Numerical simulations to assess ART and MART performance for ionospheric tomography of chapman profiles

Abstract

The incomplete geometrical coverage of the Global Navigation Satellite System (GNSS) makes the ionospheric tomographic system an ill-conditioned problem for ionospheric imaging. In order to detect the principal limitations of the ill-conditioned tomographic solutions, numerical simulations of the ionosphere are under constant investigation. In this paper, we show an investigation of the accuracy of Algebraic Reconstruction Technique (ART) and Multiplicative ART (MART) for performing tomographic reconstruction of Chapman profiles using a simulated optimum scenario of GNSS signals tracked by ground-based receivers. Chapman functions were used to represent the ionospheric morphology and a set of analyses was conducted to assess ART and MART performance for estimating the Total Electron Content (TEC) and parameters that describes the Chapman function. The results showed that MART performed better in the reconstruction of the electron density peak and ART gave a better representation for estimating TEC and the shape of the ionosphere. Since we used an optimum scenario of the GNSS signals, the analyses indicate the intrinsic problems that may occur with ART and MART to recover valuable information for many applications of Telecommunication, Spatial Geodesy and Space Weather.