plasmaspheric sections of the GPS ray paths, in an effort to improve the accuracy of the TEC retrievals, a new data assimilation module that uses background information from an empirical plasmaspheric model Gallagher et al., 1988. An empirical model of the Earth's plasmasphere. Advances in Space Research 8, (8)15–(8)24] has been incorporated into the WinTEC algorithm. The new Kalman filter-based algorithm estimates both the ionospheric and plasmaspheric electron contents, the combined satellite and receiver biases, and the estimation error covariance matrix, in a single-site or network solution. To evaluate the effect of the plasmaspheric component on the estimated biases and total TEC and to assess the performance of the newly developed algorithm, we compare the WinTEC results, with and without the plasmaspheric term included, at three GPS receivers located at different latitudes in the American sector, during a solar minimum period characterized by quiet and moderate geomagnetic conditions. We also investigate the consistency of our plasmaspheric results by taking advantage of the specific donut-shaped geometry of the plasmasphere and applying the technique at 12 stations distributed roughly over four geomagnetic latitudes and three longitude sectors. |
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