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.
Highlights
The Global Navigation Satellite System (GNSS) has emerged in recent decades as an effective technology for imaging the morphology and dynamics of the ionosphere
The first analysis (Case I) was constructed using the initial condition shown in Figure 2, but the electron density peak nm was doubled for the image to retrieve Total Electron Content (TEC) observations
The parameters hm, nm and Hs were calculated at each latitude based on the ionospheric profiles obtained from the image used for the initial condition, the image to retrieve TEC observations, the Algebraic Reconstruction Technique (ART) reconstructions and the Multiplicative ART (MART) reconstructions
Summary
The Global Navigation Satellite System (GNSS) has emerged in recent decades as an effective technology for imaging the morphology and dynamics of the ionosphere. Important contributions of GNSS have been developed by many researches in order to provide valuable information of the FABRICIO S. The accuracy of the ionospheric delay to be used in GNSS positioning is compromised (Brunini et al 2004) and GNSS data for applications that analyze the vertical morphology of the ionosphere is restricted. Due to the community’s interest in recovering vertical information, tomographic reconstruction techniques linked to GNSS observations began to be used to reconstruct electronic density information
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