An Improved Iterative Algorithm for Ionospheric Tomography Reconstruction by Using the Automatic Search Technology of Relaxation Factor

Zheng, Dunyong; Yao, Yibin; Nie, Wenfeng; Yang, Wentao; Hu, Wusheng; Ao, Minsi; Zheng, Hongwei

doi:10.1029/2018rs006588

Cited by 15 publications

(7 citation statements)

References 34 publications

(37 reference statements)

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“…Three‐dimensional computerized ionospheric tomography (3DCIT) technology can provide critical 3D information of ionospheric electron density variations and has now become a powerful new tool for ionospheric research (Zheng et al., 2016, 2018). Ssessanga et al.…”

Section: Introductionmentioning

confidence: 99%

Detection and Three‐Dimensional Reconstruction of Concentric Traveling Ionosphere Disturbances Induced by Hurricane Matthew on 7 October 2016

et al. 2022

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The response of the ionosphere to meteorological events was extensively studied for decades. These studies showed that the dynamic process was an important way of coupling the ionosphere with the lower atmospheres (Artru et al., 2005;Chane-Ming et al., 2002;Hines, 1960). Gravity waves (GWs) caused by deep convections were common in the atmosphere during severe convective meteorological events (Hoffmann & Alexander, 2010;Yue et al., 2013). The small-scale GWs tended to dissipate and break below the top of stratosphere, while medium-scale GWs that have fast-enough horizontal phase speeds can propagate upward into the thermosphere, causing ripples of electron density (

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Section: Introductionmentioning

confidence: 99%

Detection and Three‐Dimensional Reconstruction of Concentric Traveling Ionosphere Disturbances Induced by Hurricane Matthew on 7 October 2016

et al. 2022

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“…Due to the almost vertical GNSS geometry of the ground-based observations, the direct solution of Equation 1 is ill-conditioned to describe the ionosphere using several layers. Ionospheric imaging by CIT is therefore a challenge due to this incomplete geometrical coverage that renders an ill-posed system (e.g., Mitchell & Spencer, 2003;Pryse et al, 1998;Ssessanga et al, 2021;Wen et al, 2008;Yao et al, 2014;Zheng et al, 2018). Hernández-Pajares et al (1999), for instance, use Equation 1 with only two layers in order to solve the ill-conditioned problem.…”

Section: Tomography Formulationmentioning

confidence: 99%

Global‐Scale Ionospheric Tomography During the March 17, 2015 Geomagnetic Storm

et al. 2021

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Measuring the electron density in the ionosphere is an important step to improve our understanding of the solar-terrestrial environment impact on communication, surveillance, and navigation systems. Several methods can be applied to estimate the three-dimensional (3D) electron density in the ionosphere (Bust & Mitchell, 2008). In this context, the computerized ionospheric tomography (CIT) gained attention in the last three decades since it provides accurate observations of the ionospheric electron density over large areas (Austen et al., 1988;Norberg et al., 2018). The main products are 3D spatial fields of the electron density, which evolve with time in a series of snapshots. Over the last 20 years, several achievements have been obtained by CIT techniques. It has been demonstrated that these images can be used to describe the overall ionospheric plasma structure and its temporal evolution in the atmosphere. They have been successfully used to represent important ionospheric dynamics, such as traveling ionospheric disturbances (Bolmgren et al., 2020;Chen et al., 2016), geomagnetic storm signatures

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“…Generally, the relaxation parameter is determined by experience. In order to optimize the relaxation parameter, Zheng et al (2018) [66] proposed an automatic search technology to train the relaxation parameter by the RMSE of STEC in each step of the iteration. A numerical simulation experiment showed the strategy could decrease the absolute error and RMSE, and a real data experiment demonstrated that more reliable IED images were produced with the strategy.…”

Section: Iterative Reconstructionmentioning

confidence: 99%

A Review of Voxel-Based Computerized Ionospheric Tomography with GNSS Ground Receivers

Wan

2021

Remote Sensing

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Ionized by solar radiation, the ionosphere causes a phase rotation or time delay to trans-ionospheric radio waves. Reconstruction of ionospheric electron density profiles with global navigation satellite system (GNSS) observations has become an indispensable technique for various purposes ranging from space physics studies to radio applications. This paper conducts a comprehensive review on the development of voxel-based computerized ionospheric tomography (CIT) in the last 30 years. A brief introduction is given in chronological order starting from the first report of CIT with simulation to the newly proposed voxel-based algorithms for ionospheric event analysis. The statement of the tomographic geometry and voxel models are outlined with the ill-posed and ill-conditioned nature of CIT addressed. With the additional information from other instrumental observations or initial models supplemented to make the coefficient matrix less ill-conditioned, equation constructions are categorized into constraints, virtual data assimilation and multi-source observation fusion. Then, the paper classifies and assesses the voxel-based CIT algorithms of the algebraic method, statistical approach and artificial neural networks for equation solving or electron density estimation. The advantages and limitations of the algorithms are also pointed out. Moreover, the paper illustrates the representative height profiles and two-dimensional images of ionospheric electron densities from CIT. Ionospheric disturbances studied with CIT are presented. It also demonstrates how the CIT benefits ionospheric correction and ionospheric monitoring. Finally, some suggestions are provided for further research about voxel-based CIT.

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An Improved Iterative Algorithm for Ionospheric Tomography Reconstruction by Using the Automatic Search Technology of Relaxation Factor

Cited by 15 publications

References 34 publications

Detection and Three‐Dimensional Reconstruction of Concentric Traveling Ionosphere Disturbances Induced by Hurricane Matthew on 7 October 2016

Detection and Three‐Dimensional Reconstruction of Concentric Traveling Ionosphere Disturbances Induced by Hurricane Matthew on 7 October 2016

Global‐Scale Ionospheric Tomography During the March 17, 2015 Geomagnetic Storm

A Review of Voxel-Based Computerized Ionospheric Tomography with GNSS Ground Receivers

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