Abstract
Ionospheric tomography reconstruction based on global navigation satellite system observations is usually an ill-posed problem. To resolve it, an adaptive smoothness constraint ionospheric tomography algorithm is proposed in this work. The new algorithm performs an adaptive adjustment for the constrained weight coefficients of the tomography system. The computational efficiency and the reconstructed quality of ionospheric imaging are improved by using the new algorithm. A numerical simulation experiment was conducted in order to validate the feasibility and superiority of the algorithm. The statistical results of the reconstructed errors and the comparisons of ionospheric profiles confirmed the superiority of the new algorithm. Finally, the new algorithm was successfully applied to reconstruct three-dimensional ionospheric images under geomagnetic quiet and geomagnetic disturbance conditions over Hunan province. The tomographic results are reasonable and consistent with the general behavior of the ionosphere. The positive and negative phase storm effects are found during geomagnetic storm occurrence.
Highlights
The ionosphere is the upper atmosphere between 60 km and 1000 km above the earth
ISensors jk; y is2020, the 3,vector of the m known slant total electron content (STEC) measurements; A is a coefficient matrix, the element A3cdof is the length of the cth path in the dth voxel; x is a vector of the unknown Ionospheric electron density (IED); and e is a column vector is the length of the th path in the th voxel; is a vector of the unknown IED; and is a column related to the discretization errors and measurement noises [31]
In order to resolve the ill-posed problem of global navigation satellite system (GNSS)-based ionospheric tomography and the limitation of the conventional multiplicative algebraic reconstruction technique (MART) and the smoothness constraint MART (SCMART), a new ionospheric algorithm is presented in this work
Summary
The ionosphere is the upper atmosphere between 60 km and 1000 km above the earth. The temporal and spatial variations of the ionosphere affect the propagation of radio signals [1,2,3], especially during the occurrence of geomagnetic storms. Introduced the computerized ionospheric tomography technique to reconstruct the IED distributions by using the observations of the navy navigation satellite system. Due to the nonuniform and sparsity of ground GNSS observation stations, the input data of the GNSS-based ionospheric tomography are usually insufficient. This fact makes it an ill-posed problem [22]. The new algorithm adaptively adjusts the horizontal and altitudinal constraint weight coefficients according to the results of the last round of iteration. The algorithm was applied to reconstruct the three-dimension distribution of the IED over Hunan province under geomagnetic quiet and geomagnetic disturbance conditions by using the GNSS observations of the continuously operating reference stations (CORS). The reconstructed error statistics and the comparisons of the hmF2 and NmF2 further verified the superiority of the new algorithm
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