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| Titel |
Solving the non-linear model of the electron density of the ionosphere |
| VerfasserIn |
W. Liang, M. Schmidt, D. Dettmering, U. Hugentobler, M. Limberger |
| Konferenz |
EGU General Assembly 2012
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250061376
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| Zusammenfassung |
| Precise and high precision ionosphere models are important for modern satellite navigation
and positioning systems. In most cases, the ionosphere models are based on pure
mathematical approaches, e.g. by applying spherical harmonic expansions for the vertical
total electron content. In order to achieve a deeper understanding of the complex
phenomena within the ionosphere, physical conditions have to be considered and
introduced.
The physics-motivated Chapman function is very efficient for describing the vertical
structure of the electron density. Introducing the Chapman function and a plasmasphere layer,
the vertical distribution of the electron density can be described by five parameters altogether,
namely (1) the F2 peak electron density (NmF2), (2) the peak height (hmF2), (3) the
topside scale height (HF2), (4) the plasmasphere basic density (NP) and (5) the
scale height (HP). In our approach, each of these parameters is decomposed into an
initial part, derived from a given ionosphere model or other initial assumptions, and
an unknown correction term. Exploiting the localizing property of B-spline base
functions, the latter is modeled as a series expansion in terms of tensor products of three
one-dimensional endpoint-interpolating B-splines depending on latitude, longitude and time,
respectively. Considering the necessary linearization of the exponential terms of the
Chapman and the plasmaspheric layer, the unknown model coefficients are solved
by an appropriate parameter estimation procedure using an iterative algorithm. In
this contribution we focus on the numerical solution of the linearized model. This
includes a closer view on the iterative method, the regularization scheme and the
convergence analysis. Due to complexity of the problem, the topside scale height HF2 is
expanded in a first step to test the adjustment approach. Data gaps are artificially
created to investigate inhomogeneous data availability. In this case proper prior
information and regularization are needed to ensure the convergence of the system. |
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