Spatiotemporal Implicit Neural Representation for Ionospheric Tomography With Multi-LEO Occultation Data (opens in new tab)

Current ionospheric tomography faces a bottleneck: heavy reliance on empirical background fields leads to poor spatiotemporal accuracy and robustness. To resolve this, we propose an inversion strategy fusing interpretability analysis, spatiotemporal implicit neural representation (ST-INR), and the multiplicative algebraic reconstruction technique (MART). By training a physics-informed ST-INR model on multi-LEO satellite occultation data, we overcome the spectral bias of traditional networks t...