Local solutions to inverse problems in geodesy. The impact of the noise covariance structure upon the accuracy of estimation

DOI10.1007/s00190-006-0049-5zbMath1138.86006OpenAlexW1573849510MaRDI QIDQ871597

Frank Bauer, Peter Mathé, Sergei V. Pereverzyev

Publication date: 20 March 2007

Published in: Journal of Geodesy (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00190-006-0049-5

zbMATH Keywords

ill-posed inverse problemssatellite gravity gradiometryGaussian random noiseregularization by local data

Mathematics Subject Classification ID

Inverse problems in geophysics (86A22) Data smoothing in stochastic control theory (93E14) Geostatistics (86A32) Linear operators and ill-posed problems, regularization (47A52) Numerical solution to inverse problems in abstract spaces (65J22) Existence of optimal solutions to problems involving randomness (49J55)

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The quasi-optimality criterion in the linear functional strategy ⋮ A linear functional strategy for regularized ranking ⋮ Multi-task learning via linear functional strategy ⋮ Robust GCV choice of the regularization parameter for correlated data ⋮ Estimation of linear functionals from indirect noisy data without knowledge of the noise level ⋮ Adaptive spectral regularizations of high dimensional linear models ⋮ Regularized collocation for spherical harmonics gravitational field modeling ⋮ Use of extrapolation in regularization methods ⋮ Sparse recovery by the standard Tikhonov method ⋮ About the Balancing Principle for Choice of the Regularization Parameter ⋮ Joint Inversion of Multiple Observations ⋮ Parameter Choice Strategies for Least-squares Approximation of Noisy Smooth Functions on the Sphere

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