Simulation studies on the tomographic reconstruction of the equatorial and low-latitude ionosphere in the context of the Indian tomography experiment: CRABEX

• Main Authors: S. V. Thampi, T. K. Pant, S. Ravindran, C. V. Devasia, R. Sridharan
• Format: Article
• Language: English
• Published: Copernicus Publications 2004-11-01
• Series: Annales Geophysicae
• Online Access: https://www.ann-geophys.net/22/3445/2004/angeo-22-3445-2004.pdf

Equatorial ionosphere poses a challenge to any algorithm that is used for tomographic reconstruction because of the phenomena like the Equatorial Ionization Anomaly (EIA) and Equatorial Spread F (ESF). Any tomographic reconstruction of ionospheric density distributions in the equatorial region is not acceptable if it does not image these phenomena, which exhibit large spatial and temporal variability, to a reasonable accuracy. The accuracy of the reconstructed image generally depends on many factors, such as the satellite-receiver configuration, the ray path modelling, grid intersections and finally, the reconstruction algorithm. The present simulation study is performed to examine these in the context of the operational Coherent Radio Beacon Experiment (CRABEX) network just commenced in India. The feasibility of using this network for the studies of the equatorial and low-latitude ionosphere over Indian longitudes has been investigated through simulations. The electron density distributions that are characteristic of EIA and ESF are fed into various simulations and the reconstructed tomograms are investigated in terms of their reproducing capabilities. It is seen that, with the present receiver chain existing from 8.5° N to 34° N, it would be possible to obtain accurate images of EIA and the plasma bubbles. The Singular Value Decomposition (SVD) algorithm has been used for the inversion procedure in this study. As is known, by the very nature of ionospheric tomography experiments, the received data contain various kinds of errors, like the measurement and discretization errors. The sensitivity of the inversion algorithm, SVD in the present case, to these errors has also been investigated and quantified.