Gaussian Markov random field priors in ionospheric 3D multi-instrument tomography

• Published in: IEEE Transactions on Geoscience and Remote Sensing
• Main Authors: Norberg, J., Vierinen, Juha, Roininen, L, Orispää, M., Kauristie, K, Rideout, W., Coster, A. J., Lehtinen, M
• Format: Article in Journal/Newspaper
• Language: English
• Published: IEEE 2018
• Subjects: VDP::Mathematics and natural science: 400::Geosciences: 450::Other geosciences: 469; VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Andre geofag: 469; VDP::Mathematics and natural science: 400::Physics: 430::Astrophysics; astronomy: 438; VDP::Matematikk og Naturvitenskap: 400::Fysikk: 430::Astrofysikk; astronomi: 438; Bayesian; Gaussian Markov random fields (GMRFs); Ionospheric tomography; Multi-instrument; Langmuir; Fennoscandia
• Online Access: https://hdl.handle.net/10037/15387; https://doi.org/10.1109/TGRS.2018.2847026

Source at https://doi.org/10.1109/TGRS.2018.2847026 . In ionospheric tomography, the atmospheric electron density is reconstructed from different electron density related measurements, most often from ground-based measurements of satellite signals. Typically, ionospheric tomography suffers from two...