Revisiting Ionospheric Tomography: Neutral Atmospheric Signatures and Neural Radiance Models 

The global coverage of total electron content measurements (TEC) from ground-based receivers and Low Earth Orbit constellations offers an opportunity to extract new insights into the ionosphere. In this work, we present a unified framework for reconstructing ionospheric electron density volumes by combining slant TEC observations from both ground-based and spaceborne receivers.Our approach relies on vertical parameterizations of the electron density profile, which we constrain horizontally through spatial interpolation and optimize via nonlinear fitting of integrated TEC. Preliminary results demonstrate how this framework can resolve fine-scale ionospheric structures using low-dimensional parameterization for modeling gravity wave signatures in the linear regime and recovering their features in multiple dimensions. Furthermore, we will present preliminary results of tomographic reconstructions using a neural radiance field approach adapted from recent advances in view synthesis. These results highlight the potential of hybrid TEC datasets to provide volumetric reconstructions of ionospheric structure, specifically the ones driven by modulations from the neutral atmosphere.