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| Titel |
Using sparse regularization for multiresolution tomography of the ionosphere |
| VerfasserIn |
T. Panicciari, N. D. Smith, C. N. Mitchell, F. Da Dalt, P. S. J. Spencer |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
2198-5634
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics Discussions ; 2, no. 2 ; Nr. 2, no. 2 (2015-03-25), S.537-572 |
| Datensatznummer |
250115156
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| Publikation (Nr.) |
 copernicus.org/npgd-2-537-2015.pdf |
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| Zusammenfassung |
| Computerized ionospheric tomography (CIT) is a technique that allows
reconstructing the state of the ionosphere in terms of electron content from
a set of Slant Total Electron Content (STEC)
measurements. It is usually denoted as an inverse
problem. In this experiment, the
measurements are considered coming from the phase of the GPS signal
and, therefore, affected by
bias. For this reason the STEC cannot be considered in
absolute terms but rather in relative terms.
Measurements are collected from receivers not evenly distributed in space
and together with limitations such as angle and density of the
observations, they are the cause of instability in the
operation of inversion. Furthermore,
the ionosphere is a dynamic medium whose processes are continuously changing
in time and space. This can affect CIT by limiting the
accuracy in resolving structures and the processes that describe the
ionosphere. Some inversion techniques are based on
l2 minimization algorithms
(i.e. Tikhonov regularization) and
a standard approach is implemented here using spherical harmonics as
a reference to compare the new method. A new approach is
proposed for CIT that aims to permit sparsity in the reconstruction
coefficients by using wavelet basis functions. It is
based on the l1 minimization technique and wavelet basis functions due
to their properties of compact representation. The
l1 minimization is selected because it can optimise the result with an
uneven distribution of observations by exploiting the localization property
of wavelets. Also illustrated is how the interfrequency
biases on the STEC are calibrated within the operation of
inversion, and this is used as a way for evaluating the
accuracy of the method. The technique is demonstrated
using a simulation, showing the advantage of l1
minimization to estimate the coefficients over the l2
minimization. This is in particular true for an uneven
observation geometry and especially for multi resolution
CIT. |
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