[1] With the current data availability from both ground- and space-based sources, the network of ground-based Global Positioning System (GPS) receivers, GPS occultation receivers, in situ electron density sensors, and dual-frequency beacon transmitters, the time is right for a comprehensive review of the history, current state, and future directions of ionospheric imaging. A brief introduction and history of ionospheric imaging is presented, beginning with computerized ionospheric tomography. Then, a comprehensive review of the current state of ionospheric imaging is presented. The ability of imaging algorithms to ingest multiple types of data and use advanced inverse techniques borrowed from meteorological data assimilation to produce four-dimensional images of electron density is discussed. Particular emphasis is given to the mathematical basis for the different methods. The science that ionospheric imaging addresses is discussed, and the scientific contributions that ionospheric imaging has made are described. Finally, future directions for this research area are outlined.

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History, current state, and future directions of ionospheric imaging

Observing the Global Positioning System with a satellite in low earth orbit in an occulting geometry provides a powerful means of imaging the ionosphere. Tomographic imaging of the ionosphere from space and ground is examined using singular value decomposition analysis. The resolution and covariance matrices are examined, and simulations are performed that indicate that space data are significantly more effective than ground data in resolving both horizontal and vertical structures, such as the E layer, can be probed with occultation data.©1994 John Wiley & Sons Inc

Imaging the ionosphere with the global positioning system

Ionospheric tomography: its limitations and reconstruction methods

In this paper, a hybrid reconstruction algorithm (HRA) is presented to solve the ill-posed inverse problem associated with 3-D ionospheric stochastic tomography. In this new method, the ionospheric electron density (IED) can be inverted by using two steps. First, a truncated singular value decomposition (TSVD) method, whose value is independent on any initial estimation, is used to resolve the ill-posed problem of the tomography system. Second, taking into account the "approximation" of its solution, an iterative improvement process of the solution is then implemented by utilizing the conventional algebraic reconstruction algorithm (ART). The HRA, therefore, offers a more reasonable approach to choose an initial approximate for the ART and to improve the quality of the final reconstructed image. A simulated experiment demonstrates that the HRA method is superior to the TSVD or the ART alone for the tomographic inversion of IED. Finally, the HRA is used to perform GPS-based tomographic reconstruction of the IED at mid- and low-latitude regions.

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A Hybrid Reconstruction Algorithm for 3-D Ionospheric Tomography

An improved algebraic reconstruction technique (IART) is presented for the tomographic reconstruction of ionospheric electron density (IED). This method applies the total electron content (TEC) measurements to invert the spatial distribution of the IED from a set of apriori IED distributions. In this new method, a data-driven adjustment of the relaxation parameter is performed to improve the computation efficiency and image quality of the classical algebraic reconstruction technique (ART). In addition, the new algorithm is also combined with ionospheric space discretization technique to simplify the inversion of IED, and it applies CHAMP occultation data to improve the vertical resolution. A numerical simulation experiment is carried out to validate the reliability of the new method. It is then applied to the inversion of IED from real GPS data. Inverted results show that the IART algorithm has better accuracy and efficiency than the conventional ART algorithm. The reliability of the IART algorithm is also validated by ionosonde data recorded at Wuhan station.

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Three-dimensional ionospheric tomography by an improved algebraic reconstruction technique

Traditionally, knowledge of the ionospheric electron density is obtained using Faraday rotation or differential Doppler techniques which measure total electron content in columns of the ionosphere. Conventional data processing can only image the electron density in the direction perpendicular to these columns, thereby forming one-dimensional images. Because this data is proportional to line integrals through the region of interest, tomographic techniques may be used to reconstruct two-dimensional electron density images. In this paper, the resolution limit of the image reconstruction process is analyzed in terms of limited-angle tomography.

Helen Na

Papers

Resolution analysis of tomographic reconstruction of electron density profiles in the Ionosphere