Ionospheric imaging using computerized tomography

Austen, Jeffrey R.; Franke, Steven; Liu, C. H.

doi:10.1029/rs023i003p00299

Cited by 336 publications

(220 citation statements)

References 13 publications

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“…[4] During the years, the researchers have developed and used other means to gather information on the upper ionosphere and plasmasphere, such as: coherent scatter radar observations of underdense electron density irregularities [Booker, 1956;Greenwald, 1996], incoherent scatter radar probing [Bowles, 1958;Gordon, 1958;Farley, 1996], observations using topside sounders onboard satellites [Franklin and Maclean, 1969;Reinisch et al, 2001], in situ rocket and satellite observations [Pfaff, 1996], tomography [Austen et al, 1988;Leitinger, 1996b], and occultation measurements [Phinney and Anderson, 1973; Leitinger, 1996b]. There is no universal method; each type has advantages as well as shortcomings.…”

Section: Introductionmentioning

confidence: 99%

A new method for reconstruction of the vertical electron density distribution in the upper ionosphere and plasmasphere

et al. 2003

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[1] Ground-based ionosphere sounding measurements alone are incapable of reliably modeling the topside electron density distribution above the F layer peak density height. Such information can be derived from Global Positioning System (GPS)-based total electron content (TEC) measurements. A novel technique is presented for retrieving the electron density height profile from three types of measurements: ionosonde ( f o F 2 , f o E, M 3000 F 2 , h m f 2 ), TEC (GPS-based), and O + -H + ion transition level. The method employs new formulae based on Chapman, sech-squared, and exponential ionosphere profilers to construct a system of equations, the solution of which system provides the unknown ion scale heights, sufficient to construct a unique electron density profile at the site of measurements. All formulae are based on the assumption of diffusive equilibrium with constant scale height for each ion species. The presented technique is most suitable for middle-and high-geomagnetic latitudes and possible applications include: development, evaluation, and improvement of theoretical and empirical ionospheric models, development of similar reconstruction methods utilizing low-earth-orbiting satellite measurements of TEC, operational reconstruction of the electron density on a real-time basis, etc.

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Section: Introductionmentioning

confidence: 99%

A new method for reconstruction of the vertical electron density distribution in the upper ionosphere and plasmasphere

et al. 2003

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“…As the ionospheric total electron content (TEC) is an integrated value of the ionospheric electron density along a ray path of the radio signal from a satellite to a ground receiver, the problem to reconstruct the electron density profile from a set of the TEC values is a kind of computerized tomography (CT). Since Austen et al, [4] applied the algebraic reconstruction technique (ART) to the twodimensional analysis of model TEC data generated by a computer simulation various methods for CIT were proposed and applied to analyses of model data and real observation data. Though the two-dimensional ionospheric tomography has been studied extensively from both the theoretical and observational aspects [5][6][7], in these studies only the ionospheric structure within a cross-section defined by the satellite orbit and the ground receiver array can be obtained, which limits strongly the observation time and place.…”

Section: Computerized Ionospheric Tomographymentioning

confidence: 99%

Ionospheric Tomography by Neural Network Collocation Method

Takeda

2007

Plasma and Fusion Research

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We describe a neural network collocation method (NNCM) for tomographic image reconstruction with small amount of projection data, which has been successfully applied to the three-dimensional ionospheric tomography based on the dataset of signal delays from the GPS satellites. In NNCM the neural network is trained by minimizing an object function composed of squared residuals of the governing equations evaluated at the collocation points and some constraining conditions imposed usually by observation data. This method is applied not only to the computerized tomography but also to the analyses of various inverse problems such as the data assimilation, the parameter estimation, the time series prediction, and so on.

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“…The use of tomographic methods for ionospheric research was first suggested by (Austen et al, 1988). (Bust and Mitchell, 2008) provide a good overview on the development of the topic.…”

Section: Introductionmentioning

confidence: 99%

Bayesian statistical ionospheric tomography improved by incorporating ionosonde measurements

et al. 2016

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Abstract. We validate two-dimensional ionospheric tomography reconstructions against EISCAT incoherent scatter radar measurements. Our tomography method is based on Bayesian statistical inversion with prior distribution given by its mean and covariance. We employ ionosonde measurements for the choice of the prior mean and covariance parameters and use the Gaussian Markov random fields as a sparse matrix approximation for the numerical computations. This results in a computationally efficient tomographic inversion algorithm with clear probabilistic interpretation.We demonstrate how this method works with simultaneous beacon satellite and ionosonde measurements obtained in northern Scandinavia. The performance is compared with results obtained with a zero-mean prior and with the prior mean taken from the International Reference Ionosphere 2007 model. In validating the results, we use EISCAT ultrahigh-frequency incoherent scatter radar measurements as the ground truth for the ionization profile shape.We find that in comparison to the alternative prior information sources, ionosonde measurements improve the reconstruction by adding accurate information about the absolute value and the altitude distribution of electron density. With an ionosonde at continuous disposal, the presented method enhances stand-alone near-real-time ionospheric tomography for the given conditions significantly.

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Ionospheric imaging using computerized tomography

Cited by 336 publications

References 13 publications

A new method for reconstruction of the vertical electron density distribution in the upper ionosphere and plasmasphere

A new method for reconstruction of the vertical electron density distribution in the upper ionosphere and plasmasphere

Ionospheric Tomography by Neural Network Collocation Method

Bayesian statistical ionospheric tomography improved by incorporating ionosonde measurements

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