3-D Computerized Ionospheric Tomography with GPS, SAR, and Ionosonde

The GPS-based computerized ionospheric tomography (CIT) has the capacity to reconstruct the three-dimensional ionosphere (i.e., electron density distribution), making it one of the most important techniques for ionospheric observation. However, the CIT technology is unable of high vertical resolutio...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2023-01, Vol.61, p.1-1
Main Authors: Wang, Cheng, Guo, Wu-Long, Zhang, Qing-He, Zhao, Hai-Sheng, Cao, Le
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
computerized ionospheric tomography (CIT)
Density distribution
Density measurement
Density profiles
electron density profile
Electron density profiles
Electrons
Global Positioning System
Global positioning systems
GPS
Hafnium
Image reconstruction
Ionosondes
Ionosphere
Iterative algorithms
Iterative methods
Phased Array L-band Synthetic Aperture Radar (PALSAR)
Phased arrays
Positioning systems
Radar arrays
SAR (radar)
Satellite observation
Scattering
Spaceborne radar
Synthetic aperture radar
Tomography
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Summary:The GPS-based computerized ionospheric tomography (CIT) has the capacity to reconstruct the three-dimensional ionosphere (i.e., electron density distribution), making it one of the most important techniques for ionospheric observation. However, the CIT technology is unable of high vertical resolution due to the restricted viewing angle. Therefore, the precision of CIT cannot be substantially enhanced with GPS only. Aiming at this issue, this paper proposes a bi-iteration algorithm that integrates GPS, Phased Array L-band Synthetic Aperture Radar on board the Advanced Land Observing Satellite (ALOS PALSAR), and ionosonde data. The key is that the joint retrieval of PALSAR and ionosonde may offer high-precision one-dimensional electron density profile along the whole path, which can effectively enhance the authenticity of the iterative initial value. The corrected initial value is then fused into the process of CIT, which can finally improve the precision of vertical resolution after two iterations. Experimental verification demonstrates that due to the ability to obtain more realistic initial values, the reconstruction accuracy of the algorithm proposed in this paper is 51.4 percent and 45.1 percent higher than the accuracy with GPS alone and with GPS and ionosonde data, respectively. This indicates that the combination of these three kinds of data can effectively improve the precision of CIT.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2023.3285744