Ionospheric Imaging for Canadian Polar Regions - AL-FANEK, OSSAMA JAMIL SALEH (Graduate Studies, 2013)
Global Navigation Satellite Systems (GNSS) can be exploited as a cost-effective tool to remotely sense the Earth’s ionosphere and investigate its characteristics. This is due to the global coverage and dual frequency data availability offered through worldwide networks of GNSS stations. Since the ionosphere is a dispersive medium, the dual frequency data can be utilized to derive highly accurate Slant Total Electron Content (STEC) measurements. STEC is defined as the integration of the free electron distribution in a 1-m2 column along the signal path from the satellite to the receiver. Although STEC provides a valuable source of information about the ionosphere, these measurements do not contain any spatial information about the electron density distribution along the line-of-sight. Therefore, a tomographic technique is required to retrieve such three-dimensional information. Measurement of the polar ionosphere is challenging due to its variable nature and typically limited availability of ground (or space) based infrastructure for remote sensing. An opportunity exists to exploit GNSS observations for ionospheric imaging in this region. Ten GNSS reference stations of the Canadian High Arctic Ionospheric Network (CHAIN), augmented with six International GNSS Service (IGS) polar reference stations, provides sufficient observations for GNSS-based tomographic estimation of key polar ionospheric parameters. Polar implementation of tomographic imaging for such a sparse network presents major challenges, however, and requires novel methods. In this thesis, a novel Computerized Ionospheric Tomographic (CIT) reconstruction technique is developed to estimate electron density profiles over the Canadian polar region. This technique divides the ionosphere into voxels where the electron density is assumed to be homogeneous within a voxel. A functional based model is used to represent the electron density in space. The functional based model uses Empirical Orthogonal Functions (EOF) and Spherical Cap Harmonics (SCH) to ...