A PIM-Aided Kalman filter for GPS tomography of the ionospheric electron content

We develop the formalism to perform PIM I-based stochastic tomography of th e ionospheric electron content with a Kalman filter, in which the inversion problem associated with four-dimensional ionospheric stochastic tomography is regularized. For consistency, GPS data is used to select dynamically th e best PIM parameters, in a 3DVAR fashion. We demonstrate the ingestion of( IGS and GPS/MET) GPS data into a parameterized ionospheric model, in order to select the set of parameters that minimize a suitable cost functional. T he resulting PIM-fitted model is compared to direct 3D voxel tomography. We demonstrate the value of this method analyzing IGS and GPS/MET GPS data, a nd present our results in terms of a 4D model of the ionospheric electronic density. (C) 1999 Elsevier Science Ltd. All rights reserved.