A modified three-dimensional ionospheric tomography algorithm with side rays

Yao, Yibin; Zhai, Changzhi; Kong, Jian; Zhao, Qingzhi; Zhao, Chunhua

doi:10.1007/s10291-018-0772-4

Cited by 17 publications

(9 citation statements)

References 45 publications

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“…The ionospheric tomography technique was first introduced to the ionospheric community by Austen et al (1986). Since then, the technique has become a powerful tool for imaging the 3‐D ionospheric structures (Bust & Mitchell, 2008; Kong et al, 2016; Mitchell et al, 2002; Tang et al, 2015; Wen et al, 2011; Yao et al, 2018). Yizengaw and Moldwin (2005) reconstructed the ionospheric electron density structure at a specific longitude, and through comparing with the IMAGE Extreme Ultraviolet (EUV) observations, he confirmed the connection between the plasmapause position and the midlatitude trough.…”

Section: Discussionmentioning

confidence: 99%

“…The three‐dimensional computerized ionospheric tomography (3DCIT) technique is a powerful tool for ionospheric imaging. Using GPS ground receivers and radio occultation measurements, 3DCIT is capable of reconstructing the time evolution of the 3‐D ionospheric electron density distributions (Austen et al, 1986; Bust & Mitchell, 2008; Kong et al, 2016; Wen et al, 2011; Yao et al, 2018). Yin et al (2006) studied the hmF 2 variations during three geomagnetic storms using the Multi‐instrument Data Analysis System (MIDAS) (Mitchell et al, 2002), and their results showed a dramatic increase of hmF 2 during geomagnetic storms.…”

Section: Introductionmentioning

confidence: 99%

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3‐D Tomographic Reconstruction of SED Plume During 17 March 2013 Storm

Zhai

Yao

et al. 2020

JGR Space Physics

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The three-dimensional computerized ionospheric tomography (3DCIT) technique is used to reconstruct the spatial distribution of storm-enhanced density (SED) based on the global positioning system total electron content measurements over the North American area during the 17 March 2013 storm. The reconstruction results are carefully validated with observations from three ionosonde stations, the constellation observing system for meteorology, ionosphere, and climate (COSMIC) radio occultations, and the Millstone Hill incoherent scatter radar. The electron density profiles from the 3DCIT reconstruction show a good agreement with the ionosonde and COSMIC electron density profiles. The 3DCIT-derived electron density difference between the storm day of 17 March and the quiet day of 16 March also captures the similar SED plume signature that was observed by the Millstone Hill incoherent scatter radar. The 3DCIT reconstruction allows us for the first time to unveil the 3-D configuration of the SED plume and its spatiotemporal evolution. It was found that the SED plume first appeared around 400 km and then expanded downward to~300 km as well as upward to~500 km over the course of a 3-hr period from 19 to 22 UT on 17 March. Our study also showed that the density enhancement within the SED plume occurred mostly above the storm time F layer peak height.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

3‐D Tomographic Reconstruction of SED Plume During 17 March 2013 Storm

Zhai

Yao

et al. 2020

JGR Space Physics

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“…Although all the voxels in the reconstructed area are illuminated with the virtual rays added, the results of CIT may be limited by the precision of the virtual TEC. Yao et al (2018) [50] utilized the NeQuick 2 model to repair the TEC with partial rays beyond the boundary (see Figure 1 in [50]). Therefore, the unavailable observations were converted into virtual observations on the edge or bottom side.…”

Section: Virtual Data Assimilationmentioning

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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“…As they therefore only partially coincide with the inversion volume, they are traditionally not employed in ionospheric tomography, since the part of the STEC originating for the inversion volume is unknown. According to the method described by Yao et al [40], partial STECs (PSTECs) can be determined for the side rays by…”

Section: Computerized Iionospheric Tomography (Cit)mentioning

confidence: 99%

Nadir-Dependent GNSS Code Biases and Their Effect on 2D and 3D Ionosphere Modeling

Håkansson

2020

Remote Sensing

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Recent publications have shown that group delay variations are present in the code observables of the BeiDou system, as well as to a lesser degree in the code observables of the global positioning system (GPS). These variations could potentially affect precise point positioning, integer ambiguity resolution by the Hatch-Melbourne-Wübbena linear combination, and total electron content estimation for ionosphere modeling from global navigation satellite system (GNSS) observations. The latter is an important characteristic of the ionosphere and a prerequisite in some applications of precise positioning. By analyzing the residuals from total electron content estimation, the existence of group delay variations was confirmed by a method independent of the methods previously used. It also provides knowledge of the effects of group delay variations on ionosphere modeling. These biases were confirmed both for two-dimensional ionosphere modeling by the thin shell model, as well as for three-dimensional ionosphere modeling using tomographic inversion. BeiDou group delay variations were prominent and consistent in the residuals for both the two-dimensional and three-dimensional case of ionosphere modeling, while GPS group delay variations were smaller and could not be confirmed due to the accuracy limitations of the ionospheric models. Group delay variations were, to a larger extent, absorbed by the ionospheric model when three-dimensional ionospheric tomography was performed in comparison with two-dimensional modeling.computerized ionospheric tomography (CIT) [2][3][4], techniques that were inspired by and have emerged from computerized tomography (CT) for medical applications [5].GNSS hardware biases [6], and especially biases in the code observations, are well-known to affect the estimation of TEC from GNSS observations [7][8][9]. These biases, referred to as differential code biases (DCBs), are regarded as constant offsets between code observations associated with two signals transmitted between the same satellite and receiver. Thereby, an offset exists in addition to the expected offset due to different ionospheric influence caused by the difference in carrier frequencies. However, even though these biases have been assumed to be constant, recent findings by Hauschild et al. [10], Wanninger and Beer [11], and Wanninger et al. [12] show that the code biases also have a nadir-dependent component, with the largest effects shown for BeiDou [11], but with measurable effects also shown for other GNSSs [12]. These varying biases of the code observables are also referred to as group delay variations (GDV).Previous studies by Wanninger and Beer [11] and Wanninger, Sumaya, and Beer [12] have shown that nadir-dependent GDV affect precise point positioning (PPP) based on the single frequency ionosphere-free combination, wide-lane ambiguity fixing based on the Hatch-Melbourne-Wübbena linear combination [13][14][15], as well as TEC estimation of the ionosphere. The latter is an important characteristic of the ionosphere and is necess...

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A modified three-dimensional ionospheric tomography algorithm with side rays

Cited by 17 publications

References 45 publications

3‐D Tomographic Reconstruction of SED Plume During 17 March 2013 Storm

3‐D Tomographic Reconstruction of SED Plume During 17 March 2013 Storm

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

Nadir-Dependent GNSS Code Biases and Their Effect on 2D and 3D Ionosphere Modeling

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