Kalman filter-based algorithms for monitoring the ionosphere and plasmasphere with GPS in near-real time

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.

[1]  Gregory Bishop,et al.  The effect of the protonosphere on the estimation of GPS total electron content: Validation using model simulations , 1999 .

[2]  A. Astilean,et al.  Near real-time monitoring of the ionosphere using dual frequency GPS data in a Kalman filter approach , 2008, 2008 IEEE International Conference on Automation, Quality and Testing, Robotics.

[3]  A. Mazzella,et al.  The protonospheric contribution to GPS total electron content: Two‐station measurements , 1999 .

[4]  L. Ciraolo,et al.  Comparison of ionospheric total electron content from the Navy Navigation Satellite System and the GPS , 1997 .

[5]  Paul D. Craven,et al.  Global Core Plasma Model , 2000 .

[6]  C. F. Minter,et al.  A comparison of Magic and FORTE ionosphere measurements , 2007 .

[7]  L. Kersley,et al.  The influence of the protonosphere on GPS observations: Model simulations , 1999 .

[8]  R. Anderson,et al.  An ISEE/Whistler model of equatorial electron density in the magnetosphere , 1992 .

[9]  Mark B. Moldwin,et al.  Global plasmaspheric TEC and its relative contribution to GPS TEC , 2008 .

[10]  Y. Otsuka,et al.  Plasmaspheric electron content in the GPS ray paths over Japan under magnetically quiet conditions at high solar activity , 2002 .

[11]  E. Essex,et al.  Vertical E × B drift velocity variations and associated low-latitude ionospheric irregularities investigated with the TOPEX and GPS satellite data , 2003 .

[12]  C. Mcilwain,et al.  Coordinates for Mapping the Distribution of Magnetically Trapped Particles , 1961 .

[13]  Xiaoqing Pi,et al.  A new ionospheric model for wide area differential GPS: the multiple shell approach , 2002 .

[14]  Jaume Sanz,et al.  A two‐layer model of the ionosphere using Global Positioning System data , 1997 .

[15]  Takuya Tsugawa,et al.  A new technique for mapping of total electron content using GPS network in Japan , 2002 .

[16]  G. Kotova The Earth’s plasmasphere: State of studies (a Review) , 2007 .

[17]  A. Mazzella,et al.  The contribution of the protonosphere to GPS total electron content: Experimental measurements , 1999 .

[18]  T. Moore,et al.  On the azimuthal variation of core plasma in the equatorial magnetosphere , 1995 .

[19]  Bodo W. Reinisch,et al.  Plasmaspheric electron content derived from GPS TEC and digisonde ionograms , 2004 .

[20]  J. Chau,et al.  Interplanetary electric fields and their relationship to low-latitude electric fields under disturbed conditions , 2007 .

[21]  J. Klobuchar,et al.  Storm associated protonospheric depletion and recovery , 1980 .

[22]  E. Essex,et al.  A dynamic global model of the plasmasphere , 2004 .

[23]  P.S.J. Spencer,et al.  Ionospheric data assimilation methods for geodetic applications , 2004, PLANS 2004. Position Location and Navigation Symposium (IEEE Cat. No.04CH37556).

[24]  J. Klobuchar,et al.  Comparison of protonospheric electron content measurements from the American and European sectors , 1978 .

[25]  Mohinder S. Grewal,et al.  Global Positioning Systems, Inertial Navigation, and Integration , 2000 .

[26]  Paul D. Craven,et al.  An empirical model of the earth's plasmasphere , 1988 .

[27]  Gregory Bishop,et al.  Autonomous estimation of plasmasphere content using GPS measurements , 2002 .

[28]  S. Thampi,et al.  Plasmaspheric electron content (PEC) over low latitude regions around the magnetic equator in the Indian sector during different geophysical conditions , 2008 .