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Analysis and Empirical Modeling of Ionospheric Horizontal Gradients in the TEC Mapping Onboard LEO Satellites

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The ionospheric mapping function (IMF) is fundamental in retrieving total electron content (TEC) from observations onboard low earth orbiting (LEO) satellites, as well as the receiver differential code bias (DCB)… Click to show full abstract

The ionospheric mapping function (IMF) is fundamental in retrieving total electron content (TEC) from observations onboard low earth orbiting (LEO) satellites, as well as the receiver differential code bias (DCB) estimation. Most IMFs apply the assumption that the electron density field is spherically symmetric, which is only dependent on the elevation angle of signal ray path without considering the azimuthal diversity. However, the ionospheric horizontal asymmetry may introduce large mapping errors in slant to vertical TEC (VTEC) conversion or vice versa especially at low elevation angles. This study investigates the variations of the horizontal gradients in the topside ionosphere and plasmasphere and proposes a formalism for parametrizing the time, location, elevation, and azimuth angle-dependent horizontal gradients based on the global core plasma model (GCPM). Several parameters are estimated to represent the north-to-south, east-to-west asymmetric patterns of slant TEC (STEC) and the horizontal mapping factor with varying elevation angles. Results show that the empirical model of the horizontal gradients is well constructed and contributes positively to reducing the mapping error of VTEC. The root-mean-square (rms) error at all elevation angles is decreased to 0.5 and 1.0 TEC unit (TECU) under low solar activity (LSA) and high solar activity (HSA) conditions, respectively. This approach is potential to be used in the absolute global navigation satellite system (GNSS)/LEO TEC and DCB estimation and topside ionosphere/plasmasphere exploration.

Keywords: ionospheric horizontal; elevation angles; leo; leo satellites; horizontal gradients

Journal Title: IEEE Transactions on Geoscience and Remote Sensing
Year Published: 2022

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