Investigating GAIM-GM's Capability to Sense Ionospheric Irregularities via Walker Satellite Constellations.

摘要

GAIM-GM is a modularized physics based data assimilation model, which ingests data from multiple data sources. One data source is slant total electron content (TEC) from a ground station network to satellites, and along the occultation path between multiple satellites. This study examines GAIM-GM's capability to sense a depleted region in the ionosphere, overlaid on an IFM electron density grid, from satellite constellations ingesting the slant TEC values into GAIM-GM. Satellite constellations were developed in STK(registered trademark). A real ground station network, generated from IGS, was ingested into STK(registered trademark), to compute access times to the satellite constellation, and compute slant TEC values on the perturbed IFM grid. The size of the feature was varied along with the number of satellites in the Walker constellation. 25 different scenarios with these parameters varied were created to determine the sensitivity of GAIM-GM to sense the feature. A simple heuristic algorithm was applied comparing the truth data, in this case the perturbed IFM grid, to the GAIM-GM output in each scenario across the entire grid, and for those grid points within the feature.