Data assimilation of ground GPS total electron content into a physics-based ionospheric model by use of the Kalman filter

摘要

A three-dimensional (3-D) Global Assimilative Ionospheric Model (GAIM) is currently being developed by a joint University of Southern California and Jet Propulsion Laboratory (JPL) team. To estimate the electron density on a global grid, GAIM uses a first-principles ionospheric physics model and the Kalman filter as one of its possible estimation techniques. Because of the large dimension of the state (i.e., electron density on a global 3-D grid), implementation of a full Kalman filter is not computationally feasible. Of the possible suboptimal implementations of the Kalman filter, we have chosen a band-limited Kalman filter where a full time propagation of the state error covariance is performed, but it is always kept sparse and banded. The effectiveness of ground GPS data for specifying the ionosphere is assessed by assimilating slant total electron content (TEC) data from 98 sites into the GAIM Kalman filter and validating the electron density field against independent measurements. A series of GAIM analyses are presented and validated by comparisons to JPL's global ionospheric maps (GIM) of vertical TEC (VTEC) and measurements from TOPEX. A statistical evaluation of GAIM and GIM against TOPEX VTEC indicates that GAIM accuracy is comparable or superior to GIM.