Refine
Document Type
- Preprint (7) (remove)
Has Fulltext
- yes (7)
Keywords
- Inverses Problem (7) (remove)
Faculty / Organisational entity
This paper provides a brief overview of two linear inverse problems concerned with the determination of the Earth’s interior: inverse gravimetry and normal mode tomography. Moreover, a vector spline method is proposed for a combined solution of both problems. This method uses localised basis functions, which are based on reproducing kernels, and is related to approaches which have been successfully applied to the inverse gravimetric problem and the seismic traveltime tomography separately.
In this paper we construct spline functions based on a reproducing kernel Hilbert space to interpolate/approximate the velocity field of earthquake waves inside the Earth based on traveltime data for an inhomogeneous grid of sources (hypocenters) and receivers (seismic stations). Theoretical aspects including error estimates and convergence results as well as numerical results are demonstrated.
We show the numerical applicability of a multiresolution method based on harmonic splines on the 3-dimensional ball which allows the regularized recovery of the harmonic part of the Earth's mass density distribution out of different types of gravity data, e.g. different radial derivatives of the potential, at various positions which need not be located on a common sphere. This approximated harmonic density can be combined with its orthogonal anharmonic complement, e.g. determined out of the splitting function of free oscillations, to an approximation of the whole mass density function. The applicability of the presented tool is demonstrated by several test calculations based on simulated gravity values derived from EGM96. The method yields a multiresolution in the sense that the localization of the constructed spline basis functions can be increased which yields in combination with more data a higher resolution of the resulting spline. Moreover, we show that a locally improved data situation allows a highly resolved recovery in this particular area in combination with a coarse approximation elsewhere which is an essential advantage of this method, e.g. compared to polynomial approximation.
We introduce splines for the approximation of harmonic functions on a 3-dimensional ball. Those splines are combined with a multiresolution concept. More precisely, at each step of improving the approximation we add more data and, at the same time, reduce the hat-width of the used spline basis functions. Finally, a convergence theorem is proved. One possible application, that is discussed in detail, is the reconstruction of the Earth´s density distribution from gravitational data obtained at a satellite orbit. This is an exponentially ill-posed problem where only the harmonic part of the density can be recovered since its orthogonal complement has the potential 0. Whereas classical approaches use a truncated singular value decomposition (TSVD) with the well-known disadvantages like the non-localizing character of the used spherical harmonics and the bandlimitedness of the solution, modern regularization techniques use wavelets allowing a localized reconstruction via convolutions with kernels that are only essentially large in the region of interest. The essential remaining drawback of a TSVD and the wavelet approaches is that the integrals (i.e. the inner product in case of a TSVD and the convolution in case of wavelets) are calculated on a spherical orbit, which is not given in reality. Thus, simplifying modelling assumptions, that certainly include a modelling error, have to be made. The splines introduced here have the important advantage, that the given data need not be located on a sphere but may be (almost) arbitrarily distributed in the outer space of the Earth. This includes, in particular, the possibility to mix data from different satellite missions (different orbits, different derivatives of the gravitational potential) in the calculation of the Earth´s density distribution. Moreover, the approximating splines can be calculated at varying resolution scales, where the differences for increasing the resolution can be computed with the introduced spline-wavelet technique.
The mathematical formulation of many physical problems results in the task of inverting a compact operator. The only known sensible solution technique is regularization which poses a severe problem in itself. Classically one dealt with deterministic noise models and required both the knowledge of smoothness of the solution function and the overall error behavior. We will show that we can guarantee an asymptotically optimal regularization for a physically motivated noise model under no assumptions for the smoothness and rather weak assumptions on the noise behavior which can mostly obtained out of two input data sets. An application to the determination of the gravitational field out of satellite data will be shown.
SST (satellite-to-satellite tracking) and SGG (satellite gravity gradiometry) provide data that allows the determination of the first and second order radial derivative of the earth's gravitational potential on the satellite orbit, respectively. The modeling of the gravitational potential from such data is an exponentially ill-posed problem that demands regularization. In this paper, we present the numerical studies of an approach, investigated in [24] and [25], that reconstructs the potential with spline smoothing. In this case, spline smoothing is not just an approximation procedure but it solves the underlying compact operator equation of the SST-problem and the SGG-problem. The numerical studies in this paper are performed for a simplified geometrical scenario with simulated data, but the approach is designed to handle first or second order radial derivative data on a real satellite orbit.
Die Bestimmung des Erdgravitationspotentials aus den Meßdaten des Forschungssatelliten CHAMP lässt sich als Operatorgleichung formulieren (SST-Problem). Dieser Ansatz geht davon aus, dass ein geometrischer Orbit des Satelliten CHAMP vorliegt. Mittels numerischer Differentiation unter Einsatz eines geeigneten Denoising Verfahrens kann dann aus dem geometrischen Orbit der Gradient des Potentials längs der Bahn bestimmt werden. Damit sind insbesondere die Radialableitung (und der Flächengradient) auf einem Punktgitter auf der Bahn bekannt. In einem erdfesten System stellt sich dies als eine nahezu vollständige Überdeckung der Erde (bis auf Polar Gaps) mit einem ziemlich dichten Datengitter auf Flughöhe des Satelliten dar. Die Lösung der SST-Operatorgleichung (Bestimmung des Potentials auf der Erdoberfläche aus Kenntnis der Radialableitung auf einem Datengitter auf Flughöhe) ist ein schlecht gestelltes inverses Problem, das mit einer geeigneten Regularisierungstechnik gelöst werden muß. Im vorliegenden Fall wurde eine solche Regularisierung mit Hilfe von nicht-bandlimitierten Regularisierungsskalierungsfunktionen und Regularisierungswavelets umgesetzt. Diese sind stark ortslokalisierend und führen daher auf ein Potentialmodell, welches eine Linearkombination stark ortslokalisierender Funktionen ist. Ein solches Modell kann als Lokalmodell auch aus nur lokalen Daten berechnet werden und bietet daher gegenüber Kugelfunktionsmodellen wie EGM96 erhebliche Vorteile für die moderne Geopotentialbestimmung. Die Diskretisierung und numerische Umsetzung der Berechnung eines solchen Modells erfolgt mit Splines, die hier ebenfalls Linearkombinationen stark ortslokalisierender Funktionen sind. Die großen linearen Gleichungssysteme, die zur Berechnung der glättenden oder interpolierenden Splines gelöst werden müssen, können auf schnelle und effiziente Weise mit dem Schwarzschen alternierenden Algorithmus in Verbindung mit schnellen Summationsverfahren (Fast Multipole Methods) gelöst werden. Eine Kombination des Schwarzschen alternierenden Algorithmus mit solchen schnellen Summationsverfahren ermöglicht eine weitere erhebliche Beschleunigung beim Lösen dieser Gleichungssysteme. Zur Bestimmung von Glättungsparametern (Spline-Smoothing) und Regularisierungsparametern kann die L-Curve Method zum Einsatz kommen.