Publications

2018

  • B. Kargoll, M. Omidalizarandi, H. Alkhatib, and W. Schuh, “Further Results on a Mofified EM Algorithm for Paramter Estimation in Linear Models with Time-Dependent Autoregressive and t-Distributed Errors,” in Advances in Time Series Analysis and Forecasting –- Selected Contribution from ITISE 2017, I. Rojas, H. Pomares, and O. Vaenzuela, Eds., , 2018.
    [BibTeX]
    @incollection{kargoll-etal_2018,
    title = {Further {{Results}} on a {{Mofified EM Algorithm}} for {{Paramter Estimation}} in {{Linear Models}} with {{Time}}-{{Dependent Autoregressive}} and t-{{Distributed Errors}}},
    booktitle = {Advances in {{Time Series Analysis}} and {{Forecasting}} --- {{Selected Contribution}} from {{ITISE}} 2017},
    author = {Kargoll, Boris and Omidalizarandi, Mohammad and Alkhatib, Hamza and Schuh, Wolf-Dieter},
    editor = {Rojas, Ignacio and Pomares, H{\'e}ctor and Vaenzuela, Olga},
    year = {2018}
    }

  • K. R. Koch, “Bayesian Statistics and Monte Carlo Methods,” Journal of Geodetic Science, vol. 8, iss. 1, p. 18–29, 2018. doi:10.1515/jogs-2018-0003
    [BibTeX] [Abstract] [Download PDF]

    The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability. If the statements refer to the numerical values of variables, the so-called random variables, univariate and multivariate distributions follow. They lead to the point estimation by which unknown quantities, i.e. unknown parameters, are computed from measurements. The unknown parameters are random variables, they are fixed quantities in traditional statistics which is not founded on Bayes’ theorem. Bayesian statistics therefore recommends itself for Monte Carlo methods, which generate random variates from given distributions. Monte Carlo methods, of course, can also be applied in traditional statistics. The unknown parameters, are introduced as functions of the measurements, and the Monte Carlo methods give the covariance matrix and the expectation of these functions. A confidence region is derived where the unknown parameters are situated with a given probability. Following a method of traditional statistics, hypotheses are tested by determining whether a value for an unknown parameter lies inside or outside the confidence region. The error propagation of a random vector by the Monte Carlo methods is presented as an application. If the random vector results from a nonlinearly transformed vector, its covariance matrix and its expectation follow from the Monte Carlo estimate. This saves a considerable amount of derivatives to be computed, and errors of the linearization are avoided. The Monte Carlo method is therefore efficient. If the functions of the measurements are given by a sum of two or more random vectors with different multivariate distributions, the resulting distribution is generally not known. TheMonte Carlo methods are then needed to obtain the covariance matrix and the expectation of the sum.

    @article{koch_2018,
    title = {Bayesian Statistics and {{Monte Carlo}} Methods},
    volume = {8},
    doi = {10.1515/jogs-2018-0003},
    abstract = {The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability. If the statements refer to the numerical values of variables, the so-called random variables, univariate and multivariate distributions follow. They lead to the point estimation by which unknown quantities, i.e. unknown parameters, are computed from measurements. The unknown parameters are random variables, they are fixed quantities in traditional statistics which is not founded on Bayes' theorem. Bayesian statistics therefore recommends itself for Monte Carlo methods, which generate random variates from given distributions. Monte Carlo methods, of course, can also be applied in traditional statistics. The unknown parameters, are introduced as functions of the measurements, and the Monte Carlo methods give the covariance matrix and the expectation of these functions. A confidence region is derived where the unknown parameters are situated with a given probability. Following a method of traditional statistics, hypotheses are tested by determining whether a value for an unknown parameter lies inside or outside the confidence region. The error propagation of a random vector by the Monte Carlo methods is presented as an application. If the random vector results from a nonlinearly transformed vector, its covariance matrix and its expectation follow from the Monte Carlo estimate. This saves a considerable amount of derivatives to be computed, and errors of the linearization are avoided. The Monte Carlo method is therefore efficient. If the functions of the measurements are given by a sum of two or more random vectors with different multivariate distributions, the resulting distribution is generally not known. TheMonte Carlo methods are then needed to obtain the covariance matrix and the expectation of the sum.},
    number = {1},
    urldate = {2018-03-05},
    url = {https://www.degruyter.com/view/j/jogs.2018.8.issue-1/jogs-2018-0003/jogs-2018-0003.xml},
    journal = {Journal of Geodetic Science},
    author = {Koch, K. R.},
    year = {2018},
    keywords = {Confidence Region,Error Propagation;Hypothesis Test,Probability,Random Variable,Univariate and Multivariate Distributions},
    pages = {18--29},
    file = {/home/jmb/pc/internetSettings/zotero/storage/G4DXQX5M/Koch - 2018 - Bayesian statistics and Monte Carlo methods.pdf}
    }

  • B. Kargoll, M. Omidalizarandi, I. Loth, J. Paffenholz, and H. Alkhatib, “An Iteratively Reweighted Least-Squares Approach to Adaptive Robust Adjustment of Parameters in Linear Regression Models with Autoregressive and t-Distributed Deviations,” Journal of Geodesy, vol. 92, iss. 3, pp. 271-297, 2018. doi:10.1007/s00190-017-1062-6
    [BibTeX] [Abstract] [Download PDF]

    In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student’s) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.

    @article{kargoll.etal_2018,
    title = {An Iteratively Reweighted Least-Squares Approach to Adaptive Robust Adjustment of Parameters in Linear Regression Models with Autoregressive and t-Distributed Deviations},
    volume = {92},
    issn = {0949-7714, 1432-1394},
    doi = {10.1007/s00190-017-1062-6},
    abstract = {In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student's) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.},
    language = {en},
    number = {3},
    urldate = {2018-02-27},
    url = {https://link.springer.com/article/10.1007/s00190-017-1062-6},
    journal = {Journal of Geodesy},
    author = {Kargoll, Boris and Omidalizarandi, Mohammad and Loth, Ina and Paffenholz, Jens-Andr{\'e} and Alkhatib, Hamza},
    month = mar,
    year = {2018},
    pages = {271-297},
    file = {/home/jmb/pc/internetSettings/zotero/storage/37BWGSU2/Kargoll et al. - 2018 - An iteratively reweighted least-squares approach t.pdf}
    }

2017

  • J. M. Brockmann, N. Zehentner, W. -D. Schuh, and T. Mayer-Gürr, “Studies on the Potential of Reprocessing Campaign of the GOCE Observations Inline with the Time-Wise Method,” {Institute of Geodesy and Geoinformation, Department of Theoretical Geodesy, University Bonn} 2017.
    [BibTeX]
    @techreport{brockmann-etal_17,
    title = {Studies on the Potential of Reprocessing Campaign of the {{GOCE}} Observations Inline with the Time-Wise Method},
    institution = {{Institute of Geodesy and Geoinformation, Department of Theoretical Geodesy, University Bonn}},
    author = {Brockmann, J.M. and Zehentner, N. and Schuh, W.-D. and Mayer-G{\"u}rr, T.},
    year = {2017},
    owner = {swd}
    }

  • K. R. Koch, “Expectation Maximization (EM) Algorithm and Its Minimal Detectable Outliers,” Studia Geophysica et Geodaetica, vol. 61, pp. 1-18, 2017. doi:10.1007/s11200-016-0617-y
    [BibTeX]
    @article{koch_2017,
    title = {Expectation {{Maximization}} ({{EM}}) Algorithm and Its Minimal Detectable Outliers},
    volume = {61},
    doi = {10.1007/s11200-016-0617-y},
    journal = {Studia Geophysica et Geodaetica},
    author = {Koch, K.R.},
    year = {2017},
    pages = {1-18},
    owner = {swd}
    }

  • W. -D. Schuh and J. Korte, “Über Die Genauigkeit von Schätzern Für Den Skalenparameter Der Verteilungsfunktion,” Allgemeine Vermessungs-Nachrichten (AVN), vol. 6, pp. 186-196, 2017.
    [BibTeX] [Download PDF]
    @article{schuh-korte_2017,
    title = {{\"U}ber Die {{Genauigkeit}} von {{Sch{\"a}tzern}} F{\"u}r Den {{Skalenparameter}} Der {{Verteilungsfunktion}}},
    volume = {6},
    url = {ftp://skylab.itg.uni-bonn.de/schuh/Separata/schuh-korte_17.pdf},
    journal = {Allgemeine Vermessungs-Nachrichten (AVN)},
    author = {Schuh, W.-D. and Korte, J.},
    year = {2017},
    pages = {186-196},
    owner = {swd},
    note = {schuh-korte\textsubscript{1}7}
    }

  • W. -D. Schuh, “Über Die Ausgleichung Bei Überschüssigen Messungen Und Zufälligen Beobachtungen –- Auf Den Spuren von Friedrich Robert Helmert,” in Friedrich Robert Helmert –- 13. Dortmunder Symposium Zur Vermessungsgeschichte, 13.2.2017, Dortmund, 2017, pp. 30-45.
    [BibTeX] [Download PDF]
    @inproceedings{schuh_1,
    address = {Dortmund},
    title = {{\"U}ber Die {{Ausgleichung}} Bei {\"U}bersch{\"u}ssigen {{Messungen}} Und Zuf{\"a}lligen {{Beobachtungen}} --- Auf Den {{Spuren}} von {{Friedrich Robert Helmert}}},
    volume = {42},
    url = {ftp://skylab.itg.uni-bonn.de/schuh/Separata/schuh_17.pdf},
    booktitle = {Friedrich {{Robert Helmert}} --- 13. {{Dortmunder Symposium}} Zur {{Vermessungsgeschichte}}, 13.2.2017},
    publisher = {{Schriftenreihe des F{\"o}rderkreis Vermessungstechnisches Museum e.V.}},
    author = {Schuh, W.-D.},
    editor = {Wei{\ss}, Erich},
    year = {2017},
    pages = {30-45},
    owner = {swd},
    note = {schuh\textsubscript{v}17}
    }

  • T. Fecher, R. Pail, T. Gruber, and G. Consortium, “GOCO05c: A New Combined Gravity Field Model Based on Full Normal Equations and Regionally Varying Weighting,” Surveys in Geophysics, pp. 1-20, 2017. doi:10.1007/s10712-016-9406-y
    [BibTeX] [Abstract] [Download PDF]

    GOCO05c is a gravity field model computed as a combined solution of a satellite-only model and a global data set of gravity anomalies. It is resolved up to degree and order 720. It is the first model applying regionally varying weighting. Since this causes strong correlations among all gravity field parameters, the resulting full normal equation system with a size of 2 TB had to be solved rigorously by applying high-performance computing. GOCO05c is the first combined gravity field model independent of EGM2008 that contains GOCE data of the whole mission period. The performance of GOCO05c is externally validated by GNSS–{}levelling comparisons, orbit tests, and computation of the mean dynamic topography, achieving at least the quality of existing high-resolution models. Results show that the additional GOCE information is highly beneficial in insufficiently observed areas, and that due to the weighting scheme of individual data the spectral and spatial consistency of the model is significantly improved. Due to usage of fill-in data in specific regions, the model cannot be used for physical interpretations in these regions.

    @article{fecher.etal_2017,
    title = {{{GOCO05c}}: {{A New Combined Gravity Field Model Based}} on {{Full Normal Equations}} and {{Regionally Varying Weighting}}},
    issn = {0169-3298, 1573-0956},
    shorttitle = {{{GOCO05c}}},
    doi = {10.1007/s10712-016-9406-y},
    abstract = {GOCO05c is a gravity field model computed as a combined solution of a satellite-only model and a global data set of gravity anomalies. It is resolved up to degree and order 720. It is the first model applying regionally varying weighting. Since this causes strong correlations among all gravity field parameters, the resulting full normal equation system with a size of 2 TB had to be solved rigorously by applying high-performance computing. GOCO05c is the first combined gravity field model independent of EGM2008 that contains GOCE data of the whole mission period. The performance of GOCO05c is externally validated by GNSS\textendash{}levelling comparisons, orbit tests, and computation of the mean dynamic topography, achieving at least the quality of existing high-resolution models. Results show that the additional GOCE information is highly beneficial in insufficiently observed areas, and that due to the weighting scheme of individual data the spectral and spatial consistency of the model is significantly improved. Due to usage of fill-in data in specific regions, the model cannot be used for physical interpretations in these regions.},
    language = {en},
    urldate = {2017-01-18},
    url = {http://link.springer.com/article/10.1007/s10712-016-9406-y},
    journal = {Surveys in Geophysics},
    author = {Fecher, T. and Pail, R. and Gruber, T. and GOCO Consortium},
    month = jan,
    year = {2017},
    pages = {1-20},
    file = {/home/jmb/pc/internetSettings/zotero/storage/48NNN3EN/Fecher et al. - 2017 - GOCO05c A New Combined Gravity Field Model Based .pdf}
    }

  • B. Kargoll, M. Omidalizarandi, H. Alkathib, and W. -D. Schuh, “A Modified EM Algorithm for Parameter Estimation in Linear Models with Time-Dependent Autoregressive and t-Distributed Errors,” in Proceedings of the ‘International Work-Conference on TIme SEries Analysis’, Granada, Spain: , 2017, vol. 2, pp. 1132-1145.
    [BibTeX]
    @incollection{kargoll-etal_2017,
    address = {Granada, Spain},
    title = {A {{Modified EM Algorithm}} for {{Parameter Estimation}} in {{Linear Models}} with {{Time}}-{{Dependent Autoregressive}} and t-{{Distributed Errors}}},
    volume = {2},
    booktitle = {Proceedings of the '{{International Work}}-{{Conference}} on {{TIme SEries Analysis}}'},
    author = {Kargoll, B. and Omidalizarandi, M. and Alkathib, H. and Schuh, W.-D.},
    year = {2017},
    pages = {1132-1145},
    owner = {swd},
    note = {(accepted)}
    }

  • B. Kargoll, M. Omidalizarandi, I. Loth, J. Paffenholz, and H. Alkhatib, “An Iteratively Reweighted Least-Squares Approach to Adaptive Robust Adjustment of Parameters in Linear Regression Models with Autoregressive and t-Distributed Deviations,” Journal of Geodesy, 2017. doi:10.1007/s00190-017-1062-6
    [BibTeX] [Abstract] [Download PDF]

    In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student’s) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.

    @article{kargoll-etal_17,
    title = {An Iteratively Reweighted Least-Squares Approach to Adaptive Robust Adjustment of Parameters in Linear Regression Models with Autoregressive and t-Distributed Deviations},
    issn = {1432-1394},
    doi = {10.1007/s00190-017-1062-6},
    abstract = {In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student's) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.},
    url = {https://doi.org/10.1007/s00190-017-1062-6},
    journal = {Journal of Geodesy},
    author = {Kargoll, Boris and Omidalizarandi, Mohammad and Loth, Ina and Paffenholz, Jens-Andr{\'e} and Alkhatib, Hamza},
    month = sep,
    year = {2017},
    day = {09}
    }

  • C. Neyers, “Integration von Radialen SAR Doppler Ozeanoberflächengeschwindigkeitsmessungen in Die Berechnung Der Dynamischen Ozeantopographie,” Masterthesis PhD Thesis, Bonn, Germany, 2017.
    [BibTeX]
    @phdthesis{neyers_2017,
    address = {Bonn, Germany},
    type = {Masterthesis},
    title = {Integration von Radialen {{SAR Doppler Ozeanoberfl{\"a}chengeschwindigkeitsmessungen}} in Die {{Berechnung}} Der {{Dynamischen Ozeantopographie}}},
    school = {Universit{\"a}t Bonn},
    author = {Neyers, C.},
    year = {2017},
    file = {/home/jmb/pc/internetSettings/zotero/storage/M7A2STXQ/thesis_neyers.pdf},
    owner = {jmb}
    }

  • K. Koch, “Monte Carlo Methods,” GEM – International Journal on Geomathematics, pp. 1-27, 2017. doi:10.1007/s13137-017-0101-z
    [BibTeX] [Abstract] [Download PDF]

    Monte Carlo methods deal with generating random variates from probability density functions in order to estimate unknown parameters or general functions of unknown parameters and to compute their expected values, variances and covariances. One generally works with the multivariate normal distribution due to the central limit theorem. However, if random variables with the normal distribution and random variables with a different distribution are combined, the normal distribution is not valid anymore. The Monte Carlo method is then needed to get the expected values, variances and covariances for the random variables with distributions different from the normal distribution. The error propagation by Monte Carlo methods is discussed and methods for generating random variates from the multivariate normal distribution and from the multivariate uniform distribution. The Monte Carlo integration is presented leading to the sampling–{}importance-resampling algorithm. Markov chain Monte Carlo methods provide by the Metropolis algorithm and the Gibbs sampler additional ways of generating random variates. A special topic is the Gibbs sampler for computing and propagating large covariance matrices. This task arises, for instance, when the geopotential is determined from satellite observations. The example of the minimal detectable outlier shows, how the Monte Carlo method is used to determine the power of a hypothesis test.

    @article{koch_2017a,
    title = {Monte {{Carlo}} Methods},
    issn = {1869-2672, 1869-2680},
    doi = {10.1007/s13137-017-0101-z},
    abstract = {Monte Carlo methods deal with generating random variates from probability density functions in order to estimate unknown parameters or general functions of unknown parameters and to compute their expected values, variances and covariances. One generally works with the multivariate normal distribution due to the central limit theorem. However, if random variables with the normal distribution and random variables with a different distribution are combined, the normal distribution is not valid anymore. The Monte Carlo method is then needed to get the expected values, variances and covariances for the random variables with distributions different from the normal distribution. The error propagation by Monte Carlo methods is discussed and methods for generating random variates from the multivariate normal distribution and from the multivariate uniform distribution. The Monte Carlo integration is presented leading to the sampling\textendash{}importance-resampling algorithm. Markov chain Monte Carlo methods provide by the Metropolis algorithm and the Gibbs sampler additional ways of generating random variates. A special topic is the Gibbs sampler for computing and propagating large covariance matrices. This task arises, for instance, when the geopotential is determined from satellite observations. The example of the minimal detectable outlier shows, how the Monte Carlo method is used to determine the power of a hypothesis test.},
    language = {en},
    urldate = {2017-12-08},
    url = {https://link.springer.com/article/10.1007/s13137-017-0101-z},
    journal = {GEM - International Journal on Geomathematics},
    author = {Koch, Karl-Rudolf},
    month = dec,
    year = {2017},
    pages = {1-27},
    file = {/home/jmb/pc/internetSettings/zotero/storage/GL2888TX/GEM-Int-J-Geomath_2017.pdf}
    }

2016

  • J. M. Brockmann and W. Schuh, “Computational Aspects of High-Resolution Global Gravity Dield Determination – Numbering Schemes and Reodering,” in NIC Symposium, Proceedings, G. Münster, D. Wolf, and M. Kremer, Eds., {Schriftenreihe des Forschungszentrums Jülich}, 2016, pp. 309-317.
    [BibTeX]
    @incollection{brockmann-schuh_16,
    series = {IAS Series},
    title = {Computational Aspects of High-Resolution Global Gravity Dield Determination - Numbering Schemes and Reodering},
    booktitle = {{{NIC Symposium}}, {{Proceedings}}},
    publisher = {{Schriftenreihe des Forschungszentrums J{\"u}lich}},
    author = {Brockmann, Jan Martin and Schuh, Wolf-Dieter},
    editor = {M{\"u}nster, G. and Wolf, D. and Kremer, M.},
    year = {2016},
    pages = {309-317},
    owner = {swd},
    note = {brockmann-schuh\textsubscript{1}6}
    }

  • S. Halsig, L. Roese-Koerner, T. Artz, A. Nothnagel, and W. -D. Schuh, “Improved Parameter Estimation of Zenith Wet Delay Using an Inequality Constrained Least Squares Method,” in IAG 150 Years, Proceedings of the 2013 IAG Scientific Assembly, Potsdam, IAG Symposia, Lecture Notes in Earth Science ed., C. Rizos and P. Willis, Eds., Berlin – Heidelberg: {Springer}, 2016, vol. 143, pp. 69-74.
    [BibTeX]
    @incollection{halsig-etal_16,
    address = {Berlin - Heidelberg},
    edition = {Lecture Notes in Earth Science},
    title = {Improved {{Parameter Estimation}} of {{Zenith Wet Delay Using}} an {{Inequality Constrained Least Squares Method}}},
    volume = {143},
    booktitle = {{{IAG}} 150 {{Years}}, {{Proceedings}} of the 2013 {{IAG Scientific Assembly}}, {{Potsdam}}, {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {Halsig, S. and Roese-Koerner, L. and Artz, T. and Nothnagel, A. and Schuh, W.-D.},
    editor = {Rizos, Chris and Willis, Pascal},
    year = {2016},
    keywords = {Inequality Constrained Least Squares,Refractivity variations,Tropospheric delay,VLBI},
    pages = {69-74},
    owner = {swd},
    note = {halsig-etal\_15}
    }

  • I. Loth and C. Esch, “Consistent Assimilation of Spaceborne Radar Interferometry (InSAR) Data into Integrated Terrestrial Systems. HPSC TerrSys Final-Project-Report,” {Institute of Geodesy and Geoinformation, Department of Theoretical Geodesy, University Bonn} 2016.
    [BibTeX]
    @techreport{loth-esch_16,
    title = {Consistent Assimilation of Spaceborne Radar Interferometry ({{InSAR}}) Data into Integrated Terrestrial Systems. {{HPSC TerrSys Final}}-{{Project}}-{{Report}}},
    institution = {{Institute of Geodesy and Geoinformation, Department of Theoretical Geodesy, University Bonn}},
    author = {Loth, I. and Esch, Christina},
    year = {2016},
    owner = {swd},
    note = {loth-esch\textsubscript{1}6}
    }

  • W. -D. Schuh, “Signalverarbeitung in Der Physikalischen Geodäsie,” in Handbuch Der Geodäsie, W. Freeden and R. Rummel, Eds., {Springer Spektrum}, 2016, vol. Erdmessung und Satellitengeodäsie, pp. 73-121.
    [BibTeX] [Download PDF]
    @incollection{schuh_16,
    series = {Springer Reference Naturwissenschaften},
    title = {Signalverarbeitung in Der {{Physikalischen Geod{\"a}sie}}},
    volume = {Erdmessung und Satellitengeod{\"a}sie},
    url = {ftp://skylab.itg.uni-bonn.de/schuh/Separata/schuh_16.pdf},
    booktitle = {Handbuch Der {{Geod{\"a}sie}}},
    publisher = {{Springer Spektrum}},
    author = {Schuh, W.-D.},
    editor = {Freeden, W. and Rummel, R.},
    year = {2016},
    pages = {73-121},
    owner = {schuh},
    note = {schuh\textsubscript{1}6}
    }

  • K. Koch and J. M. Brockmann, “Systematic Effects in Laser Scanning and Visualization by Confidence Regions,” Journal of Applied Geodesy, vol. 10, iss. 4, p. 247–257, 2016. doi:10.1515/jag-2016-0012
    [BibTeX] [Abstract] [Download PDF]

    A new method for dealing with systematic effects in laser scanning and visualizing them by confidence regions is derived. The standard deviations of the systematic effects are obtained by repeatedly measuring three-dimensional coordinates by the laser scanner. In addition, autocovariance and cross-covariance functions are computed by the repeated measurements and give the correlations of the systematic effects. The normal distribution for the measurements and the multivariate uniform distribution for the systematic effects are applied to generate random variates for the measurements and random variates for the measurements plus systematic effects. Monte Carlo estimates of the expectations and the covariance matrix of the measurements with systematic effects are computed. The densities for the confidence ellipsoid for the measurements and the confidence region for the measurements with systematic effects are obtained by relative frequencies. They only depend on the size of the rectangular volume elements for which the densities are determined. The problem of sorting the densities is solved by sorting distances together with the densities. This allows a visualization of the confidence ellipsoid for the measurements and the confidence region for the measurements with systematic effects.

    @article{koch.brockmann_2016,
    title = {Systematic {{Effects}} in {{Laser Scanning}} and {{Visualization}} by {{Confidence Regions}}},
    volume = {10},
    issn = {1862-9016},
    doi = {10.1515/jag-2016-0012},
    abstract = {A new method for dealing with systematic effects in laser scanning and visualizing them by confidence regions is derived. The standard deviations of the systematic effects are obtained by repeatedly measuring three-dimensional coordinates by the laser scanner. In addition, autocovariance and cross-covariance functions are computed by the repeated measurements and give the correlations of the systematic effects. The normal distribution for the measurements and the multivariate uniform distribution for the systematic effects are applied to generate random variates for the measurements and random variates for the measurements plus systematic effects. Monte Carlo estimates of the expectations and the covariance matrix of the measurements with systematic effects are computed. The densities for the confidence ellipsoid for the measurements and the confidence region for the measurements with systematic effects are obtained by relative frequencies. They only depend on the size of the rectangular volume elements for which the densities are determined. The problem of sorting the densities is solved by sorting distances together with the densities. This allows a visualization of the confidence ellipsoid for the measurements and the confidence region for the measurements with systematic effects.},
    number = {4},
    urldate = {2017-01-09},
    url = {https://www.degruyter.com/view/j/jag.2016.10.issue-4/jag-2016-0012/jag-2016-0012.xml?format=INT},
    journal = {Journal of Applied Geodesy},
    author = {Koch, Karl-Rudolf and Brockmann, Jan Martin},
    year = {2016},
    pages = {247--257},
    file = {/home/jmb/pc/internetSettings/zotero/storage/NDTAWDU3/[Journal of Applied Geodesy] Systematic Effects in Laser Scanning and Visualization by Confidence Regions.pdf}
    }

  • L. Roese-Koerner and W. Schuh, “Effects of Different Objective Functions in Inequality Constrained and Rank-Deficient Least-Squares Problems,” in VIII. Hotine-Marussi-Symposium, IAG Symposia, 2016, pp. 325-331. doi:10.1007/1345_2015_140
    [BibTeX]
    @inproceedings{roese-koerner-schuh_2016,
    series = {Lecture Notes in Earth Science},
    title = {Effects of {{Different Objective Functions}} in {{Inequality Constrained}} and {{Rank}}-{{Deficient Least}}-{{Squares Problems}}},
    volume = {142},
    doi = {10.1007/1345_2015_140},
    booktitle = {{{VIII}}. {{Hotine}}-{{Marussi}}-{{Symposium}}, {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {Roese-Koerner, Lutz and Schuh, Wolf-Dieter},
    editor = {Sneeuw, Nico and Nov{\'a}k, Pavel and Crespi, Mattia and Sans{\`o}, Fernando},
    year = {2016},
    pages = {325-331},
    owner = {swd},
    note = {roese-koerner-schuh\textsubscript{2}016}
    }

  • O. Didova, B. Gunter, R. Riva, R. Klees, and L. Roese-Koerner, “An Approach for Estimating Time-Variable Rates from Geodetic Time Series,” Journal of Geodesy, vol. 90, iss. 11, pp. 1207-1221, 2016. doi:10.1007/s00190-016-0918-5
    [BibTeX] [Abstract] [Download PDF]

    There has been considerable research in the literature focused on computing and forecasting sea-level changes in terms of constant trends or rates. The Antarctic ice sheet is one of the main contributors to sea-level change with highly uncertain rates of glacial thinning and accumulation. Geodetic observing systems such as the Gravity Recovery and Climate Experiment (GRACE) and the Global Positioning System (GPS) are routinely used to estimate these trends. In an effort to improve the accuracy and reliability of these trends, this study investigates a technique that allows the estimated rates, along with co-estimated seasonal components, to vary in time. For this, state space models are defined and then solved by a Kalman filter (KF). The reliable estimation of noise parameters is one of the main problems encountered when using a KF approach, which is solved by numerically optimizing likelihood. Since the optimization problem is non-convex, it is challenging to find an optimal solution. To address this issue, we limited the parameter search space using classical least-squares adjustment (LSA). In this context, we also tested the usage of inequality constraints by directly verifying whether they are supported by the data. The suggested technique for time-series analysis is expanded to classify and handle time-correlated observational noise within the state space framework. The performance of the method is demonstrated using GRACE and GPS data at the CAS1 station located in East Antarctica and compared to commonly used LSA. The results suggest that the outlined technique allows for more reliable trend estimates, as well as for more physically valuable interpretations, while validating independent observing systems.

    @article{didova.etal_2016,
    title = {An Approach for Estimating Time-Variable Rates from Geodetic Time Series},
    volume = {90},
    issn = {0949-7714, 1432-1394},
    doi = {10.1007/s00190-016-0918-5},
    abstract = {There has been considerable research in the literature focused on computing and forecasting sea-level changes in terms of constant trends or rates. The Antarctic ice sheet is one of the main contributors to sea-level change with highly uncertain rates of glacial thinning and accumulation. Geodetic observing systems such as the Gravity Recovery and Climate Experiment (GRACE) and the Global Positioning System (GPS) are routinely used to estimate these trends. In an effort to improve the accuracy and reliability of these trends, this study investigates a technique that allows the estimated rates, along with co-estimated seasonal components, to vary in time. For this, state space models are defined and then solved by a Kalman filter (KF). The reliable estimation of noise parameters is one of the main problems encountered when using a KF approach, which is solved by numerically optimizing likelihood. Since the optimization problem is non-convex, it is challenging to find an optimal solution. To address this issue, we limited the parameter search space using classical least-squares adjustment (LSA). In this context, we also tested the usage of inequality constraints by directly verifying whether they are supported by the data. The suggested technique for time-series analysis is expanded to classify and handle time-correlated observational noise within the state space framework. The performance of the method is demonstrated using GRACE and GPS data at the CAS1 station located in East Antarctica and compared to commonly used LSA. The results suggest that the outlined technique allows for more reliable trend estimates, as well as for more physically valuable interpretations, while validating independent observing systems.},
    language = {en},
    number = {11},
    urldate = {2016-12-24},
    url = {http://link.springer.com/article/10.1007/s00190-016-0918-5},
    journal = {Journal of Geodesy},
    author = {Didova, Olga and Gunter, Brian and Riva, Riccardo and Klees, Roland and Roese-Koerner, Lutz},
    month = nov,
    year = {2016},
    pages = {1207-1221},
    file = {/home/jmb/pc/internetSettings/zotero/storage/TDXUK3JS/Didova et al. - 2016 - An approach for estimating time-variable rates fro.pdf}
    }

2015

  • C. Esch, “Consistent Assimilation of Spaceborne Radar Interferometry (InSAR) Data into Integrated Terrestrial Systems. HPSC TerrSys Project-Report 2015,” {Institute of Geodesy and Geoinformation, Department of Theoretical Geodesy, University Bonn} 2015.
    [BibTeX]
    @techreport{esch_15,
    title = {Consistent Assimilation of Spaceborne Radar Interferometry ({{InSAR}}) Data into Integrated Terrestrial Systems. {{HPSC TerrSys Project}}-{{Report}} 2015},
    institution = {{Institute of Geodesy and Geoinformation, Department of Theoretical Geodesy, University Bonn}},
    author = {Esch, Christina},
    year = {2015},
    owner = {swd},
    note = {esch\textsubscript{1}5}
    }

  • K. R. Koch and B. Kargoll, “Outlier Detection by the EM Algorithm for Laser Scanning in Rectangular and Polar Coordinate Systems,” J Applied Geodesy, vol. 9, pp. 162-173, 2015. doi:10.1515/jag-2015-0004
    [BibTeX]
    @article{koch-kargoll_15b,
    title = {Outlier Detection by the {{EM}} Algorithm for Laser Scanning in Rectangular and Polar Coordinate Systems},
    volume = {9},
    doi = {10.1515/jag-2015-0004},
    journal = {J Applied Geodesy},
    author = {Koch, K.R. and Kargoll, B.},
    year = {2015},
    pages = {162-173},
    owner = {swd}
    }

  • K. R. Koch, “Minimal Detectable Outliers as Measures of Reliability,” J Geodesy, vol. 89, pp. 483-490, 2015. doi:10.1007/s00190-015-0793-5
    [BibTeX]
    @article{koch_15,
    title = {Minimal Detectable Outliers as Measures of Reliability},
    volume = {89},
    doi = {10.1007/s00190-015-0793-5},
    journal = {J Geodesy},
    author = {Koch, K.R.},
    year = {2015},
    pages = {483-490},
    owner = {swd}
    }

  • K. R. Koch, “Prediction of Missing Measurements for Laser Scanners,” Allgemeine Vermessungs-Nachrichten, vol. 122, pp. 140-144, 2015.
    [BibTeX] [Download PDF]
    @article{koch_15a,
    title = {Prediction of {{Missing Measurements}} for {{Laser Scanners}}},
    volume = {122},
    url = {http://gispoint.de/artikelarchiv/avn/2015/avn-ausgabe-042015/},
    journal = {Allgemeine Vermessungs-Nachrichten},
    author = {Koch, K.R.},
    year = {2015},
    pages = {140-144},
    owner = {schuh}
    }

  • I. Krasbutter, B. Kargoll, and W. -D. Schuh, “Magic Square of Real Spectral and Time Series Analysis with an Application to Moving Average Processes,” in The 1st International Workshop on the Quality of Geodetic Observation and Monitoring Systems (QuGOMS’11), IAG Symposia, H. Kutterer, F. Seitz, H. Alkhatib, and M. Schmidt, Eds., {Springer}, 2015, vol. 140, pp. 9-14.
    [BibTeX]
    @incollection{krasbutter-etal_15,
    series = {International Association of Geodesy Symposia},
    title = {Magic {{Square}} of {{Real Spectral}} and {{Time Series Analysis}} with an {{Application}} to {{Moving Average Processes}}},
    volume = {140},
    isbn = {978-3-319-10827-8},
    language = {English},
    booktitle = {The 1st {{International Workshop}} on the {{Quality}} of {{Geodetic Observation}} and {{Monitoring Systems}} ({{QuGOMS}}'11), {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {Krasbutter, I. and Kargoll, B. and Schuh, W.-D.},
    editor = {Kutterer, H. and Seitz, F. and Alkhatib, H. and Schmidt, M.},
    year = {2015},
    keywords = {Moving average process,Spectral analysis,Stochastic process,Time series analysis},
    pages = {9-14},
    owner = {swd},
    note = {krasbutter-etal\textsubscript{1}5}
    }

  • L. Roese-Koerner, B. Devaraju, W. -D. Schuh, and N. Sneeuw, “Describing the Quality of Inequality Constrained Estimates,” in The 1st International Workshop on the Quality of Geodetic Observation and Monitoring Systems (QuGOMS’11), IAG Symposia, H. Kutterer, F. Seitz, H. Alkhatib, and M. Schmidt, Eds., {Springer}, 2015, vol. 140, pp. 15-20.
    [BibTeX]
    @incollection{roese-koerner-etal_15,
    series = {International Association of Geodesy Symposia},
    title = {Describing the {{Quality}} of {{Inequality Constrained Estimates}}},
    volume = {140},
    isbn = {978-3-319-10827-8},
    language = {English},
    booktitle = {The 1st {{International Workshop}} on the {{Quality}} of {{Geodetic Observation}} and {{Monitoring Systems}} ({{QuGOMS}}'11), {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {Roese-Koerner, L. and Devaraju, B. and Schuh, W.-D. and Sneeuw, N.},
    editor = {Kutterer, H. and Seitz, F. and Alkhatib, H. and Schmidt, M.},
    year = {2015},
    keywords = {Monte Carlo method,Confidence regions,Convex optimization,Inequality constrained least-squares,Stochastic modeling},
    pages = {15-20},
    owner = {swd},
    note = {roese-koerner-etal\textsubscript{1}5}
    }

  • W. -D. Schuh, S. Müller, and J. M. Brockmann, “Completion of Band-Limited Data Sets on the Sphere,” in The 1st International Workshop on the Quality of Geodetic Observations and Monitoring Systems (QuGOMS’11), IAG Symposia, H. Kutterer, F. Seitz, H. Alkhatib, and M. Schmidt, Eds., {Springer}, 2015, vol. 140, pp. 171-178.
    [BibTeX]
    @incollection{schuh-etal_15a,
    series = {Lecture Notes in Earth Science},
    title = {Completion of Band-Limited Data Sets on the Sphere},
    volume = {140},
    booktitle = {The 1st {{International Workshop}} on the {{Quality}} of {{Geodetic Observations}} and {{Monitoring Systems}} ({{QuGOMS}}'11), {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {Schuh, W.-D. and M{\"u}ller, S. and Brockmann, J. M.},
    editor = {Kutterer, H and Seitz, F and Alkhatib, H and Schmidt, M},
    year = {2015},
    pages = {171-178},
    owner = {swd},
    note = {schuh-etal\textsubscript{1}5a}
    }

  • J. Köhler, “Entwicklung von Datenstrukturen Zur Darstellung Der Raum/Zeitlichen Zusammenhänge Zwischen Kohärenten Pixeln in D-InSAR-Bildstapeln,” Master Thesis, Bonn, Germany, 2015.
    [BibTeX]
    @mastersthesis{koehler_2015,
    address = {Bonn, Germany},
    title = {Entwicklung von {{Datenstrukturen}} Zur {{Darstellung}} Der Raum/Zeitlichen {{Zusammenh{\"a}nge}} Zwischen Koh{\"a}renten {{Pixeln}} in {{D}}-{{InSAR}}-{{Bildstapeln}}},
    school = {Universit{\"a}t Bonn, Institut f{\"u}r Geod{\"a}sie und Geoinformation},
    author = {K{\"o}hler, Jo{\"e}l},
    year = {2015},
    file = {/home/jmb/pc/internetSettings/zotero/storage/62I9C5SZ/Masterarbeit_J_Koehler.pdf}
    }

2014

  • S. Becker, J. M. Brockmann, and W. -D. Schuh, “Mean Dynamic Topography Estimates Purely Based on GOCE Gravity Field Models and Altimetry,” Geophysical Research Letters, vol. 41, iss. 6, pp. 2063-2069, 2014. doi:10.1002/2014GL059510
    [BibTeX] [Abstract]

    The quality of mean dynamic topography (MDT) models derived from an altimetric mean sea surface and a gravity field model mainly depends on the spatial resolution and accuracy of the particular gravity field model. We use an integrated approach which allows for estimating the MDT and its (inverse) covariance matrix on a predefined grid which is one of the requirements for ocean data assimilation. The quality and accuracy of the MDT directly reflects the quality and accuracy of the used gravity field model. For the first time, MDT estimates along with its full error covariance matrix based on GOCE data can be provided. We demonstrate the progress accomplished with GOCE processing and the valuable contribution of the GOCE gravity field models regarding the estimation of the MDT by showing results based on altimetric observations of Jason-1 and Envisat in combination with different GOCE gravity field models for the North Atlantic.

    @article{becker-etal_14b,
    title = {Mean Dynamic Topography Estimates Purely Based on {{GOCE}} Gravity Field Models and Altimetry},
    volume = {41},
    issn = {1944-8007},
    doi = {10.1002/2014GL059510},
    abstract = {The quality of mean dynamic topography (MDT) models derived from an altimetric mean sea surface and a gravity field model mainly depends on the spatial resolution and accuracy of the particular gravity field model. We use an integrated approach which allows for estimating the MDT and its (inverse) covariance matrix on a predefined grid which is one of the requirements for ocean data assimilation. The quality and accuracy of the MDT directly reflects the quality and accuracy of the used gravity field model. For the first time, MDT estimates along with its full error covariance matrix based on GOCE data can be provided. We demonstrate the progress accomplished with GOCE processing and the valuable contribution of the GOCE gravity field models regarding the estimation of the MDT by showing results based on altimetric observations of Jason-1 and Envisat in combination with different GOCE gravity field models for the North Atlantic.},
    number = {6},
    journal = {Geophysical Research Letters},
    author = {Becker, S. and Brockmann, J. M. and Schuh, W.-D.},
    year = {2014},
    keywords = {GOCE,mean dynamic topography,gravity field,consistent combination},
    pages = {2063-2069},
    owner = {swd},
    note = {becker-etal\textsubscript{1}4b}
    }

  • S. Becker, M. Losch, J. M. Brockmann, G. Freiwald, and W. -D. Schuh, “A Tailored Computation of the Mean Dynamic Topography for a Consistent Integration into Ocean Circulation Models,” Surveys in Geophysics, vol. 35, iss. 6, pp. 1507-1525, 2014. doi:10.1007/s10712-013-9272-9
    [BibTeX]
    @article{becker-etal_14a,
    title = {A Tailored Computation of the Mean Dynamic Topography for a Consistent Integration into Ocean Circulation Models},
    volume = {35},
    doi = {10.1007/s10712-013-9272-9},
    number = {6},
    journal = {Surveys in Geophysics},
    author = {Becker, S. and Losch, M. and Brockmann, J. M. and Freiwald, G. and Schuh, W.-D.},
    year = {2014},
    keywords = {mean dynamic topography,gravity field,consistent combination,Altimetry,Ocean circulation},
    pages = {1507-1525},
    owner = {swd},
    note = {becker-etal\textsubscript{1}4a}
    }

  • J. M. Brockmann, L. Roese-Koerner, and W. Schuh, “A Concept for the Estimation of High-Degree Gravity Field Models in a High Performance Computing Environment,” Studia Geophysica et Geodaetica, vol. 58, iss. 4, pp. 571-594, 2014. doi:10.1007/s11200-013-1246-3
    [BibTeX]
    @article{brockmann-etal_14,
    title = {A Concept for the Estimation of High-Degree Gravity Field Models in a High Performance Computing Environment},
    volume = {58},
    issn = {0039-3169},
    doi = {10.1007/s11200-013-1246-3},
    language = {English},
    number = {4},
    journal = {Studia Geophysica et Geodaetica},
    author = {Brockmann, Jan Martin and Roese-Koerner, Lutz and Schuh, Wolf-Dieter},
    year = {2014},
    keywords = {high performance computing,iterative solvers,global gravity field recovery,high-degree spherical harmonics},
    pages = {571-594},
    owner = {swd},
    note = {brockmann-etal\textsubscript{1}4}
    }

  • J. M. Brockmann, L. Roese-Koerner, and W. Schuh, “Use of High Performance Computing for the Rigorous Estimation of Very High Degree Spherical Harmonic Gravity Field Models,” in Gravity, Geoid and Height Systems (GGHS 2012), IAG Symposia, U. Marti, Ed., {Springer}, 2014, vol. 141, pp. 27-33.
    [BibTeX]
    @incollection{brockmann-etal_14b,
    series = {Lecture Notes in Earth Science},
    title = {Use of {{High Performance Computing}} for the {{Rigorous Estimation}} of {{Very High Degree Spherical Harmonic Gravity Field Models}}},
    volume = {141},
    booktitle = {Gravity, {{Geoid}} and {{Height Systems}} ({{GGHS}} 2012), {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {Brockmann, Jan Martin and Roese-Koerner, Lutz and Schuh, Wolf-Dieter},
    editor = {Marti, U.},
    year = {2014},
    pages = {27-33},
    owner = {swd},
    note = {brockmann-etal\textsubscript{1}4b}
    }

  • J. M. Brockmann, “On High Performance Computing in Geodesy – Applications in Global Gravity Field Determination,” PhD Thesis, Bonn, Germany, 2014.
    [BibTeX] [Download PDF]
    @phdthesis{brockmann_14,
    address = {Bonn, Germany},
    title = {On {{High Performance Computing}} in {{Geodesy}} -- {{Applications}} in {{Global Gravity Field Determination}}},
    url = {http://nbn-resolving.de/urn:nbn:de:hbz:5n-38608},
    school = {Rheinischen Friedrich-Wilhelms-Universit{\"a}t Bonn},
    author = {Brockmann, Jan Martin},
    year = {2014},
    owner = {jmb},
    note = {brockmann\textsubscript{1}4}
    }

  • J. M. Brockmann, N. Zehentner, E. Höck, R. Pail, I. Loth, T. Mayer-Gürr, and W. -D. Schuh, “EGM_TIM_RL05: An Independent Geoid with Centimeter Accuracy Purely Based on the GOCE Mission,” Geophysical Research Letters, vol. 41, iss. 22, pp. 8089-8099, 2014. doi:10.1002/2014GL061904
    [BibTeX] [Abstract]

    After more than 4.5\,years in orbit, the Gravity field and steady-state Ocean Circulation Explorer (GOCE) mission ended with the reentry of the satellite on 11 November 2013. This publication serves as a reference for the 5th gravity field model based on the time-wise approach (EGM\textsubscript{T}IM\textsubscript{R}L05), a global model only determined from GOCE observations. Due to its independence of any other gravity data, a consistent and homogeneous set of spherical harmonic coefficients up to degree and order 280 (corresponding to spatial resolution of 71.5 km on ground) is provided including a full covariance matrix characterizing the uncertainties of the model. The associated covariance matrix realistically describes the model quality. It is the first model which is purely based on GOCE including all observations collected during the entire mission. The achieved mean global accuracy is 2.4 cm in terms of geoid heights and 0.7 mGal for gravity anomalies at a spatial resolution of 100 km.

    @article{brockmann-etal_14c,
    title = {{{EGM}}\_{{TIM}}\_{{RL05}}: {{An Independent Geoid}} with {{Centimeter Accuracy Purely Based}} on the {{GOCE Mission}}},
    volume = {41},
    doi = {10.1002/2014GL061904},
    abstract = {After more than 4.5\,years in orbit, the Gravity field and steady-state Ocean Circulation Explorer (GOCE) mission ended with the reentry of the satellite on 11 November 2013. This publication serves as a reference for the 5th gravity field model based on the time-wise approach (EGM\textsubscript{T}IM\textsubscript{R}L05), a global model only determined from GOCE observations. Due to its independence of any other gravity data, a consistent and homogeneous set of spherical harmonic coefficients up to degree and order 280 (corresponding to spatial resolution of 71.5 km on ground) is provided including a full covariance matrix characterizing the uncertainties of the model. The associated covariance matrix realistically describes the model quality. It is the first model which is purely based on GOCE including all observations collected during the entire mission. The achieved mean global accuracy is 2.4 cm in terms of geoid heights and 0.7 mGal for gravity anomalies at a spatial resolution of 100 km.},
    number = {22},
    journal = {Geophysical Research Letters},
    author = {Brockmann, J. M. and Zehentner, N. and H{\"o}ck, E. and Pail, R. and Loth, I. and Mayer-G{\"u}rr, T. and Schuh, W.-D.},
    year = {2014},
    keywords = {GOCE,Earth's gravity field determination,spherical harmonic model},
    pages = {8089-8099},
    file = {/home/jmb/pc/internetSettings/zotero/storage/GS2C274E/brockmann_etal_2014a.pdf},
    owner = {swd},
    note = {brockmann-etal\textsubscript{1}4c}
    }

  • E. Forootan, J. Kusche, I. Loth, W. -D. Schuh, A. Eicker, J. Awange, L. Longuevergne, B. Diekkrüger, M. Schmidt, and C. K. Shum, “Multivariate Prediction of Total Water Storage Changes over West Africa from Multi-Satellite Data,” Surveys in Geophysics, vol. 35, pp. 913-940, 2014. doi:10.1007/s10712-014-9292-0
    [BibTeX]
    @article{forootan-etal_14,
    title = {Multivariate Prediction of Total Water Storage Changes over {{West Africa}} from Multi-Satellite Data},
    volume = {35},
    doi = {10.1007/s10712-014-9292-0},
    journal = {Surveys in Geophysics},
    author = {Forootan, E. and Kusche, J. and Loth, I. and Schuh, W.-D. and Eicker, A. and Awange, J. and Longuevergne, L. and Diekkr{\"u}ger, B. and Schmidt, M. and Shum, C.K.},
    year = {2014},
    pages = {913-940},
    owner = {swd},
    note = {forootan-etal\textsubscript{1}4}
    }

  • K. R. Koch, “Outlier Detection for the Nonlinear Gauss Helmert Model with Variance Components by the Expectation Maximization Algorithm,” J Applied Geodesy, vol. 8, iss. 3, pp. 185-194, 2014. doi:10.1515/jag-2014-0004
    [BibTeX]
    @article{koch_14b,
    title = {Outlier Detection for the Nonlinear {{Gauss Helmert}} Model with Variance Components by the Expectation Maximization Algorithm},
    volume = {8},
    doi = {10.1515/jag-2014-0004},
    number = {3},
    journal = {J Applied Geodesy},
    author = {Koch, K.R.},
    year = {2014},
    pages = {185-194},
    owner = {swd}
    }

  • K. R. Koch, “Predicting Missing Observations in Linear Models,” ZfV–Z Geodäsie, Geoinformation und Landmanagement, vol. 139, pp. 110-114, 2014.
    [BibTeX]
    @article{koch_14a,
    title = {Predicting Missing Observations in Linear Models},
    volume = {139},
    journal = {ZfV--Z Geod{\"a}sie, Geoinformation und Landmanagement},
    author = {Koch, K.R.},
    year = {2014},
    keywords = {expectation maximization algorithm,laser scanner,linear model,Missing observations,prediction},
    pages = {110-114},
    owner = {swd}
    }

  • K. R. Koch, “Robust Estimations for the Nonlinear Gauss Helmert Model by the Expectation Maximization Algorithm,” J Geodesy, vol. 88, pp. 263-271, 2014. doi:10.1007/s00190-013-0681-9
    [BibTeX]
    @article{koch_14,
    title = {Robust Estimations for the Nonlinear {{Gauss Helmert}} Model by the Expectation Maximization Algorithm},
    volume = {88},
    doi = {10.1007/s00190-013-0681-9},
    journal = {J Geodesy},
    author = {Koch, K.R.},
    year = {2014},
    pages = {263-271},
    owner = {swd}
    }

  • I. Krasbutter, J. M. Brockmann, B. Kargoll, and W. -D. Schuh, “Adjustment of Digital Filters for Decorrelation of GOCE SGG Data,” in Observation of the System Earth from Space – CHAMP, GRACE, GOCE and Future Missions., F. Flechtner, N. Sneeuw, and W. -D. Schuh, Eds., {Springer}, 2014, vol. 20, pp. 109-114.
    [BibTeX]
    @incollection{krasbutter-etal_14,
    series = {Advanced Technologies in Earth Sciences, GEOTECHNOLOGIEN Science Report},
    title = {Adjustment of Digital Filters for Decorrelation of {{GOCE SGG}} Data},
    volume = {20},
    booktitle = {Observation of the {{System Earth}} from {{Space}} - {{CHAMP}}, {{GRACE}}, {{GOCE}} and Future Missions.},
    publisher = {{Springer}},
    author = {Krasbutter, I. and Brockmann, J. M. and Kargoll, B. and Schuh, W.-D.},
    editor = {Flechtner, F. and Sneeuw, N. and Schuh, W.-D.},
    year = {2014},
    pages = {109-114},
    owner = {swd},
    note = {krasbutter-etal\textsubscript{1}4}
    }

  • I. Loth (née Krasbutter), “Consistent Assimilation of Spaceborne Radar Interferometriy (InSAR) Data into Integrated Terrestrial Systems. HPSC TerrSys Project-Report 2014,” {Institute of Geodesy and Geoinformation, Department of Theoretical Geodesy, University Bonn} 2014.
    [BibTeX]
    @techreport{loth_14,
    title = {Consistent Assimilation of Spaceborne Radar Interferometriy ({{InSAR}}) Data into Integrated Terrestrial Systems. {{HPSC TerrSys Project}}-{{Report}} 2014},
    institution = {{Institute of Geodesy and Geoinformation, Department of Theoretical Geodesy, University Bonn}},
    author = {Loth (n{\'e}e Krasbutter), I.},
    year = {2014},
    owner = {swd}
    }

  • S. Müller, J. M. Brockmann, and W. Schuh, “Consistent Combination of Gravity Field, Altimetry and Hydrographic Data,” in Gravity, Geoid and Height Systems (GGHS 2012), IAG Symposia, U. Marti, Ed., {Springer}, 2014, vol. 141, pp. 267-273.
    [BibTeX]
    @incollection{mueller-etal_14,
    series = {Lecture Notes in Earth Sciences},
    title = {Consistent {{Combination}} of {{Gravity Field}}, {{Altimetry}} and {{Hydrographic Data}}},
    volume = {141},
    booktitle = {Gravity, {{Geoid}} and {{Height Systems}} ({{GGHS}} 2012), {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {M{\"u}ller, Silvia and Brockmann, Jan Martin and Schuh, Wolf-Dieter},
    editor = {Marti, U.},
    year = {2014},
    pages = {267-273},
    owner = {swd},
    note = {mueller-etal\textsubscript{1}4}
    }

  • R. Pail, A. Albertella, D. Rieser, J. M. Brockmann, W. Schuh, and R. Savcenko, “Satellite Gravity Models and Their Use for Estimating Mean Ocean Circulation,” in Earth on the Edge: Science for a Sustainable Planet, IAG Symposia, C. Rizos and P. Willis, Eds., {Springer}, 2014, vol. 139, pp. 275-281.
    [BibTeX]
    @incollection{pail-etal_14,
    series = {Lecture Notes in Earth Science},
    title = {Satellite {{Gravity Models}} and {{Their Use}} for {{Estimating Mean Ocean Circulation}}},
    volume = {139},
    language = {English},
    booktitle = {Earth on the {{Edge}}: {{Science}} for a {{Sustainable Planet}}, {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {Pail, Roland and Albertella, Alberta and Rieser, Daniel and Brockmann, Jan Martin and Schuh, Wolf-Dieter and Savcenko, Roman},
    editor = {Rizos, Chris and Willis, Pascal},
    year = {2014},
    keywords = {GOCE,mean dynamic topography,Global gravity model,Ocean currents,Spherical harmonics},
    pages = {275-281},
    owner = {swd},
    note = {pail-etal\textsubscript{1}4}
    }

  • L. Roese-Koerner and W. -D. Schuh, “Convex Optimization under Inequality Constraints in Rank Deficient Systems,” Journal of Geodesy, vol. 88, iss. 5, pp. 415-426, 2014. doi:10.1007/s00190-014-0692-1
    [BibTeX] [Abstract]

    Many geodetic applications require the minimiza- tion of a convex objective function subject to some linear equality and/or inequality constraints. If a system is singu- lar (e.g. a geodetic network without a defined datum) this results in a manifold of solutions. Most state-of-the-art al- gorithms for inequality constrained optimization (e.g. the Active-Set-Method or primal-dual Interior-Point-Methods) are either not able to deal with a rank deficient objective function or yield only one of an infinite number of particu- lar solutions. In this contribution, we develop a framework for the rig- orous computation of a general solution of a rank deficient problem with inequality constraints. We aim for the com- putation of a unique particular solution which fulfills pre- defined optimality criteria as well as for an adequate rep- resentation of the homogeneous solution including the con- straints. In a case study, our theoretical findings are applied to de- termine optimal repetition numbers for a geodetic network to demonstrate the potential of the proposed framework.

    @article{roese-koerner-schuh_14,
    title = {Convex {{Optimization}} under Inequality Constraints in Rank Deficient Systems},
    volume = {88},
    doi = {10.1007/s00190-014-0692-1},
    abstract = {Many geodetic applications require the minimiza- tion of a convex objective function subject to some linear equality and/or inequality constraints. If a system is singu- lar (e.g. a geodetic network without a defined datum) this results in a manifold of solutions. Most state-of-the-art al- gorithms for inequality constrained optimization (e.g. the Active-Set-Method or primal-dual Interior-Point-Methods) are either not able to deal with a rank deficient objective function or yield only one of an infinite number of particu- lar solutions. In this contribution, we develop a framework for the rig- orous computation of a general solution of a rank deficient problem with inequality constraints. We aim for the com- putation of a unique particular solution which fulfills pre- defined optimality criteria as well as for an adequate rep- resentation of the homogeneous solution including the con- straints. In a case study, our theoretical findings are applied to de- termine optimal repetition numbers for a geodetic network to demonstrate the potential of the proposed framework.},
    number = {5},
    journal = {Journal of Geodesy},
    author = {Roese-Koerner, L. and Schuh, W.-D.},
    year = {2014},
    pages = {415 - 426},
    owner = {swd},
    note = {roese-koerner-schuh\textsubscript{1}4}
    }

  • L. Roese-Koerner and W. Schuh, “Effects of Different Objective Functions in Inequality Constrained and Rank-Deficient Least-Squares Problems,” in VIII. Hotine-Marussi-Symposium, IAG Symposia, N. Sneeuw, P. Novák, M. Crespi, and F. Sansò, Eds., {Springer}, 2014, vol. 142.
    [BibTeX]
    @incollection{roese-koerner-schuh_14b,
    series = {Lecture Notes in Earth Science},
    title = {Effects of {{Different Objective Functions}} in {{Inequality Constrained}} and {{Rank}}-{{Deficient Least}}-{{Squares Problems}}},
    volume = {142},
    booktitle = {{{VIII}}. {{Hotine}}-{{Marussi}}-{{Symposium}}, {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {Roese-Koerner, Lutz and Schuh, Wolf-Dieter},
    editor = {Sneeuw, Nico and Nov{\'a}k, Pavel and Crespi, Mattia and Sans{\`o}, Fernando},
    year = {2014},
    owner = {swd},
    note = {(in print)}
    }

  • W. -D. Schuh and B. Kargoll, “Real Data Analysis GOCE (REAL GOCE): A Retrospective Overview,” in Observation of the System Earth from Space – CHAMP, GRACE, GOCE and Future Missions. GEOTECHNOLOGIEN Science Report, F. Flechtner, N. Sneeuw, and W. -D. Schuh, Eds., {Springer (Advanced Technologies in Earth Sciences), Heidelberg}, 2014, vol. 20, pp. 75-79.
    [BibTeX]
    @incollection{schuh-kargoll_14,
    title = {Real {{Data Analysis GOCE}} ({{REAL GOCE}}): A Retrospective Overview},
    volume = {20},
    isbn = {978-3-642-32134-4},
    booktitle = {Observation of the {{System Earth}} from {{Space}} - {{CHAMP}}, {{GRACE}}, {{GOCE}} and Future Missions. {{GEOTECHNOLOGIEN Science Report}}},
    publisher = {{Springer (Advanced Technologies in Earth Sciences), Heidelberg}},
    author = {Schuh, W.-D. and Kargoll, B.},
    editor = {Flechtner, F. and Sneeuw, N. and Schuh, W.-D.},
    year = {2014},
    pages = {75-79},
    owner = {swd},
    note = {schuh-kargoll\textsubscript{1}4}
    }

  • W. Schuh, I. Krasbutter, and B. Kargoll, “Korrelierte Messung – Was Nun?,” in Zeitabhängige Messgrößen – Ihre Daten Haben (Mehr-)Wert, H. Neuner, Ed., {Wißner, Augsburg}, 2014, vol. 74, pp. 85-101.
    [BibTeX]
    @incollection{schuh-etal_14,
    series = {DVW-Schriftenreihe},
    title = {Korrelierte {{Messung}} - Was Nun?},
    volume = {74},
    booktitle = {Zeitabh{\"a}ngige {{Messgr{\"o}{\ss}en}} - {{Ihre Daten}} Haben ({{Mehr}}-){{Wert}}},
    publisher = {{Wi{\ss}ner, Augsburg}},
    author = {Schuh, Wolf-Dieter and Krasbutter, Ina and Kargoll, Boris},
    editor = {Neuner, Hans},
    year = {2014},
    keywords = {Stochastische Prozesse,Magisches Quadrat,Cholesky,Autokovarianzen,Dekorrelation},
    pages = {85 - 101},
    owner = {swd},
    note = {schuh-etal\textsubscript{1}4}
    }

2013

  • S. Halsig, A. Ernst, and W. -D. Schuh, “Ausgleichung von Höhennetzen Aus Mehreren Epochen Unter Berücksichtigung von Bodenbewegungen,” Zeitschrift für Vermessungswesen, vol. 138, iss. 4, pp. 288-297, 2013.
    [BibTeX] [Download PDF]
    @article{halsig-etal_13,
    title = {Ausgleichung von {{H{\"o}hennetzen}} Aus Mehreren {{Epochen}} Unter {{Ber{\"u}cksichtigung}} von {{Bodenbewegungen}}},
    volume = {138},
    number = {4},
    url = {http://geodaesie.info/zfv/heftbeitrag/1768},
    journal = {Zeitschrift f{\"u}r Vermessungswesen},
    author = {Halsig, S. and Ernst, A. and Schuh, W.-D.},
    year = {2013},
    pages = {288 - 297},
    owner = {swd},
    note = {halsig-etal\textsubscript{1}3}
    }

  • G. Jager, A. Kunoth, and W. Schuh, “Approximate Continuation of Harmonic Functions in Geodesy: A Spline Based Least Squares Approach with Regularization,” Journal of Computational and Applied Mathematics, vol. 237, pp. 62-82, 2013. doi:10.1016/j.cam.2012.07.007
    [BibTeX]
    @article{jager-etal_13,
    title = {Approximate Continuation of Harmonic Functions in Geodesy: {{A}} Spline Based Least Squares Approach with Regularization},
    volume = {237},
    issn = {0377-0427},
    doi = {10.1016/j.cam.2012.07.007},
    journal = {Journal of Computational and Applied Mathematics},
    author = {Jager, Gabriela and Kunoth, Angela and Schuh, Wolf-Dieter},
    year = {2013},
    pages = {62 - 82},
    owner = {swd}
    }

  • K. R. Koch and B. Kargoll, “Expectation Maximization Algorithm for the Variance-Inflation Model by Applying the t-Distribution,” J Applied Geodesy, vol. 7, pp. 115-123, 2013. doi:10.1515/jag-2013-0007
    [BibTeX]
    @article{koch-kargoll_13,
    title = {Expectation Maximization Algorithm for the Variance-Inflation Model by Applying the t-Distribution},
    volume = {7},
    doi = {10.1515/jag-2013-0007},
    journal = {J Applied Geodesy},
    author = {Koch, K.R. and Kargoll, B.},
    year = {2013},
    pages = {115-123},
    owner = {swd}
    }

  • K. R. Koch, “Comparison of Two Robust Estimations by Expectation Maximization Algorithms with Huber’s Method and Outlier Tests,” Journal of Applied Geodesy, vol. 7, pp. 115-124, 2013. doi:10.1515/jag-2013-0050
    [BibTeX] [Abstract]

    The robust estimation by the expectation maximization (EM) algorithm is derived for the variance-inflation model in addition to the known estimation for the mean-shift model. To compare these methods with the tau – test, Huber’s robust M-estimation and the multiple outlier test, a random linear model and laser scans for fitting a plane are generated by Monte Carlo methods. It turns out that the results for detecting outliers by the EM algorithms for the mean-shift and variance-inflation model approximately agree although the numbers of convergences are different. The results are superior to the ones of the methods with which they are compared. In case of the generated laser scans, the maximum number of outliers, which can be detected, is approximately identified.

    @article{koch_13a,
    title = {Comparison of Two Robust Estimations by Expectation Maximization Algorithms with {{Huber}}'s Method and Outlier Tests},
    volume = {7},
    doi = {10.1515/jag-2013-0050},
    abstract = {The robust estimation by the expectation maximization (EM) algorithm is derived for the variance-inflation model in addition to the known estimation for the mean-shift model. To compare these methods with the tau - test, Huber's robust M-estimation and the multiple outlier test, a random linear model and laser scans for fitting a plane are generated by Monte Carlo methods. It turns out that the results for detecting outliers by the EM algorithms for the mean-shift and variance-inflation model approximately agree although the numbers of convergences are different. The results are superior to the ones of the methods with which they are compared. In case of the generated laser scans, the maximum number of outliers, which can be detected, is approximately identified.},
    journal = {Journal of Applied Geodesy},
    author = {Koch, K.R.},
    year = {2013},
    keywords = {EM algorithm,Huber's M-estimation,mean-shift model,Monte Carlo method,multiple outlier test,tau-test,variance-inflation model},
    pages = {115 - 124},
    owner = {swd},
    note = {ISSN (Print) 1862-9016 ISSN (Online) 1862-9024}
    }

  • K. R. Koch, “Comparison of Two Robust Estimations by Expectation Maximization Algorithms with Huber’s Method and Outlier Tests,” J Applied Geodesy, vol. 7, p. (online first), 2013. doi:10.1515/jag-2012-0050
    [BibTeX]
    @article{koch_o13a,
    title = {Comparison of Two Robust Estimations by Expectation Maximization Algorithms with {{Huber}}'s Method and Outlier Tests},
    volume = {7},
    doi = {10.1515/jag-2012-0050},
    journal = {J Applied Geodesy},
    author = {Koch, K.R.},
    year = {2013},
    pages = {(online first)},
    owner = {swd}
    }

  • K. R. Koch, “Robust Estimation by Expectation Maximization Algorithm,” Journal of Geodesy, vol. 87, pp. 107-116, 2013. doi:10.1007/s00190-012-0582-3
    [BibTeX]
    @article{koch_13,
    title = {Robust Estimation by Expectation Maximization Algorithm},
    volume = {87},
    doi = {10.1007/s00190-012-0582-3},
    journal = {Journal of Geodesy},
    author = {Koch, K.R.},
    year = {2013},
    pages = {107-116},
    owner = {swd}
    }

  • J. Köhler, “Ermittlung Des Atmosphärischen Phasenanteils in Interferometrischen SAR-Daten Und Vergleich Mit in Situ Wetterdaten,” Bachelorsthesis PhD Thesis, Bonn, Germany, 2013.
    [BibTeX]
    @phdthesis{koehler_2013,
    address = {Bonn, Germany},
    type = {Bachelorsthesis},
    title = {Ermittlung Des Atmosph{\"a}rischen {{Phasenanteils}} in Interferometrischen {{SAR}}-{{Daten}} Und {{Vergleich}} Mit in Situ {{Wetterdaten}}},
    school = {Universit{\"a}t Bonn, Institut f{\"u}r Geod{\"a}sie und Geoinformation},
    author = {K{\"o}hler, Jo{\"e}l},
    year = {2013},
    file = {/home/jmb/pc/internetSettings/zotero/storage/ZLWRI92G/ba_J_Koehler.pdf}
    }

2012

  • S. Becker, G. Freiwald, M. Losch, and W. -D. Schuh, “Rigorous Fusion of Gravity Field, Altimetry and Stationary Ocean Models,” Journal of Geodynamics, vol. 59-60, pp. 99-110, 2012. doi:10.1016/j.jog.2011.07.006
    [BibTeX] [Download PDF]
    @article{becker-etal_12,
    title = {Rigorous {{Fusion}} of {{Gravity Field}}, {{Altimetry}} and {{Stationary Ocean Models}}},
    volume = {59-60},
    doi = {10.1016/j.jog.2011.07.006},
    url = {http://www.sciencedirect.com/science/article/pii/S0264370711000834},
    journal = {Journal of Geodynamics},
    author = {Becker, S. and Freiwald, G. and Losch, M and Schuh, W.-D.},
    year = {2012},
    pages = {99-110},
    owner = {swd}
    }

  • S. Becker, “Konsistente Kombination von Schwerefeld, Altimetrie Und Hydrographischen Daten Zur Modellierung Der Dynamischen Ozeantopographie,” PhD Thesis, 2012.
    [BibTeX] [Download PDF]
    @phdthesis{becker_12,
    title = {Konsistente {{Kombination}} von {{Schwerefeld}}, {{Altimetrie}} Und Hydrographischen {{Daten}} Zur {{Modellierung}} Der Dynamischen {{Ozeantopographie}}},
    url = {http://nbn-resolving.de/urn:nbn:de:hbz:5n-29199},
    school = {Promotion an der Landwirtschaftliche Fakult{\"a}t der Universit{\"a}t Bonn, Schriftenreihe des Instituts f{\"u}r Geod{\"a}sie und Geoinformation der Rheinischen Friedrich-Wilhelms-Universit{\"a}t, Folge 31},
    author = {Becker, S.},
    year = {2012},
    owner = {swd}
    }

  • J. M. Brockmann and B. Kargoll, “Uncertainty Assessment of Some Data-Adaptive M-Estimators,” in VII. Hotine-Marussi-Symposium, IAG Symposia, N. Sneeuw, P. Novák, M. Crespi, and F. Sansò, Eds., {Springer}, 2012, vol. 137, pp. 87-92.
    [BibTeX] [Abstract]

    The effect of reordering strategies on the rounding errors is considered for the factorization and solution of sparse symmetric systems. On the one hand, a reduction of rounding errors can be expected, because the number of floating point operations decreases. On the other hand, the clustering of neighboring parameters and therefore the fixing of the sequence of parameter elimination may result in numerical instabilities. These effects are demonstrated for sparse covariance matrices in Wiener filtering. In particular Cholesky factorization and profile reordering in conjunction with envelope storage schemes are examined.

    @incollection{brockmann-kargoll_12,
    series = {Lecture Notes in Earth Science},
    title = {Uncertainty Assessment of Some Data-Adaptive {{M}}-Estimators},
    volume = {137},
    abstract = {The effect of reordering strategies on the rounding errors is considered for the factorization and solution of sparse symmetric systems. On the one hand, a reduction of rounding errors can be expected, because the number of floating point operations decreases. On the other hand, the clustering of neighboring parameters and therefore the fixing of the sequence of parameter elimination may result in numerical instabilities. These effects are demonstrated for sparse covariance matrices in Wiener filtering. In particular Cholesky factorization and profile reordering in conjunction with envelope storage schemes are examined.},
    booktitle = {{{VII}}. {{Hotine}}-{{Marussi}}-{{Symposium}}, {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {Brockmann, J. M. and Kargoll, B.},
    editor = {Sneeuw, Nico and Nov{\'a}k, Pavel and Crespi, Mattia and Sans{\`o}, Fernando},
    year = {2012},
    pages = {87-92},
    owner = {swd},
    note = {2012}
    }

  • A. Ernst and W. -D. Schuh, “The Effect of Reordering Strategies on Rounding Errors in Large, Sparse Equation Systems,” in VII. Hotine-Marussi-Symposium, IAG Symposia, N. Sneeuw, P. Novák, M. Crespi, and F. Sansò, Eds., Berlin – Heidelberg: {Springer}, 2012, vol. 137, pp. 99-104.
    [BibTeX]
    @incollection{ernst-schuh_12,
    address = {Berlin - Heidelberg},
    series = {Lecture Notes in Earth Sciences},
    title = {The Effect of Reordering Strategies on Rounding Errors in Large, Sparse Equation Systems},
    volume = {137},
    booktitle = {{{VII}}. {{Hotine}}-{{Marussi}}-{{Symposium}}, {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {Ernst, A. and Schuh, W.-D.},
    editor = {Sneeuw, Nico and Nov{\'a}k, Pavel and Crespi, Mattia and Sans{\`o}, Fernando},
    year = {2012},
    pages = {99-104},
    owner = {swd}
    }

  • K. R. Koch, J. M. Brockmann, and W. -D. Schuh, “Optimal Regularization for Geopotential Model GOCO02S by Monte Carlo Methods and Multi-Scale Representation of Density Anomalies,” Journal of Geodesy, vol. 86, pp. 647-660, 2012. doi:10.1007/s00190-012-0546-7
    [BibTeX]
    @article{koch-etal_12,
    title = {Optimal Regularization for Geopotential Model {{GOCO02S}} by {{Monte Carlo}} Methods and Multi-Scale Representation of Density Anomalies},
    volume = {86},
    doi = {10.1007/s00190-012-0546-7},
    journal = {Journal of Geodesy},
    author = {Koch, K.R. and Brockmann, J. M. and Schuh, W.-D.},
    year = {2012},
    pages = {647-660},
    owner = {swd}
    }

  • L. Roese-Koerner, I. Krasbutter, and W. -D. Schuh, “A Constrained Quadratic Programming Technique for Data-Adaptive Design of Decorrelation Filters,” in VII. Hotine-Marussi-Symposium, IAG Symposia, N. Sneeuw, P. Novák, M. Crespi, and F. Sansò, Eds., Berlin – Heidelberg: {Springer}, 2012, vol. 137, pp. 165-170.
    [BibTeX] [Abstract]

    Signals from sensors with high sampling rates are often highly correlated. For the decorrelation of such data, which is often applied for the efficient estimation of parametric data models, discrete filters have proven to be both highly flexible and numerically efficient. Standard filter techniques are, however, often not suitable for eliminating strong local fluctuations or trends present in the noise spectral density. Therefore we propose a constrained least-squares filter design method. The spectral features to be filtered out are specified through inequality constraints regarding the noise spectral density. To solve for the optimal filter parameters under such inequality constraints, we review and apply the Active Set Method, a quadratic programming technique. Results are validated by statistical tests. The proposed filter design algorithm is applied to GOCE gradiometer signals to analyze its numerical behaviour and efficiency for a realistic and complex application.

    @incollection{roese-koerner-etal_12,
    address = {Berlin - Heidelberg},
    series = {Lecture Notes in Earth Sciences},
    title = {A Constrained Quadratic Programming Technique for Data-Adaptive Design of Decorrelation Filters},
    volume = {137},
    abstract = {Signals from sensors with high sampling rates are often highly correlated. For the decorrelation of such data, which is often applied for the efficient estimation of parametric data models, discrete filters have proven to be both highly flexible and numerically efficient. Standard filter techniques are, however, often not suitable for eliminating strong local fluctuations or trends present in the noise spectral density. Therefore we propose a constrained least-squares filter design method. The spectral features to be filtered out are specified through inequality constraints regarding the noise spectral density. To solve for the optimal filter parameters under such inequality constraints, we review and apply the Active Set Method, a quadratic programming technique. Results are validated by statistical tests. The proposed filter design algorithm is applied to GOCE gradiometer signals to analyze its numerical behaviour and efficiency for a realistic and complex application.},
    booktitle = {{{VII}}. {{Hotine}}-{{Marussi}}-{{Symposium}}, {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {Roese-Koerner, L. and Krasbutter, I. and Schuh, W.-D.},
    editor = {Sneeuw, Nico and Nov{\'a}k, Pavel and Crespi, Mattia and Sans{\`o}, Fernando},
    year = {2012},
    keywords = {-,adjustment,decorrelation,Active,constraints,Filter,inequality,Method,Set,with},
    pages = {165-170},
    owner = {swd},
    note = {roese-koerner-etal\textsubscript{1}2}
    }

  • L. Roese-Koerner, B. Devaraju, N. Sneeuw, and W. Schuh, “A Stochastic Framework for Inequality Constrained Estimation,” Journal of Geodesy, vol. 86, pp. 1005-1018, 2012. doi:10.1007/s00190-012-0560-9
    [BibTeX]
    @article{roese-koerner-etal_12a,
    title = {A Stochastic Framework for Inequality Constrained Estimation},
    volume = {86},
    doi = {10.1007/s00190-012-0560-9},
    journal = {Journal of Geodesy},
    author = {Roese-Koerner, Lutz and Devaraju, Balaji and Sneeuw, Nico and Schuh, Wolf-Dieter},
    month = nov,
    year = {2012},
    pages = {1005 -1018},
    owner = {swd},
    note = {roese-koerner-etal\textsubscript{1}2a}
    }

  • C. Siemes, “Digital Filtering Algorithms for Decorrelation within Large Least Squares Problems.,” in Schriftenreihe Des Instituts Für Geodäsie Und Geoinformation, Bonn: {Rheinischen Friedrich-Wilhelms-Universität Bonn}, 2012, vol. 32.
    [BibTeX] [Download PDF]
    @incollection{siemes:12,
    address = {Bonn},
    title = {Digital {{Filtering Algorithms}} for {{Decorrelation}} within {{Large Least Squares Problems}}.},
    volume = {32},
    url = {http://nbn-resolving.de/urn:nbn:de:hbz:5N-13749},
    booktitle = {Schriftenreihe Des {{Instituts}} F{\"u}r {{Geod{\"a}sie}} Und {{Geoinformation}}},
    publisher = {{Rheinischen Friedrich-Wilhelms-Universit{\"a}t Bonn}},
    author = {Siemes, Ch.},
    year = {2012},
    owner = {schuh}
    }

2011

  • J. Brockmann and W. -D. Schuh, “Use of Massive Parallel Computing Libraries in the Context of Global Gravity Field Determination from Satellite Data,” in Proceedings of the 4th International GOCE User Workshop, L. Ouwehand, Ed., {ESA Publication SP-696, ESA/ESTEC, ISBN (Online) 978-92-9092-260-5, ISSN 1609-042X}, 2011.
    [BibTeX]
    @incollection{brockmann-schuh_11,
    title = {Use of {{Massive Parallel Computing Libraries}} in the {{Context}} of {{Global Gravity Field Determination}} from {{Satellite Data}}},
    booktitle = {Proceedings of the 4th International {{GOCE User Workshop}}},
    publisher = {{ESA Publication SP-696, ESA/ESTEC, ISBN (Online) 978-92-9092-260-5, ISSN 1609-042X}},
    author = {Brockmann, J. and Schuh, W.-D.},
    editor = {Ouwehand, L.},
    year = {2011},
    owner = {swd},
    note = {brockmann-schuh\textsubscript{1}1}
    }

  • K. R. Koch and M. Schmidt, “N-Dimensional B-Spline Surface Estimated by Lofting for Locally Improving IRI,” J Geodetic Science, vol. 1, iss. 1, pp. 41-51, 2011. doi:10.2478/v10156-010-0006-3
    [BibTeX]
    @article{koch-schmidt:11,
    title = {N-Dimensional {{B}}-Spline Surface Estimated by Lofting for Locally Improving {{IRI}}},
    volume = {1},
    doi = {10.2478/v10156-010-0006-3},
    number = {1},
    journal = {J Geodetic Science},
    author = {Koch, K.R. and Schmidt, M.},
    year = {2011},
    pages = {41-51},
    owner = {swd}
    }

  • K. R. Koch, “Data Compression by Multi-Scale Representation of Signals,” J Applied Geodesy, vol. 5, pp. 1-12, 2011. doi:10.1515/JAG.2011.001
    [BibTeX]
    @article{koch:11,
    title = {Data Compression by Multi-Scale Representation of Signals},
    volume = {5},
    doi = {10.1515/JAG.2011.001},
    journal = {J Applied Geodesy},
    author = {Koch, K.R.},
    year = {2011},
    pages = {1-12},
    owner = {swd}
    }

  • K. R. Koch, “Digital Images with 3D Geometry from Data Compession by Multi-Scale Representations of B-Spline Surfaces,” Journal of Geodetic Science, vol. 1, iss. 3, pp. 240-250, 2011. doi:10.2478/v10156-011-0002-2
    [BibTeX]
    @article{koch:11c,
    title = {Digital {{Images}} with {{3D Geometry}} from {{Data Compession}} by {{Multi}}-Scale {{Representations}} of {{B}}-{{Spline Surfaces}}},
    volume = {1},
    doi = {10.2478/v10156-011-0002-2},
    number = {3},
    journal = {Journal of Geodetic Science},
    author = {Koch, K.R.},
    year = {2011},
    pages = {240-250},
    owner = {swd}
    }

  • K. R. Koch, “Thresholds for Data Compression by Multi-Scale Representation of Signals,” Allgemeine Vermessungs-Nachrichten, vol. 118, pp. 293-301, 2011.
    [BibTeX]
    @article{koch:11b,
    title = {Thresholds for {{Data Compression}} by Multi-Scale {{Representation}} of {{Signals}}},
    volume = {118},
    journal = {Allgemeine Vermessungs-Nachrichten},
    author = {Koch, K.R.},
    year = {2011},
    pages = {293-301},
    owner = {swd}
    }

  • I. Krasbutter, J. M. Brockmann, H. Goiginger, B. Kargoll, R. Pail, and W. -D. Schuh, “Refinement of the Stochastic Model of GOCE Scientific Data in along Time Series,” in Proceedings of the 4th International GOCE User Workshop, 2011.
    [BibTeX]
    @inproceedings{krasbutter-etal_11,
    title = {Refinement of the Stochastic Model of {{GOCE}} Scientific Data in along Time Series},
    booktitle = {Proceedings of the 4th International {{GOCE User Workshop}}},
    publisher = {{ESA Publication SP-696, ESA/ESTEC, ISBN (Online) 978-92-9092-260-5, ISSN 1609-042X}},
    author = {Krasbutter, I. and Brockmann, J. M. and Goiginger, H. and Kargoll, B. and Pail, R. and Schuh, W.-D.},
    editor = {Ouwehand, L.},
    year = {2011},
    owner = {swd},
    note = {krasbutter-etal\textsubscript{1}1}
    }

  • R. Pail, S. Bruinsma, F. Miggliaccio, C. Förste, H. Goiginger, W. -D. Schuh, E. Höck, M. Reguzzoni, J. Brockmann, O. Abrikosov, M. Veicherts, T. Fecher, R. Mayrhofer, I. Krasbutter, F. Sansó, and C. C. Tscherning, “First GOCE Gravity Field Models Derived by Three Different Approaches,” J Geodesy, vol. 85, iss. 11, pp. 819-843, 2011. doi:10.1007/s00190-011-0467-x
    [BibTeX]
    @article{pail-etal_11a,
    title = {First {{GOCE}} Gravity Field Models Derived by Three Different Approaches},
    volume = {85},
    doi = {10.1007/s00190-011-0467-x},
    number = {11},
    journal = {J Geodesy},
    author = {Pail, R. and Bruinsma, S. and Miggliaccio, F. and F{\"o}rste, C. and Goiginger, H. and Schuh, W.-D. and H{\"o}ck, E. and Reguzzoni, M. and Brockmann, J. and Abrikosov, O. and Veicherts, M. and Fecher, T. and Mayrhofer, R. and Krasbutter, I. and Sans{\'o}, F. and Tscherning, C. C.},
    year = {2011},
    pages = {819 - 843},
    owner = {swd}
    }

  • R. Pail, H. Goiginger, W. -D. Schuh, E. Höck, J. M. Brockmann, T. Fecher, T. Mayer-Gürr, J. Kusche, A. Jäggi, D. Rieser, W. Hausleitner, A. Maier, S. Krauss, O. Baur, I. Krasbutter, and T. Gruber, “Combination of GOCE Data with Complementary Gravity Field Information,” in Proceedings of the 4th International GOCE User Workshop, 2011.
    [BibTeX]
    @inproceedings{pail-etal_11b,
    title = {Combination of {{GOCE}} Data with Complementary Gravity Field Information},
    booktitle = {Proceedings of the 4th International {{GOCE User Workshop}}},
    publisher = {{ESA Publication SP-696, ESA/ESTEC, ISBN (Online) 978-92-9092-260-5, ISSN 1609-042X}},
    author = {Pail, R. and Goiginger, H. and Schuh, W.-D. and H{\"o}ck, E. and Brockmann, J. M. and Fecher, T. and Mayer-G{\"u}rr, T. and Kusche, J. and J{\"a}ggi, A. and Rieser, D. and Hausleitner, W. and Maier, A. and Krauss, S. and Baur, O. and Krasbutter, I. and Gruber, T.},
    editor = {L, Ouwehand},
    year = {2011},
    owner = {swd}
    }

  • R. Pail, H. Goiginger, W. -D. Schuh, E. Höck, J. M. Brockmann, T. Fecher, R. Mayrhofer, I. Krasbutter, and T. Mayer-Gürr, “GOCE-Only Gravity Field Models Derived from 8 Months of GOCE Data,” in Proceedings of the 4th International GOCE User Workshop, 2011.
    [BibTeX] [Download PDF]
    @inproceedings{pail-etal_11c,
    title = {{{GOCE}}-Only Gravity Field Models Derived from 8 Months of {{GOCE}} Data},
    url = {http://www.spacebooks-online.com/product_info.php?cPath=104\&products_id=17254},
    booktitle = {Proceedings of the 4th International {{GOCE User Workshop}}},
    publisher = {{ESA Publication SP-696, ESA/ESTEC, ISBN (Online) 978-92-9092-260-5, ISSN 1609-042X}},
    author = {Pail, R. and Goiginger, H. and Schuh, W.-D. and H{\"o}ck, E. and Brockmann, J. M. and Fecher, T. and Mayrhofer, R. and Krasbutter, I. and Mayer-G{\"u}rr, T.},
    editor = {L, Ouwehand},
    year = {2011},
    owner = {swd}
    }

  • W. -D. Schuh and B. Kargoll, “On the Current Status of the Cooperative Research Project Real Data Analysis GOCE(REAL GOCE),” in Proceedings of the 4th International GOCE User Workshop, L. Ouwehand, Ed., {ESA Publication SP-696, ESA/ESTEC, ISBN (Online) 978-92-9092-260-5, ISSN 1609-042X}, 2011.
    [BibTeX]
    @incollection{schuh-kargoll_11,
    title = {On the {{Current Status}} of the {{Cooperative Research Project Real Data Analysis GOCE}}({{REAL GOCE}})},
    booktitle = {Proceedings of the 4th International {{GOCE User Workshop}}},
    publisher = {{ESA Publication SP-696, ESA/ESTEC, ISBN (Online) 978-92-9092-260-5, ISSN 1609-042X}},
    author = {Schuh, W.-D. and Kargoll, B.},
    editor = {Ouwehand, L.},
    year = {2011},
    owner = {swd}
    }

2010

  • J. M. Brockmann, B. Kargoll, I. Krasbutter, W. -D. Schuh, and M. Wermuth, “GOCE Data Analysis: From Calibrated Measurements to the Global Earth Gravity Field,” in System Earth via Geodetic-Geophysical Space Techniques, F. Flechtner, M. Mandea, T. Gruber, M. Rothacher, J. Wickert, and A. Güntner, Eds., Berlin: {Springer}, 2010, pp. 213-229.
    [BibTeX] [Download PDF]
    @incollection{brockmann-etal_10,
    address = {Berlin},
    title = {{{GOCE Data Analysis}}: {{From Calibrated Measurements}} to the {{Global Earth Gravity Field}}},
    url = {http://www.springer.com/gp/book/9783642102271\#},
    booktitle = {System {{Earth}} via {{Geodetic}}-{{Geophysical Space Techniques}}},
    publisher = {{Springer}},
    author = {Brockmann, J. M. and Kargoll, B. and Krasbutter, I. and Schuh, W.-D. and Wermuth, M.},
    editor = {Flechtner, F. and Mandea, M. and Gruber, T. and Rothacher, M. and Wickert, J. and G{\"u}ntner, A.},
    year = {2010},
    pages = {213 - 229},
    owner = {swd}
    }

  • G. Freiwald, M. Losch, W. -D. Schuh, and S. Becker, “RIFUGIO – Rigorous Fusion of Gravity Field into Stationary Ocean Models,” in ESA Living Planet Symposium Bergen, Proceedings, 2010.
    [BibTeX]
    @inproceedings{freiwald-etal_10,
    title = {{{RIFUGIO}} - Rigorous Fusion of Gravity Field into Stationary Ocean Models},
    booktitle = {{{ESA Living Planet Symposium Bergen}}, {{Proceedings}}},
    publisher = {{ESA-SP-686, ESA/ESTEC, ISBN (Online) 978-92-9221-250-6 ISSN 1609-042X}},
    author = {Freiwald, G. and Losch, M. and Schuh, W.-D. and Becker, S.},
    editor = {Lacsoste-Francis, H.},
    year = {2010},
    owner = {swd},
    note = {freiwald-etal\textsubscript{1}0}
    }

  • K. R. Koch, H. Kuhlmann, and W. -D. Schuh, “Approximating Covariance Matrices Estimated in Multivariate Models by Estimated Auto- and Cross-Covariances,” J. Geodesy, vol. 84, iss. 6, pp. 383-397, 2010. doi:10.1007/s00190-010-0375-5
    [BibTeX]
    @article{koch-etal_10,
    title = {Approximating Covariance Matrices Estimated in Multivariate Models by Estimated Auto- and Cross-Covariances},
    volume = {84},
    doi = {10.1007/s00190-010-0375-5},
    number = {6},
    journal = {J. Geodesy},
    author = {Koch, K.R. and Kuhlmann, H. and Schuh, W.-D.},
    year = {2010},
    pages = {383-397},
    owner = {swd},
    note = {koch-etal\textsubscript{1}0}
    }

  • K. R. Koch, “NURBS Surface with Changing Shape,” Allgemeine Vermessungs-Nachrichten, vol. 117, pp. 83-89, 2010.
    [BibTeX]
    @article{koch:10a,
    title = {{{NURBS}} Surface with Changing Shape},
    volume = {117},
    journal = {Allgemeine Vermessungs-Nachrichten},
    author = {Koch, K.R.},
    year = {2010},
    pages = {83-89},
    owner = {swd}
    }

  • K. R. Koch, “Three-Dimensional NURBS Surface Estimated by Lofting Method,” Int J Advanced Manufacturing Technology, vol. 49, pp. 1059-1068, 2010. doi:DOI\%002010.1007/s00170-009-2460-6
    [BibTeX]
    @article{koch:10,
    title = {Three-Dimensional {{NURBS}} Surface Estimated by Lofting Method},
    volume = {49},
    doi = {DOI\%002010.1007/s00170-009-2460-6},
    journal = {Int J Advanced Manufacturing Technology},
    author = {Koch, K.R.},
    year = {2010},
    pages = {1059-1068},
    owner = {swd}
    }

  • K. R. Koch, “Uncertainty of Results of Laser Scanning Data with Correlated Systematic Effects by Monte Carlo Methods,” ZfV–Z Geodäsie, Geoinformation und Landmanagement, vol. 135, pp. 376-385, 2010.
    [BibTeX]
    @article{koch:10b,
    title = {Uncertainty of Results of Laser Scanning Data with Correlated Systematic Effects by {{Monte Carlo}} Methods},
    volume = {135},
    journal = {ZfV--Z Geod{\"a}sie, Geoinformation und Landmanagement},
    author = {Koch, K.R.},
    year = {2010},
    pages = {376-385},
    owner = {swd}
    }

  • I. Krasbutter, J. M. Brockmann, B. Kargoll, and W. -D. Schuh, “Stochastic Model Refinements for GOCE Gradiometry Data,” BMBF Geotechnologien Science Report, vol. 17, pp. 70-76, 2010.
    [BibTeX]
    @article{krasbutter-etal_10,
    title = {Stochastic Model Refinements for {{GOCE}} Gradiometry Data},
    volume = {17},
    journal = {BMBF Geotechnologien Science Report},
    author = {Krasbutter, I. and Brockmann, J. M. and Kargoll, B. and Schuh, W.-D.},
    year = {2010},
    pages = {70-76},
    owner = {swd}
    }

  • R. Pail, H. Goiginger, R. Mayerhofer, W. -D. Schuh, J. M. Brockmann, I. Krasbutter, E. Höck, and T. Fecher, “GOCE Gravity Field Model Derived from Orbit and Gradiometry Data Applying the Time-Wise Approach,” in ESA Living Planet Symposium Bergen, Proceedings, 2010.
    [BibTeX]
    @inproceedings{pail-etal_10a,
    title = {{{GOCE}} Gravity Field Model Derived from Orbit and Gradiometry Data Applying the Time-Wise Approach},
    booktitle = {{{ESA Living Planet Symposium Bergen}}, {{Proceedings}}},
    publisher = {{ESA-SP-686, ESA/ESTEC, ISBN (Online) 978-92-9221-250-6 ISSN 1609-042X}},
    author = {Pail, R. and Goiginger, H. and Mayerhofer, R. and Schuh, W.-D. and Brockmann, J. M. and Krasbutter, I. and H{\"o}ck, E. and Fecher, T.},
    editor = {Lacoste-Francis, H.},
    year = {2010},
    owner = {swd}
    }

  • R. Pail, H. Goiginger, W. -D. Schuh, E. Höck, J. M. Brockmann, T. Fecher, and T. Gruber, “Combined Satellite Gravity Field Model GOCO01S Derived from GOCE and GRACE,” Geophys. Res. Lett., vol. 37, p. L20314, 2010. doi:10.1029/2010GL044906
    [BibTeX]
    @article{pail-etal_10b,
    title = {Combined Satellite Gravity Field Model {{GOCO01S}} Derived from {{GOCE}} and {{GRACE}}},
    volume = {37},
    doi = {10.1029/2010GL044906},
    journal = {Geophys. Res. Lett.},
    author = {Pail, R. and Goiginger, H. and Schuh, W.-D. and H{\"o}ck, E. and Brockmann, J. M. and Fecher, T. and Gruber, T.},
    year = {2010},
    pages = {L20314},
    owner = {swd}
    }

  • W. -D. Schuh and S. Becker, “Potential Field and Smoothness Conditions,” in The Apple of Knowledge – In Honour of Prof. N. Arabelos, 2010, pp. 237-250.
    [BibTeX]
    @inproceedings{schuh-becker_10,
    title = {Potential Field and Smoothness Conditions},
    booktitle = {The Apple of Knowledge - {{In}} Honour of {{Prof}}. {{N}}. {{Arabelos}}},
    publisher = {{AUTH - Faculty of rural and surveying engineering}},
    author = {Schuh, W.-D. and Becker, S.},
    editor = {Contadakis, M.E. and Kaltsikis, C. and Spatalas, S. and Tokmakidis, K. and Tziavos, I.N.},
    year = {2010},
    pages = {237 - 250},
    owner = {swd},
    note = {ISBN 978-960-243-674-5 schuh-becker\textsubscript{1}0}
    }

  • W. -D. Schuh, J. M. Brockmann, B. Kargoll, and I. Krasbutter, “Adaptive Optimization of GOCE Gravity Field Modeling,” in NIC Symposium, Proceedings, G. Münster, D. Wolf, and M. Kremer, Eds., {Schriftenreihe des Forschungszentrums Jülich}, 2010, vol. 3, pp. 313-320.
    [BibTeX]
    @incollection{schuh-etal_10a,
    series = {IAS Series},
    title = {Adaptive {{Optimization}} of {{GOCE Gravity Field Modeling}}},
    volume = {3},
    booktitle = {{{NIC Symposium}}, {{Proceedings}}},
    publisher = {{Schriftenreihe des Forschungszentrums J{\"u}lich}},
    author = {Schuh, W.-D. and Brockmann, J. M. and Kargoll, B. and Krasbutter, I.},
    editor = {M{\"u}nster, G. and Wolf, D. and Kremer, M.},
    year = {2010},
    pages = {313 - 320},
    owner = {swd},
    note = {schuh-etal\textsubscript{1}0a}
    }

  • W. -D. Schuh, J. M. Brockmann, I. Krasbutter, and R. Pail, “Refinement of the Stochastic Model of GOCE Scientific Data and Its Effect on the In-Situ Gravity Field Solution,” in ESA Living Planet Symposium Bergen, Proceedings, 2010.
    [BibTeX]
    @inproceedings{schuh-etal_10b,
    title = {Refinement of the Stochastic Model of {{GOCE}} Scientific Data and Its Effect on the In-Situ Gravity Field Solution},
    booktitle = {{{ESA Living Planet Symposium Bergen}}, {{Proceedings}}},
    publisher = {{ESA-SP-686, ESA/ESTEC, ISBN (Online) 978-92-9221-250-6 ISSN 1609-042X}},
    author = {Schuh, W.-D. and Brockmann, J. M. and Krasbutter, I. and Pail, R.},
    editor = {Lacoste-Francis, H.},
    year = {2010},
    owner = {swd},
    note = {schuh-etal\textsubscript{1}0b}
    }

  • J. M. Brockmann and W. -D. Schuh, “Fast Variance Component Estimation in GOCE Data Processing,” in Gravity, Geoid and Earth Observation, S. P. Mertikas, Ed., {Springer Berlin Heidelberg}, 2010, pp. 185-193. doi:10.1007/978-3-642-10634-7_25
    [BibTeX] [Abstract] [Download PDF]

    For the processing of GOCE (Gravity Field and steady-state Ocean Circulation Explorer) data the program system pcgma (Preconditioned Conjugate Gradient Multiple Adjustment) was designed as a tailored solution strategy for the determination of the Earth’s gravity field in terms of a spherical harmonic analysis. Within GOCE-HPF (High Level Processing Facility) the pcgma algorithm works with the purpose of a tuning machine in that it is used to optimize the filter design and to determine optimal variance components with respect to the combination of satellite-to-satellite tracking (sst) data, satellite gravity gradiometry (sgg) data and additional prior information about the smoothness of the gravity field (the latter especially with regard to the polar regions). pcgma is based on an extended version of the iterative conjugate gradient (CG) algorithm, which allows for data combination in terms of observation and normal equations. A basic prerequisite for handling the nesting of the two iterative methods (variance component estimation (VCE) and parameter estimation using CG) is an efficient and fast implementation, because the VCE requires a repeated solution of the system. In this paper we will show how the nesting can be organized in an optimal way. We will concentrate on the reduction of CG iteration steps.

    @incollection{brockmann.schuh_2010a,
    series = {International Association of Geodesy Symposia},
    title = {Fast {{Variance Component Estimation}} in {{GOCE Data Processing}}},
    copyright = {\textcopyright{}2010 Springer-Verlag Berlin Heidelberg},
    isbn = {978-3-642-10633-0 978-3-642-10634-7},
    abstract = {For the processing of GOCE (Gravity Field and steady-state Ocean Circulation Explorer) data the program system pcgma (Preconditioned Conjugate Gradient Multiple Adjustment) was designed as a tailored solution strategy for the determination of the Earth's gravity field in terms of a spherical harmonic analysis. Within GOCE-HPF (High Level Processing Facility) the pcgma algorithm works with the purpose of a tuning machine in that it is used to optimize the filter design and to determine optimal variance components with respect to the combination of satellite-to-satellite tracking (sst) data, satellite gravity gradiometry (sgg) data and additional prior information about the smoothness of the gravity field (the latter especially with regard to the polar regions). pcgma is based on an extended version of the iterative conjugate gradient (CG) algorithm, which allows for data combination in terms of observation and normal equations. A basic prerequisite for handling the nesting of the two iterative methods (variance component estimation (VCE) and parameter estimation using CG) is an efficient and fast implementation, because the VCE requires a repeated solution of the system. In this paper we will show how the nesting can be organized in an optimal way. We will concentrate on the reduction of CG iteration steps.},
    language = {en},
    number = {135},
    urldate = {2017-01-03},
    url = {http://link.springer.com/chapter/10.1007/978-3-642-10634-7_25},
    booktitle = {Gravity, {{Geoid}} and {{Earth Observation}}},
    publisher = {{Springer Berlin Heidelberg}},
    author = {Brockmann, J. M. and Schuh, W.-D.},
    editor = {Mertikas, Stelios P.},
    year = {2010},
    keywords = {Geophysics/Geodesy,Earth Sciences; general,Earth,and,Environmental,Science,Geotechnical Engineering \& Applied Earth Sciences},
    pages = {185-193},
    file = {/home/jmb/pc/internetSettings/zotero/storage/VVS8DXP2/brockmann-schuh_2008.pdf},
    doi = {10.1007/978-3-642-10634-7_25}
    }

2009

  • A. M. Bauer, F. Hoti, T. C. Reetz, W. -D. Schuh, J. Léon, and M. J. Sillanpää, “Bayesian Prediction of Breeding Values by Accounting for Genotype-by-Environment Interaction in Self-Pollinating Crops,” Genetical Research, vol. 91, pp. 193-207, 2009. doi:10.1017/S0016672309000160
    [BibTeX]
    @article{bauer-etal_09,
    title = {Bayesian Prediction of Breeding Values by Accounting for Genotype-by-Environment Interaction in Self-Pollinating Crops},
    volume = {91},
    doi = {10.1017/S0016672309000160},
    journal = {Genetical Research},
    author = {Bauer, A.M. and Hoti, F. and Reetz, T.C. and Schuh, W.-D. and L{\'e}on, J. and Sillanp{\"a}{\"a}, M.J.},
    year = {2009},
    pages = {193-207},
    owner = {swd}
    }

  • J. M. Brockmann, B. Kargoll, I. Krasbutter, W. -D. Schuh, and M. Wermuth, “GOCE Data Analysis: From Calibrated Measurements to the Global Earth Gravity Field Observation of the Earth System from Space,” Springer (accepted), 2009.
    [BibTeX]
    @article{brockmann-etal:09,
    title = {{{GOCE Data Analysis}}: {{From Calibrated Measurements}} to the {{Global Earth Gravity Field Observation}} of the {{Earth System}} from {{Space}}},
    journal = {Springer (accepted)},
    author = {Brockmann, J.M. and Kargoll, B. and Krasbutter, I. and Schuh, W.-D. and Wermuth, M.},
    year = {2009},
    owner = {swd}
    }

  • A. Ernst, “Implementierung Effizienter Algorithmen Zur Umordnung, Auflösung Und Inversion von Dünn Besetzten Normalgleichungen Mit Geodätischen Anwendungen,” Master Thesis, 2009.
    [BibTeX]
    @mastersthesis{ernst:09,
    title = {Implementierung Effizienter {{Algorithmen}} Zur {{Umordnung}}, {{Aufl{\"o}sung}} Und {{Inversion}} von D{\"u}nn Besetzten {{Normalgleichungen}} Mit Geod{\"a}tischen {{Anwendungen}}},
    school = {Institut f{\"u}r Geod{\"a}sie und Geoinformation, Professur f{\"u}r Theoretische Geod{\"a}sie},
    author = {Ernst, A.},
    year = {2009},
    owner = {schuh}
    }

  • K. R. Koch and H. Kuhlmann, “The Impact of Correcting Measurements of Laserscanners on the Uncertainty of Derived Results,” ZfV–Z Geodäsie, Geoinformation und Landmanagement, vol. 134, pp. 38-44, 2009.
    [BibTeX] [Download PDF]
    @article{koch-kuhlmann_09,
    title = {The Impact of Correcting Measurements of Laserscanners on the Uncertainty of Derived Results},
    volume = {134},
    url = {http://www.geodaesie.info/sites/default/files/privat/zfv_2009_1_Koch_Kuhlmann.pdf},
    journal = {ZfV--Z Geod{\"a}sie, Geoinformation und Landmanagement},
    author = {Koch, K.R. and Kuhlmann, H.},
    year = {2009},
    pages = {38-44},
    owner = {swd}
    }

  • K. R. Koch, “Fitting Free-Form Surfaces to Laserscan Data by NURBS,” Allgemeine Vermessungs-Nachrichten, vol. 116, pp. 134-140, 2009.
    [BibTeX]
    @article{koch:09a,
    title = {Fitting Free-Form Surfaces to Laserscan Data by {{NURBS}}},
    volume = {116},
    journal = {Allgemeine Vermessungs-Nachrichten},
    author = {Koch, K.R.},
    year = {2009},
    pages = {134-140},
    owner = {swd}
    }

  • K. R. Koch, “Identity of Simultaneous Estimates of Control Points and of Their Estimates by the Lofting Method for NURBS Surface Fitting,” Int J Advanced Manufacturing Technology, vol. 44, pp. 1175-1180, 2009. doi:10.1007/s00170-009-1934-x
    [BibTeX]
    @article{koch:09,
    title = {Identity of Simultaneous Estimates of Control Points and of Their Estimates by the Lofting Method for {{NURBS}} Surface Fitting},
    volume = {44},
    doi = {10.1007/s00170-009-1934-x},
    journal = {Int J Advanced Manufacturing Technology},
    author = {Koch, K.R.},
    year = {2009},
    pages = {1175-1180},
    owner = {swd}
    }

  • K. R. Koch, “Uncertainty of NURBS Surface Fit by Monte Carlo Simulations,” Journal of Applied Geodesy, vol. 3, iss. 4, pp. 249-258, 2009.
    [BibTeX]
    @article{koch:09b,
    title = {Uncertainty of {{NURBS}} Surface Fit by {{Monte Carlo}} Simulations},
    volume = {3},
    number = {4},
    journal = {Journal of Applied Geodesy},
    author = {Koch, K.R.},
    year = {2009},
    pages = {249-258},
    owner = {swd}
    }

  • I. Krasbutter, “Dekorrelation Und Daten TÜV Der GOCE-Residuen,” Diplomathesis PhD Thesis, 2009.
    [BibTeX]
    @phdthesis{krasbutter_09,
    type = {Diplomathesis},
    title = {Dekorrelation Und {{Daten T{\"U}V}} Der {{GOCE}}-{{Residuen}}},
    school = {Universit{\"a}t Bonn, Institut f{\"u}r Geod{\"a}sie und Geoinformation},
    author = {Krasbutter, Ina},
    year = {2009},
    owner = {swd}
    }

  • L. Roese-Koerner, “Quadratische Programmierung Mit Ungleichungen Als Restriktionen,” Diplomathesis PhD Thesis, 2009.
    [BibTeX]
    @phdthesis{roese-koerner:09,
    type = {Diplomathesis},
    title = {Quadratische {{Programmierung}} Mit {{Ungleichungen}} Als {{Restriktionen}}},
    school = {Institut f{\"u}r Geod{\"a}sie und Geoinformation, Professur f{\"u}r Theoretische Geod{\"a}sie},
    author = {Roese-Koerner, L.},
    year = {2009},
    owner = {schuh}
    }

2008

  • J. Brockmann, “Effiziente Varianzkomponentenschätzung Über Iterative Techniken Bei Der GOCE-Daten Prozessierung,” Diplomarbeit PhD Thesis, 2008.
    [BibTeX]
    @phdthesis{brockmann:08,
    type = {Diplomarbeit},
    title = {Effiziente {{Varianzkomponentensch{\"a}tzung}} {\"U}ber Iterative {{Techniken}} Bei Der {{GOCE}}-{{Daten Prozessierung}}},
    school = {Professur f{\"u}r Theoretische Geod{\"a}sie, Universit{\"a}t Bonn},
    author = {Brockmann, J.},
    year = {2008},
    owner = {swd}
    }

  • K. R. Koch, “Determining Uncertainties of Correlated Measurements by Monte Carlo Simulations Applied to Laserscanning,” Journal of Applied Geodesy, vol. 2, pp. 139-147, 2008. doi:10.1515/JAG.2008.016
    [BibTeX]
    @article{koch:08a,
    title = {Determining Uncertainties of Correlated Measurements by {{Monte Carlo}} Simulations Applied to Laserscanning},
    volume = {2},
    doi = {10.1515/JAG.2008.016},
    journal = {Journal of Applied Geodesy},
    author = {Koch, K.R.},
    year = {2008},
    pages = {139-147},
    owner = {schuh}
    }

  • K. R. Koch, “Evaluation of Uncertainties in Measurements by Monte Carlo Simulations with an Application for Laserscanning,” J Applied Geodesy, vol. 2, pp. 67-77, 2008.
    [BibTeX]
    @article{koch:08c,
    title = {Evaluation of Uncertainties in Measurements by {{Monte Carlo}} Simulations with an Application for Laserscanning},
    volume = {2},
    journal = {J Applied Geodesy},
    author = {Koch, K.R.},
    year = {2008},
    pages = {67-77},
    owner = {swd}
    }

  • W. -D. Schuh, “Geodäsie –- Mathematik Zum Angreifen,” in Universalgeodäsie in Graz, 2008, pp. 162-166.
    [BibTeX]
    @inproceedings{schuh_08,
    title = {Geod{\"a}sie --- {{Mathematik}} Zum {{Angreifen}}},
    booktitle = {Universalgeod{\"a}sie in {{Graz}}},
    publisher = {{Verlag der Technischen Universit{\"a}t Graz}},
    author = {Schuh, W.-D.},
    editor = {Hofmann-Wellenhof, B.},
    year = {2008},
    pages = {162-166},
    owner = {swd},
    note = {schuh\textsubscript{0}8}
    }

  • C. Siemes, “Digital Filtering Algorithms for Decorrelation within Large Least Squares Problems.,” PhD Thesis, Bonn, 2008.
    [BibTeX] [Download PDF]
    @phdthesis{siemes_08,
    address = {Bonn},
    title = {Digital {{Filtering Algorithms}} for {{Decorrelation}} within {{Large Least Squares Problems}}.},
    url = {http://nbn-resolving.de/urn:nbn:de:hbz:5N-13749},
    school = {Rheinischen Friedrich-Wilhelms-Universit{\"a}t Bonn},
    author = {Siemes, Ch.},
    year = {2008},
    owner = {schuh},
    note = {siemes\textsubscript{0}8}
    }

2007

  • H. Alkhatib and W. -D. Schuh, “Integration of the Monte Carlo Covariance Estimation Strategy into Tailored Solution Procedures for Large-Scaled Least Squares Problems,” Journal of Geodesy, vol. 70, p. 53-66, DOI: 10.1007/s00190-006-0034-z, 2007. doi:10.1007/s00190-006-0034-z
    [BibTeX]
    @article{alkhatib-schuh:07,
    title = {Integration of the {{Monte Carlo}} Covariance Estimation Strategy into Tailored Solution Procedures for Large-Scaled Least Squares Problems},
    volume = {70},
    doi = {10.1007/s00190-006-0034-z},
    journal = {Journal of Geodesy},
    author = {Alkhatib, H. and Schuh, W.-D.},
    year = {2007},
    keywords = {Covariance estimation,GOCE gravity field processing,MonteCarlo integration,variance propagation,inverse problems},
    pages = {53-66, DOI: 10.1007/s00190-006-0034-z},
    owner = {swd}
    }

  • H. Alkhatib, “On Monte Carlo Methods with Applications to the Current Satellite Gravity Missions,” PhD Thesis, 2007.
    [BibTeX] [Download PDF]
    @phdthesis{alkhatib:07,
    title = {On {{Monte Carlo}} Methods with Applications to the Current Satellite Gravity Missions},
    url = {http://nbn-resolving.de/urn:nbn:de:hbz:5N-10783},
    school = {Promotion an der Landwirtschaftlichen Fakult{\"a}t der Universit{\"a}t Bonn, Schriftenreihe des Instituts f{\"u}r Geod{\"a}sie und Geoinformation der Rheinischen Friedrich-Wilhelms-Universit{\"a}t, Folge 7},
    author = {Alkhatib, H.},
    year = {2007},
    owner = {schuh}
    }

  • B. Kargoll, “On the Theory and Application of Model Misspecification Tests in Geodesy,” PhD Thesis, 2007.
    [BibTeX] [Download PDF]
    @phdthesis{kargoll:07,
    title = {On the {{Theory}} and {{Application}} of {{Model Misspecification Tests}} in {{Geodesy}}},
    url = {http://nbn-resolving.de/urn:nbn:de:hbz:5N-11136},
    school = {Promotion an der Landwirtschaftlichen Fakult{\"a}t der Universit{\"a}t Bonn, Schriftenreihe des Instituts f{\"u}r Geod{\"a}sie und Geoinformation der Rheinischen Friedrich-Wilhelms-Universit{\"a}t, Folge 8},
    author = {Kargoll, B.},
    year = {2007},
    owner = {schuh}
    }

  • K. Koch and J. Kusche, “Comments on Xu et~Al. (2006) Variance Component Estimation in Linear Inverse Ill-Posed Models, J Geod 80(1):69-81,” Journal of Geodesy, vol. 81, iss. 9, pp. 629-631, 2007. doi:10.1007/s00190-007-0163-z
    [BibTeX] [Download PDF]
    @article{koch_kusche:07,
    title = {Comments on {{Xu}} et~Al. (2006) {{Variance}} Component Estimation in Linear Inverse Ill-Posed Models, {{J Geod}} 80(1):69-81},
    volume = {81},
    issn = {0949-7714},
    doi = {10.1007/s00190-007-0163-z},
    number = {9},
    url = {http://dx.doi.org/10.1007/s00190-007-0163-z},
    journal = {Journal of Geodesy},
    author = {Koch, K. and Kusche, J.},
    year = {2007},
    keywords = {Geo-,Umweltwissenschaften,und},
    pages = {629-631},
    affiliation = {University of Bonn Institute for Theoretical Geodesy Nussallee 17 53115 Bonn Germany},
    owner = {swd}
    }

  • K. Koch, “Gibbs Sampler by Sampling-Importance-Resampling,” Journal of Geodesy, vol. 81, iss. 9, pp. 581-591, 2007. doi:10.1007/s00190-006-0121-1
    [BibTeX] [Abstract] [Download PDF]

    Among the Markov chain Monte Carlo methods, the Gibbs sampler has the advantage that it samples from the conditional distributions for each unknown parameter, thus decomposing the sample space. In the case the conditional distributions are not tractable, the Gibbs sampler by means of sampling-importance-resampling is presented here. It uses the prior density function of a Bayesian analysis as the importance sampling distribution. This leads to a fast convergence of the Gibbs sampler as demonstrated by the smoothing with preserving the edges of 3D images of emission tomography.

    @article{koch:07,
    title = {Gibbs Sampler by Sampling-Importance-Resampling},
    volume = {81},
    issn = {0949-7714},
    doi = {10.1007/s00190-006-0121-1},
    abstract = {Among the Markov chain Monte Carlo methods, the Gibbs sampler has the advantage that it samples from the conditional distributions for each unknown parameter, thus decomposing the sample space. In the case the conditional distributions are not tractable, the Gibbs sampler by means of sampling-importance-resampling is presented here. It uses the prior density function of a Bayesian analysis as the importance sampling distribution. This leads to a fast convergence of the Gibbs sampler as demonstrated by the smoothing with preserving the edges of 3D images of emission tomography.},
    number = {9},
    url = {http://dx.doi.org/10.1007/s00190-006-0121-1},
    journal = {Journal of Geodesy},
    author = {Koch, K.},
    year = {2007},
    keywords = {Geo-,Umweltwissenschaften,und},
    pages = {581-591},
    affiliation = {University of Bonn Institute for Theoretical Geodesy Nussallee 17 53115 Bonn Germany},
    owner = {swd}
    }

  • K. R. Koch and J. Kusche, “Comments on XU et Al (2006). Variance Component Estimation in Linear Inverse Ill-Posed Models,” J.~Geodesy, vol. 80, pp. 69-81, 2007.
    [BibTeX]
    @article{koch-kusche:07,
    title = {Comments on {{XU}} et Al (2006). {{Variance}} Component Estimation in Linear Inverse Ill-Posed Models},
    volume = {80},
    journal = {J.~Geodesy},
    author = {Koch, K.R. and Kusche, J.},
    year = {2007},
    pages = {69-81},
    owner = {swd}
    }

  • K. R. Koch, “Gibbs Sampler by Sampling-Importance-Resampling,” J.~Geodesy, vol. 81, pp. 581-591, 2007.
    [BibTeX]
    @article{koch:07b,
    title = {Gibbs Sampler by Sampling-Importance-Resampling},
    volume = {81},
    journal = {J.~Geodesy},
    author = {Koch, K.R.},
    year = {2007},
    pages = {581-591},
    owner = {swd}
    }

  • K. R. Koch, Introduction to Bayesian Statistics, 2 ed., Berlin: {Springer}, 2007.
    [BibTeX]
    @book{koch:07a,
    address = {Berlin},
    edition = {2},
    title = {Introduction to {{Bayesian Statistics}}},
    publisher = {{Springer}},
    author = {Koch, K.R.},
    year = {2007},
    owner = {swd}
    }

  • K. R. Koch, “Outlier Detection in Observations Including Leverage Points by Monte Carlo Simulations,” Allgemeine Vermessungsnachrichten, vol. 114, pp. 330-336, 2007.
    [BibTeX]
    @article{koch:07c,
    title = {Outlier Detection in Observations Including Leverage Points by {{Monte Carlo}} Simulations},
    volume = {114},
    journal = {Allgemeine Vermessungsnachrichten},
    author = {Koch, K.R.},
    year = {2007},
    pages = {330-336},
    owner = {swd}
    }

  • H. Kutterer and W. -D. Schuh, “Quality Measures and Control (Stochastic and Non-Stochastic Methodes Od Data Evaluation),” in National Report of the Federal Republic of Germany On the Geodetic Activities in the Years 2003-2007. XXIV General Assembly of the International Union for Geodesy and Geophysics (IUGG) 2007 in Perugia/Italy, J. Müller and H. Hornik, Eds., München: {Deutsche Geodätische Kommission}, 2007, pp. 160-165.
    [BibTeX]
    @incollection{kutterer-schuh:07,
    address = {M{\"u}nchen},
    series = {Reihe B 315},
    title = {Quality {{Measures}} and {{Control}} ({{Stochastic}} and {{Non}}-{{Stochastic Methodes}} Od {{Data Evaluation}})},
    booktitle = {National {{Report}} of the {{Federal Republic}} of {{Germany On}} the {{Geodetic Activities}} in the {{Years}} 2003-2007. {{XXIV General Assembly}} of the {{International Union}} for {{Geodesy}} and {{Geophysics}} ({{IUGG}}) 2007 in {{Perugia}}/{{Italy}}},
    publisher = {{Deutsche Geod{\"a}tische Kommission}},
    author = {Kutterer, H. and Schuh, W.-D.},
    editor = {M{\"u}ller, J. and Hornik, H.},
    year = {2007},
    pages = {160-165},
    owner = {swd}
    }

  • R. Pail, B. Metzler, B. Lackner, T. Preimesberger, E. Höck, W. -D. Schuh, H. Alkathib, C. Boxhammer, C. Siemes, and M. Wermuth, “GOCE Gravity Field Analysis in the Framework of HPF: Operational Software System and Simulation Results,” in Proceedings of the “`3\textsuperscriptRd Int. GOCE User Workshop”‘, 2007.
    [BibTeX]
    @inproceedings{pail-etal_07b,
    title = {{{GOCE}} Gravity Field Analysis in the Framework of {{HPF}}: Operational Software System and Simulation Results},
    booktitle = {Proceedings of the "`3{\textsuperscript{Rd}} {{Int}}. {{GOCE}} User Workshop"'},
    publisher = {{ESA, SP-627}},
    author = {Pail, R. and Metzler, B. and Lackner, B. and Preimesberger, T. and H{\"o}ck, E. and Schuh, W.-D. and Alkathib, H. and Boxhammer, Ch and Siemes, Ch and Wermuth, M.},
    year = {2007},
    adress = {Noordwijk},
    owner = {swd},
    note = {ISBN 92-9092-938-3}
    }

  • R. Pail, B. Metzler, B. Lackner, T. Preimesberger, E. Höck, W. -D. Schuh, H. Alkathib, C. Boxhammer, C. Siemes, and M. Wermuth, “GOCE-Schwerefeldprozessierung: Software-Architektur Und Simulationsergebnisse,” ZfV, vol. 132, pp. 16-25, 2007.
    [BibTeX]
    @article{pail-etal:07a,
    title = {{{GOCE}}-{{Schwerefeldprozessierung}}: {{Software}}-{{Architektur}} Und {{Simulationsergebnisse}}},
    volume = {132},
    journal = {ZfV},
    author = {Pail, R. and Metzler, B. and Lackner, B. and Preimesberger, T. and H{\"o}ck, E. and Schuh, W.-D. and Alkathib, H. and Boxhammer, Ch and Siemes, Ch and Wermuth, M.},
    year = {2007},
    pages = {16-25},
    owner = {swd}
    }

  • W. -D. Schuh, C. Boxhammer, and C. Siemes, Correlations, Variances, Covariances –- From GOCE Signals to GOCE Products, {ESA, SP-627}, 2007.
    [BibTeX]
    @book{schuh-etal:07,
    title = {Correlations, Variances, Covariances --- {{From GOCE}} Signals to {{GOCE}} Products},
    publisher = {{ESA, SP-627}},
    author = {Schuh, W.-D. and Boxhammer, Ch and Siemes, Ch},
    year = {2007},
    adress = {Noordwijk},
    owner = {swd}
    }

  • C. Siemes, W. -D. Schuh, J. Cai, N. Sneeuw, and O. Baur, “GOCE Data Processing: The Numerical Challange of Data Gaps,” in Proceedings of the Status Seminar Geotechnologien, “`Observation of the System Earth from Space”‘, Munich, Nov. 22-23, 2007, {Geotechnologien, Science Report}, 2007, vol. 11, pp. 99-105.
    [BibTeX]
    @incollection{siemes-etal:07,
    title = {{{GOCE}} Data Processing: The Numerical Challange of Data Gaps},
    volume = {11},
    booktitle = {Proceedings of the {{Status Seminar Geotechnologien}}, "`{{Observation}} of the {{System Earth}} from {{Space}}"', {{Munich}}, {{Nov}}. 22-23, 2007},
    publisher = {{Geotechnologien, Science Report}},
    author = {Siemes, Ch. and Schuh, W.-D. and Cai, J. and Sneeuw, N. and Baur, O.},
    year = {2007},
    pages = {99-105},
    owner = {swd}
    }

2006

  • C. Boxhammer and W. -D. Schuh, “GOCE Gravity Field Modeling: Computational Aspects – Free Kite Numbering Scheme,” in Observation of the Earth System from Space, R. Rummel, C. Reigber, M. Rothacher, G. Boedecker, U. Schreiber, and J. Flury, Eds., Berlin – Heidelberg: {Springer}, 2006, pp. 209-224.
    [BibTeX]
    @incollection{boxhammer-schuh_06,
    address = {Berlin - Heidelberg},
    title = {{{GOCE}} Gravity Field Modeling: Computational Aspects - Free Kite Numbering Scheme},
    booktitle = {Observation of the {{Earth System}} from {{Space}}},
    publisher = {{Springer}},
    author = {Boxhammer, Ch. and Schuh, W.-D.},
    editor = {Rummel, R. and Reigber, Ch and Rothacher, M. and Boedecker, G. and Schreiber, U. and Flury, J.},
    year = {2006},
    pages = {209-224},
    owner = {swd}
    }

  • C. Boxhammer, “Effiziente Numerische Verfahren Zur Sphä$\-$rischen Harmonischen Analyse von Satellitendaten,” Dissertation PhD Thesis, 2006.
    [BibTeX] [Download PDF]
    @phdthesis{boxhammer:06,
    type = {Dissertation},
    title = {Effiziente Numerische {{Verfahren}} Zur Sph{\"a}$\-$rischen Harmonischen {{Analyse}} von {{Satellitendaten}}},
    url = {http://hss.ulb.uni-bonn.de/diss_online/landw_fak/2006/boxhammer_christian},
    school = {Promotion an der Landwirtschaftlichen Fakult{\"a}t der Universit{\"a}t Bonn, Mitteilungen aus den Geod{\"a}tischen Instituten, Universit{\"a}t Bonn, Folge~94},
    author = {Boxhammer, Ch.},
    year = {2006},
    keywords = {paralleles Rechnen,pcgma,sphärische harmonische Analyse},
    owner = {schuh}
    }

  • K. Koch and C. Kotsakis, “Comments and Reply Regarding Kotsakis (2005): A Type of Biased Estimators for Linear Models with Uniformly Biased Data,” Journal of Geodesy, vol. 79, iss. 10, pp. 652-653, 2006. doi:10.1007/s00190-005-0016-6
    [BibTeX] [Download PDF]
    @article{koch-kotsakis:06,
    title = {Comments and Reply Regarding {{Kotsakis}} (2005): {{A}} Type of Biased Estimators for Linear Models with Uniformly Biased Data},
    volume = {79},
    issn = {0949-7714},
    doi = {10.1007/s00190-005-0016-6},
    number = {10},
    url = {http://dx.doi.org/10.1007/s00190-005-0016-6},
    journal = {Journal of Geodesy},
    author = {Koch, K. and Kotsakis, C.},
    year = {2006},
    keywords = {Geo-,Umweltwissenschaften,und},
    pages = {652-653},
    affiliation = {University of Bonn Institute of Theoretical Geodesy Nussallee 17 53115 Bonn Germany},
    owner = {swd},
    note = {10.1007/s00190-005-0016-6}
    }

  • K. R. Koch, “Gibbs Sampler by Sampling-Importance-Resampling,” J.~Geodesy, vol. DOI 10.1007/s00190-006-0121-1, 2006.
    [BibTeX]
    @article{koch:06c,
    title = {Gibbs Sampler by Sampling-Importance-Resampling},
    volume = {DOI 10.1007/s00190-006-0121-1},
    journal = {J.~Geodesy},
    author = {Koch, K.R.},
    year = {2006},
    owner = {swd}
    }

  • K. R. Koch, “ICM Algorithm for the Bayesian Reconstruction of Tomographic Images,” Photogrammetrie, Fernerkundung, Geoinformation, vol. 2006(3), pp. 229-238, 2006.
    [BibTeX]
    @article{koch:06a,
    title = {{{ICM}} Algorithm for the {{Bayesian}} Reconstruction of Tomographic Images},
    volume = {2006(3)},
    journal = {Photogrammetrie, Fernerkundung, Geoinformation},
    author = {Koch, K.R.},
    year = {2006},
    pages = {229-238},
    owner = {swd}
    }

  • W. D. Schuh, H. Alkhatib, C. Boxhammer, B. Kargoll, C. Siemes, O. Baur, and N. Sneeuw, Numerical Challenges for GOCE Data Analysis, , 2006.
    [BibTeX]
    @book{schuh-etal:06,
    series = {Status Seminar Geotechnologien, Bonn, Sept. 18-19, 2006},
    title = {Numerical {{Challenges}} for {{GOCE Data Analysis}}},
    author = {Schuh, W.D. and Alkhatib, H. and Boxhammer, Ch and Kargoll, B. and Siemes, Ch and Baur, O. and Sneeuw, N.},
    year = {2006},
    owner = {swd},
    note = {Geotechnologien, Science Report}
    }

2005

  • B. Kargoll, “Comparison of Some Robust Parameter Estimation Techniques for Outlier Analysisapplied to Simulated GOCE Mission Data,” in Gravity, Geoid and Space Missions, Berlin – Heidelberg – New York, 2005, pp. 77-82.
    [BibTeX]
    @inproceedings{kargoll:05,
    address = {Berlin - Heidelberg - New York},
    series = {Lecture Notes in Earth Sciences 129 (GGSM 2004, Porto)},
    title = {Comparison of Some Robust Parameter Estimation Techniques for Outlier Analysisapplied to Simulated {{GOCE}} Mission Data},
    booktitle = {Gravity, {{Geoid}} and {{Space Missions}}},
    publisher = {{Springer}},
    author = {Kargoll, B.},
    editor = {Jekeli, C. and Bastos, L. and Fernandes, J.},
    year = {2005},
    keywords = {robust,estimation},
    pages = {77-82},
    owner = {swd}
    }

  • K. R. Koch, “50 Jahre Institut Für Theoretische Geodäsie an Der Landwirtschaftlichen Fakultät Der Rheinischen Friedrich-Wilhelms-Universität Bonn,” Mitteilungen aus den Geodätischen Instituten der Rheinischen Friedrich-Wilhelms-Universität Bon, vol. Nr. 93, pp. 3-11, 2005.
    [BibTeX]
    @article{koch:05d,
    title = {50 {{Jahre Institut}} F{\"u}r {{Theoretische Geod{\"a}sie}} an Der {{Landwirtschaftlichen Fakult{\"a}t}} Der {{Rheinischen Friedrich}}-{{Wilhelms}}-{{Universit{\"a}t Bonn}}},
    volume = {Nr. 93},
    journal = {Mitteilungen aus den Geod{\"a}tischen Instituten der Rheinischen Friedrich-Wilhelms-Universit{\"a}t Bon},
    author = {Koch, K.R.},
    year = {2005},
    pages = {3-11},
    owner = {swd}
    }

  • K. R. Koch, “Bayesian Image Restoration by Markov Chain Monte Carlo Methods,” ZfV, p. 130,318-324, 2005.
    [BibTeX]
    @article{koch:05b,
    title = {Bayesian {{Image Restoration}} by {{Markov Chain Monte Carlo Methods}}},
    journal = {ZfV},
    author = {Koch, K.R.},
    year = {2005},
    pages = {130,318-324},
    owner = {swd}
    }

  • K. R. Koch, “Bemerkungen Zu: Von Der Zufallsvariablen Zum Sch”atzwert,” AVN 2005, vol. 112, 270, pp. 104-109, 2005.
    [BibTeX]
    @article{koch:05c,
    title = {Bemerkungen Zu: {{Von}} Der {{Zufallsvariablen}} Zum {{Sch}}"atzwert},
    volume = {112, 270},
    journal = {AVN 2005},
    author = {Koch, K.R.},
    year = {2005},
    pages = {104-109},
    owner = {swd}
    }

  • K. R. Koch, “Determining the Maximum Degree of Harmonic Coefficients in Geopotential Models by Monte Carlo Methods,” Studia Geophysica et Geodaetica, vol. 49, pp. 259-275, 2005.
    [BibTeX]
    @article{koch:05a,
    title = {Determining the {{Maximum Degree}} of {{Harmonic Coefficients}} in {{Geopotential Models}} by {{Monte Carlo Methods}}},
    volume = {49},
    journal = {Studia Geophysica et Geodaetica},
    author = {Koch, K.R.},
    year = {2005},
    keywords = {Gibbs sampler,Bayesian Statistics,degree variances,hypothesis tests},
    pages = {259-275},
    owner = {swd}
    }

  • R. Pail, W. -D. Schuh, and M. Wermuth, “GOCE Gravity Field Processing,” in Gravity, Geoid and Space Missions, IAG Symposia, Berlin – Heidelberg – New York, 2005, pp. 36-41.

  • R. Pail, W. -D. Schuh, and M. Wermuth, “GOCE Gravity Field Processing,” in IAG International Symposium “Gravity, Geoid and Space Missions” (GGSM2004), 2004.
    [BibTeX]
    @inproceedings{pail-etal:04,
    series = {CD-ROM},
    title = {{{GOCE Gravity Field Processing}}},
    booktitle = {{{IAG International Symposium}} ``{{Gravity}}, {{Geoid}} and {{Space Missions}}'' ({{GGSM2004}})},
    publisher = {{Porto/Portugal, Aug.~30~-~Sept.~3}},
    author = {Pail, R. and Schuh, W.-D. and Wermuth, M.},
    year = {2004},
    owner = {swd}
    }

  • W. -D. Schuh and B. Kargoll, “The Numerical Treatment of the Downward Continuation Problem for the Gravitypotential,” in V. Hotine-Marussi-Symposium, IAG Symposia, F. Sansò, Ed., Berlin – Heidelberg: {Springer}, 2004, vol. 127, pp. 22-31.
    [BibTeX]
    @incollection{schuh-kargoll_04,
    address = {Berlin - Heidelberg},
    series = {Lecture Notes in Earth Sciences},
    title = {The Numerical Treatment of the Downward Continuation Problem for the Gravitypotential},
    volume = {127},
    booktitle = {V. {{Hotine}}-{{Marussi}}-{{Symposium}}, {{IAG Symposia}}},
    publisher = {{Springer}},
    author = {Schuh, W.-D. and Kargoll, B.},
    editor = {Sans{\`o}, F.},
    year = {2004},
    pages = {22-31},
    owner = {swd}
    }

  • 2003

    • H. Alkhatib, A. Benoit, and W. -D. Schuh, “Berechung Der SST-Normalgleichungsanteile Über Die CHAMP Korrelations$\-$matrix; Analysen Und Implementierung,” {Theoretische Geodäsie, Universität Bonn}, Interner {{Technischer Bericht}} , 2003.
      [BibTeX]
      @techreport{alkhatib-etal:03,
      type = {Interner {{Technischer Bericht}}},
      title = {Berechung Der {{SST}}-{{Normalgleichungsanteile}} {\"U}ber Die {{CHAMP Korrelations}}$\-$matrix; {{Analysen}} Und {{Implementierung}}},
      institution = {{Theoretische Geod{\"a}sie, Universit{\"a}t Bonn}},
      author = {Alkhatib, H. and Benoit, A. and Schuh, W.-D.},
      year = {2003},
      owner = {swd}
      }

    • C. Boxhammer and W. -D. Schuh, “Orthogonalisierungsverfahren,” {Theoretische Geodäsie, Universität Bonn}, Interner {{Technischer Bericht}} , 2003.
      [BibTeX]
      @techreport{boxhammer-schuh:03,
      type = {Interner {{Technischer Bericht}}},
      title = {Orthogonalisierungsverfahren},
      institution = {{Theoretische Geod{\"a}sie, Universit{\"a}t Bonn}},
      author = {Boxhammer, C. and Schuh, W.-D.},
      year = {2003},
      owner = {swd}
      }

    • C. Boxhammer, Tailored Parallel Least Squares Algorithms for GOCE Data Processing, {Observation of the System Earth from Space}, 2003.
      [BibTeX]
      @book{boxhammer:03b,
      series = {Status Seminar Bavarian State Mapping Agency (BLVA), Munich, June 12-13, 2003},
      title = {Tailored Parallel Least Squares Algorithms for {{GOCE}} Data Processing},
      publisher = {{Observation of the System Earth from Space}},
      author = {Boxhammer, C.},
      year = {2003},
      owner = {swd},
      note = {Geotechnologien, Science Report, No.3, 27--30}
      }

    • B. Gundlich, K. -R. Koch, and J. Kusche, “Gibbs Sampler for Computing and Propagating Large Covariance Matrices,” Journal of Geodesy, vol. 77, iss. 9, pp. 514-528, 2003. doi:10.1007/s00190-003-0350-5
      [BibTeX] [Abstract] [Download PDF]

      The use of sampling-based Monte Carlo methods for the computation and propagation of large covariance matrices in geodetic applications is investigated. In particular, the so-called Gibbs sampler, and its use in deriving covariance matrices by Monte Carlo integration, and in linear and nonlinear error propagation studies, is discussed. Modifications of this technique are given which improve in efficiency in situations where estimated parameters are highly correlated and normal matrices appear as ill-conditioned. This is a situation frequently encountered in satellite gravity field modelling. A synthetic experiment, where covariance matrices for spherical harmonic coefficients are estimated and propagated to geoid height covariance matrices, is described. In this case, the generated samples correspond to random realizations of errors of a gravity field model.

      @article{gundlich-etal:03,
      title = {Gibbs Sampler for Computing and Propagating Large Covariance Matrices},
      volume = {77},
      issn = {0949-7714},
      doi = {10.1007/s00190-003-0350-5},
      abstract = {The use of sampling-based Monte Carlo methods for the computation and propagation of large covariance matrices in geodetic applications is investigated. In particular, the so-called Gibbs sampler, and its use in deriving covariance matrices by Monte Carlo integration, and in linear and nonlinear error propagation studies, is discussed. Modifications of this technique are given which improve in efficiency in situations where estimated parameters are highly correlated and normal matrices appear as ill-conditioned. This is a situation frequently encountered in satellite gravity field modelling. A synthetic experiment, where covariance matrices for spherical harmonic coefficients are estimated and propagated to geoid height covariance matrices, is described. In this case, the generated samples correspond to random realizations of errors of a gravity field model.},
      number = {9},
      url = {http://dx.doi.org/10.1007/s00190-003-0350-5},
      journal = {Journal of Geodesy},
      author = {Gundlich, B. and Koch, K.-R. and Kusche, J.},
      year = {2003},
      keywords = {Geo-,Umweltwissenschaften,und},
      pages = {514-528},
      affiliation = {Mathematical Geodesy and Positioning Delft University of Technology Thijsseweg 11 2629 JA Delft The Netherlands},
      owner = {swd}
      }

    • B. Kargoll and W. -D. Schuh, “Closed-Loop Simulationen Und Validierung von SGG-Modellen,” {Theoretische Geodäsie, Universität Bonn}, Interner {{Technischer Bericht}} , 2003.
      [BibTeX]
      @techreport{kargoll-schuh:03,
      type = {Interner {{Technischer Bericht}}},
      title = {Closed-{{Loop Simulationen}} Und {{Validierung}} von {{SGG}}-{{Modellen}}},
      institution = {{Theoretische Geod{\"a}sie, Universit{\"a}t Bonn}},
      author = {Kargoll, B. and Schuh, W.-D.},
      year = {2003},
      owner = {swd}
      }

    • B. Kargoll, Implementation and Validation of the Stochastic Model of GOCE SGG Data, {Observation of the System Earth from Space}, 2003.
      [BibTeX]
      @book{kargoll:03,
      series = {Status Seminar Bavarian State Mapping Agency (BLVA), Munich, June 12-13, 2003},
      title = {Implementation and Validation of the Stochastic Model of {{GOCE SGG}} Data},
      publisher = {{Observation of the System Earth from Space}},
      author = {Kargoll, B.},
      year = {2003},
      owner = {swd},
      note = {Geotechnologien, Science Report, No.3, 85--88}
      }

    • K. R. Koch and H. B. Papo, “The Bayesian Approach in Two-Step Modeling of Deformations,” Allgemeine Vermessungs-Nachrichten, vol. 110. Jg., p. 365-370, 208, 2003.
      [BibTeX]
      @article{koch-papo:03,
      title = {The {{Bayesian}} Approach in Two-Step Modeling of Deformations},
      volume = {110. Jg.},
      journal = {Allgemeine Vermessungs-Nachrichten},
      author = {Koch, K.R. and Papo, H. B.},
      year = {2003},
      pages = {365-370, 208},
      owner = {swd}
      }

    • K. R. Koch, “Foundations of Bayesian Statistics,” in Geodesy – The Challenge of the 3rd Millenium, Berlin, 2003, pp. 349-353.
      [BibTeX]
      @inproceedings{koch:03a,
      address = {Berlin},
      title = {Foundations of {{Bayesian}} Statistics},
      booktitle = {Geodesy - {{The Challenge}} of the 3rd {{Millenium}}},
      publisher = {{Springer}},
      author = {Koch, K.R.},
      editor = {Grafarend, E.W. and Krumm, F. W. and Schwarze, V. S.},
      year = {2003},
      pages = {349-353},
      owner = {swd}
      }

    • H. Schuh, R. Dill, H. Greiner-Mai, H. Kutterer, J. Müller, A. Nothnagel, B. Richter, M. Rothacher, U. Schreiber, and M. Soffel, Erdrotation Und Glo$\-$bale Dynamische Prozesse. Stand Und Ziele Der Modellbildung, Der Mess- Und Der Auswerte$\-$verfahren, Frankfurt/Main: {Bundesamt für Kartographie und Geodäsie}, 2003.
      [BibTeX]
      @book{schuh-etal:03,
      address = {Frankfurt/Main},
      title = {Erdrotation Und Glo$\-$bale Dynamische {{Prozesse}}. {{Stand}} Und {{Ziele}} Der {{Modellbildung}}, Der {{Mess}}- Und Der {{Auswerte}}$\-$verfahren},
      publisher = {{Bundesamt f{\"u}r Kartographie und Geod{\"a}sie}},
      author = {Schuh, H. and Dill, R. and Greiner-Mai, H. and Kutterer, H. and M{\"u}ller, J. and Nothnagel, A. and Richter, B. and Rothacher, M. and Schreiber, U. and Soffel, M.},
      year = {2003},
      owner = {swd}
      }

    • W. -D. Schuh and M. Pennekamp, “Stochastische Simulation Zur Approximativen Berechnung von Kovarianzmatrizen,” {Theoretische Geodäsie, Universität Bonn}, Interner {{Technischer Bericht}} , 2003.
      [BibTeX]
      @techreport{schuh-pennekamp:03,
      type = {Interner {{Technischer Bericht}}},
      title = {Stochastische {{Simulation}} Zur Approximativen {{Berechnung}} von {{Kovarianzmatrizen}}},
      institution = {{Theoretische Geod{\"a}sie, Universit{\"a}t Bonn}},
      author = {Schuh, W.-D. and Pennekamp, M.},
      year = {2003},
      owner = {swd}
      }

    • W. -D. Schuh, Auswertung Der Differentiellen Beschleunigungsmessungen Mit Einem Numerischen Ansatz Sowie Assimilation von GPS- Und Gradiometrie-Lösungen, {GOCE-GRAND, AP2, Zwischenbericht}, 2003.
      [BibTeX]
      @book{schuh:03a,
      title = {Auswertung Der Differentiellen {{Beschleunigungsmessungen}} Mit Einem Numerischen {{Ansatz}} Sowie {{Assimilation}} von {{GPS}}- Und {{Gradiometrie}}-{{L{\"o}sungen}}},
      publisher = {{GOCE-GRAND, AP2, Zwischenbericht}},
      author = {Schuh, W.-D.},
      year = {2003},
      owner = {swd}
      }

    • W. -D. Schuh, GOCE Gravity Field Determination – Simulation Studies, {Observation of the System Earth from Space}, 2003.
      [BibTeX]
      @book{schuh:03b,
      series = {Status Seminar Bavarian State Mapping Agency (BLVA), Munich, June 12-13, 2003},
      title = {{{GOCE}} Gravity Field Determination - Simulation Studies},
      publisher = {{Observation of the System Earth from Space}},
      author = {Schuh, W.-D.},
      year = {2003},
      owner = {swd},
      note = {Geotechnologien, Science Report, No.3, 152--155}
      }

    • W. -D. Schuh, Numerische Verfahren Zur Geodätischen Optimierung, {Theoretische Geodäsie, Universität Bonn}, 2003.
      [BibTeX] [Download PDF]
      @book{schuh_03,
      series = {Skriptum},
      title = {Numerische {{Verfahren}} Zur Geod{\"a}tischen {{Optimierung}}},
      url = {http://www.igg.uni-bonn.de/tg/uploads/tx_ikgpublication/schuh_03d.pdf},
      publisher = {{Theoretische Geod{\"a}sie, Universit{\"a}t Bonn}},
      author = {Schuh, W.-D.},
      year = {2003},
      owner = {swd}
      }

    • W. -D. Schuh, “The Processing of Band-Limited Measurements; Filtering Techniques in the Least Squares Context and in the Presence of Data Gaps,” in Earth Gravity Field from Space – From Sensors to Earth Sciences, G. Beutler, M. R. Drinkwater, R. Rummel, and R. von Steiger, Eds., {Space Science Reviews}, 2003, vol. 108, pp. 67-78.
      [BibTeX]
      @incollection{schuh:03c_alt,
      title = {The Processing of Band-Limited Measurements; Filtering Techniques in the Least Squares Context and in the Presence of Data Gaps},
      volume = {108},
      booktitle = {Earth {{Gravity Field}} from {{Space}} - {{From Sensors}} to {{Earth Sciences}}},
      publisher = {{Space Science Reviews}},
      author = {Schuh, W.-D.},
      editor = {Beutler, G. and Drinkwater, M. R. and Rummel, R. and von Steiger, R.},
      year = {2003},
      keywords = {Filtering,least squares,band-limited observations,decorrelation,whitening process},
      pages = {67-78},
      owner = {swd},
      note = {ISSI Workshop, Bern (March 11-15,2002)}
      }

    • W. -D. Schuh, “The Processing of Band-Limited Measurements; Filtering Techniques in the Least Squares Context and in the Presence of Data Gaps,” Space Science Reviews, vol. 108, iss. 1-2, pp. 67-78, 2003. doi:10.1023/A:1026121814042
      [BibTeX]
      @article{schuh_03c,
      title = {The Processing of Band-Limited Measurements; Filtering Techniques in the Least Squares Context and in the Presence of Data Gaps},
      volume = {108},
      doi = {10.1023/A:1026121814042},
      number = {1-2},
      journal = {Space Science Reviews},
      author = {Schuh, W.-D.},
      editor = {Beutler, G. and Drinkwater, M. R. and Rummel, R. and von Steiger, R.},
      year = {2003},
      keywords = {Filtering,least squares,band-limited observations,decorrelation,whitening process},
      pages = {67-78},
      owner = {swd},
      note = {schuh\textsubscript{0}3c}
      }

    2002

    • B. Gundlich and K. -R. Koch, “Confidence Regions for GPS Baselines by Bayesian Statistics,” Journal of Geodesy, vol. 76, iss. 1, pp. 55-62, 2002. doi:10.1007/s001900100222
      [BibTeX] [Abstract] [Download PDF]

      The global positioning system (GPS) model is distinctive in the way that the unknown parameters are not only real-valued, the baseline coordinates, but also integers, the phase ambiguities. The GPS model therefore leads to a mixed integer-real-valued estimation problem. Common solutions are the float solution, which ignores the ambiguities being integers, or the fixed solution, where the ambiguities are estimated as integers and then are fixed. Confidence regions, so-called HPD (highest posterior density) regions, for the GPS baselines are derived by Bayesian statistics. They take care of the integer character of the phase ambiguities but still consider them as unknown parameters. Estimating these confidence regions leads to a numerical integration problem which is solved by Monte Carlo methods. This is computationally expensive so that approximations of the confidence regions are also developed. In an example it is shown that for a high confidence level the confidence region consists of more than one region.

      @article{gundlich-koch:02,
      title = {Confidence Regions for {{GPS}} Baselines by {{Bayesian}} Statistics},
      volume = {76},
      issn = {0949-7714},
      doi = {10.1007/s001900100222},
      abstract = {The global positioning system (GPS) model is distinctive in the way that the unknown parameters are not only real-valued, the baseline coordinates, but also integers, the phase ambiguities. The GPS model therefore leads to a mixed integer-real-valued estimation problem. Common solutions are the float solution, which ignores the ambiguities being integers, or the fixed solution, where the ambiguities are estimated as integers and then are fixed. Confidence regions, so-called HPD (highest posterior density) regions, for the GPS baselines are derived by Bayesian statistics. They take care of the integer character of the phase ambiguities but still consider them as unknown parameters. Estimating these confidence regions leads to a numerical integration problem which is solved by Monte Carlo methods. This is computationally expensive so that approximations of the confidence regions are also developed. In an example it is shown that for a high confidence level the confidence region consists of more than one region.},
      number = {1},
      url = {http://dx.doi.org/10.1007/s001900100222},
      journal = {Journal of Geodesy},
      author = {Gundlich, B. and Koch, K.-R.},
      year = {2002},
      keywords = {Geo-,Umweltwissenschaften,und},
      pages = {55-62},
      affiliation = {Institute for Theoretical Geodesy, University of Bonn, Nussallee 17, 53115 Bonn, Germany e-mail: koch@theor.geod.uni-bonn.de; Tel.: +49-228-73-3395; Fax: +49-228-73-3029 DE DE},
      owner = {swd}
      }

    • K. R. Koch and J. Kusche, “Regularization of Geopotential Determination from Satellite Data by Variance Components,” J.~Geodesy, vol. 76, pp. 259-268, 2002.
      [BibTeX]
      @article{koch-kusche:02,
      title = {Regularization of Geopotential Determination from Satellite Data by Variance Components},
      volume = {76},
      journal = {J.~Geodesy},
      author = {Koch, K.R. and Kusche, J.},
      year = {2002},
      keywords = {confidence intervals,regularization,Bayesian Statistics,Geopotential determination,variance components},
      pages = {259-268},
      owner = {swd}
      }

    • K. -R. Koch and J. Kusche, “Regularization of Geopotential Determination from Satellite Data by Variance Components,” Journal of Geodesy, vol. 76, iss. 5, pp. 259-268, 2002. doi:10.1007/s00190-002-0245-x
      [BibTeX] [Abstract] [Download PDF]

      Different types of present or future satellite data have to be combined by applying appropriate weighting for the determination of the gravity field of the Earth, for instance GPS observations for CHAMP with satellite to satellite tracking for the coming mission GRACE as well as gradiometer measurements for GOCE. In addition, the estimate of the geopotential has to be smoothed or regularized because of the inversion problem. It is proposed to solve these two tasks by Bayesian inference on variance components. The estimates of the variance components are computed by a stochastic estimator of the traces of matrices connected with the inverse of the matrix of normal equations, thus leading to a new method for determining variance components for large linear systems. The posterior density function for the variance components, weighting factors and regularization parameters are given in order to compute the confidence intervals for these quantities. Test computations with simulated gradiometer observations for GOCE and satellite to satellite tracking for GRACE show the validity of the approach.

      @article{koch_kusche:02,
      title = {Regularization of Geopotential Determination from Satellite Data by Variance Components},
      volume = {76},
      issn = {0949-7714},
      doi = {10.1007/s00190-002-0245-x},
      abstract = {Different types of present or future satellite data have to be combined by applying appropriate weighting for the determination of the gravity field of the Earth, for instance GPS observations for CHAMP with satellite to satellite tracking for the coming mission GRACE as well as gradiometer measurements for GOCE. In addition, the estimate of the geopotential has to be smoothed or regularized because of the inversion problem. It is proposed to solve these two tasks by Bayesian inference on variance components. The estimates of the variance components are computed by a stochastic estimator of the traces of matrices connected with the inverse of the matrix of normal equations, thus leading to a new method for determining variance components for large linear systems. The posterior density function for the variance components, weighting factors and regularization parameters are given in order to compute the confidence intervals for these quantities. Test computations with simulated gradiometer observations for GOCE and satellite to satellite tracking for GRACE show the validity of the approach.},
      number = {5},
      url = {http://dx.doi.org/10.1007/s00190-002-0245-x},
      journal = {Journal of Geodesy},
      author = {Koch, K.-R. and Kusche, J.},
      year = {2002},
      keywords = {Geo-,Umweltwissenschaften,und},
      pages = {259-268},
      affiliation = {Institute for Theoretical Geodesy, University of Bonn, Nussallee 17, 53115 Bonn, Germany e-mail: koch@theor.geod.uni-bonn.de; Tel.: +49-228-73-3395; Fax: +49-228-73-3029 DE},
      owner = {swd}
      }

    • K. R. Koch, “Die Frühere Zentralleitung Des Deutschen Geodätischen Forschungsinstituts,” in Am Puls von Raum Und Zeit, 50 Jahre Deutsche Geodätische Kommission, München, 2002, p. Reihe E, Nr. 26, 157-158.
      [BibTeX]
      @inproceedings{koch:02c,
      address = {M{\"u}nchen},
      title = {Die Fr{\"u}here {{Zentralleitung}} Des {{Deutschen Geod{\"a}tischen Forschungsinstituts}}},
      booktitle = {Am {{Puls}} von {{Raum}} Und {{Zeit}}, 50 {{Jahre Deutsche Geod{\"a}tische Kommission}}},
      publisher = {{Deutsche Geod{\"a}tische Kommission}},
      author = {Koch, K.R.},
      editor = {Albertz, J. and B{\"a}hr, H.-P. and Hornik, H. and Rummel, R.},
      year = {2002},
      pages = {Reihe E, Nr. 26, 157-158},
      owner = {swd}
      }

    • K. R. Koch, “Monte-Carlo-Simulation Für Regularisierungsparameter,” ZfV, vol. 127, pp. 305-309, 2002.
      [BibTeX]
      @article{koch:02a,
      title = {Monte-{{Carlo}}-{{Simulation}} F{\"u}r {{Regularisierungsparameter}}},
      volume = {127},
      journal = {ZfV},
      author = {Koch, K.R.},
      year = {2002},
      pages = {305-309},
      owner = {swd}
      }

    • K. R. Koch, “Räumliche Helmert-Transformation Variabler Koordinaten Im Gauß-Markoff-Modell,” ZfV, vol. 127, pp. 147-152, 2002.
      [BibTeX]
      @article{koch:02b,
      title = {R{\"a}umliche {{Helmert}}-{{Transformation}} Variabler {{Koordinaten}} Im {{Gau{\ss}}}-{{Markoff}}-{{Modell}}},
      volume = {127},
      journal = {ZfV},
      author = {Koch, K.R.},
      year = {2002},
      pages = {147-152},
      owner = {swd}
      }

    • W. -D. Schuh, “Improved Modeling of SGG-Data Sets by Advanced Filter Strategies,” in ESA-Project “From Eötvös to mGal+”, WP 2, Final-Report, {ESA/ESTEC Contract No. 14287/00/NL/DC}, 2002, pp. 113-181.
      [BibTeX]
      @incollection{schuh_02,
      title = {Improved Modeling of {{SGG}}-Data Sets by Advanced Filter Strategies},
      booktitle = {{{ESA}}-{{Project}} ``{{From E{\"o}tv{\"o}s}} to {{mGal}}+'', {{WP}} 2, {{Final}}-{{Report}}},
      publisher = {{ESA/ESTEC Contract No. 14287/00/NL/DC}},
      author = {Schuh, W.-D.},
      year = {2002},
      pages = {113-181},
      owner = {swd},
      note = {schuh\textsubscript{0}2}
      }

    2001

    • R. Blinken and K. R. Koch, “Geoid and Sea Surface Topography Derived from ERS-1 Altimeter Data by the Adjoint Method,” Studia geophysica et geodaetica, vol. 45, pp. 235-250, 2001. doi:10.1023/A:1022080011849
      [BibTeX]
      @article{blinken-koch_01,
      title = {Geoid and Sea Surface Topography Derived from {{ERS}}-1 Altimeter Data by the Adjoint Method},
      volume = {45},
      doi = {10.1023/A:1022080011849},
      journal = {Studia geophysica et geodaetica},
      author = {Blinken, R. and Koch, K. R.},
      year = {2001},
      pages = {235-250},
      owner = {swd}
      }

    • K. R. Koch, “Bemerkungen Zu Der Veröffentlichung ”Zur Bestimmung Eindeutiger Transformationsparameter”,” ZfV, vol. 126, p. 297, 2001.
      [BibTeX]
      @article{koch:01,
      title = {Bemerkungen Zu Der {{Ver{\"o}ffentlichung}} ''{{Zur Bestimmung}} Eindeutiger {{Transformationsparameter}}''},
      volume = {126},
      journal = {ZfV},
      author = {Koch, K.R.},
      year = {2001},
      pages = {297},
      owner = {swd}
      }

    • R. Pail, G. Plank, and W. -D. Schuh, “Spatially Restricted Data Distributions on the Sphere: The Method of Orthonormalized Functions and Applications,” Journal of Geodesy, vol. 75, pp. 44-56, 2001. doi:10.1007/s001900000153
      [BibTeX]
      @article{pail-etal_01,
      title = {Spatially Restricted Data Distributions on the Sphere: The Method of Orthonormalized Functions and Applications},
      volume = {75},
      doi = {10.1007/s001900000153},
      journal = {Journal of Geodesy},
      author = {Pail, R. and Plank, G. and Schuh, W.-D.},
      year = {2001},
      pages = {44-56},
      owner = {swd}
      }

    • G. Plank and W. -D. Schuh, Numerical Solution Strategies for Global Gravity Field Determination, {Wien}, 2001.
      [BibTeX]
      @book{plank-schuh:01,
      series = {{\"O}sterreichische Beitr{\"a}ge zu Meteorologie und Geophysik, Heft 26},
      title = {Numerical Solution Strategies for Global Gravity Field Determination},
      publisher = {{Wien}},
      author = {Plank, G. and Schuh, W.-D.},
      year = {2001},
      owner = {swd}
      }

    • W. -D. Schuh, R. Pail, and G. Plank, “Assessment of Different Numerical Solution Strategies for Gravity Field Recovery,” in Proceedings of the ”First International GOCE~User Workshop”, {ESTEC, Noordwijk, The Netherlands (April 23-24, 2001)}, 2001, pp. 87-95.
      [BibTeX] [Download PDF]
      @incollection{schuh-etal_01,
      title = {Assessment of Different Numerical Solution Strategies for Gravity Field Recovery},
      url = {http://earth.esa.int/goce04/first_igw/papers/Schuh_etal.pdf},
      booktitle = {Proceedings of the ''{{First International GOCE~User Workshop}}''},
      publisher = {{ESTEC, Noordwijk, The Netherlands (April 23-24, 2001)}},
      author = {Schuh, W.-D. and Pail, R. and Plank, G.},
      year = {2001},
      pages = {87-95},
      owner = {swd}
      }

    • W. -D. Schuh, “Improved Modeling of SGG-Data Sets by Advanced Filter Strategies,” in ESA-Project “From Eötvös to mGal+”, WP 2, Midterm-Report, {ESA/ESTEC Contract No. 14287/00/NL/DC}, 2001, pp. 111-145.
      [BibTeX]
      @incollection{schuh:01a,
      title = {Improved Modeling of {{SGG}}-Data Sets by Advanced Filter Strategies},
      booktitle = {{{ESA}}-{{Project}} ``{{From E{\"o}tv{\"o}s}} to {{mGal}}+'', {{WP}} 2, {{Midterm}}-{{Report}}},
      publisher = {{ESA/ESTEC Contract No. 14287/00/NL/DC}},
      author = {Schuh, W.-D.},
      year = {2001},
      pages = {111-145},
      owner = {swd}
      }

    • W. -D. Schuh, Numerische Verfahren Zur Geodätischen Optimierung, {Theoretische Geodäsie, Universität Bonn}, 2001.
      [BibTeX]
      @book{schuh:01b,
      series = {Skriptum},
      title = {Numerische {{Verfahren}} Zur Geod{\"a}tischen {{Optimierung}}},
      publisher = {{Theoretische Geod{\"a}sie, Universit{\"a}t Bonn}},
      author = {Schuh, W.-D.},
      year = {2001},
      owner = {swd}
      }

    2000

    • S. Hekimoglu and K. R. Koch, “How Can Reliability of the Test for Outliers Be Measured?,” Allgemeine Vermessungs-Nachrichten, vol. 107. Jg., pp. 247-253, 2000.
      [BibTeX]
      @article{hekimoglu-koch:00,
      title = {How Can Reliability of the Test for Outliers Be Measured?},
      volume = {107. Jg.},
      journal = {Allgemeine Vermessungs-Nachrichten},
      author = {Hekimoglu, S. and Koch, K. R.},
      year = {2000},
      pages = {247-253},
      owner = {swd}
      }

    • K. Koch, Beispiele Zur Parameterschätzung, Zur Festlegung von Konfidenzregionen Und Zur Hypothesenprüfung, Bonn: {Mitteilungen aus den Geodätischen Instituten der Universität Bonn}, 2000, vol. 87.
      [BibTeX]
      @book{koch:00a,
      address = {Bonn},
      title = {Beispiele Zur {{Parametersch{\"a}tzung}}, Zur {{Festlegung}} von {{Konfidenzregionen}} Und Zur {{Hypothesenpr{\"u}fung}}},
      volume = {87},
      publisher = {{Mitteilungen aus den Geod{\"a}tischen Instituten der Universit{\"a}t Bonn}},
      author = {Koch, Karl-Rudolf},
      year = {2000},
      owner = {swd}
      }

    • K. R. Koch, H. Fröhlich, and G. Bröker, “Transformation Räumlicher Variabler Koordinaten,” Allgemeine Vermessungs-Nachrichten, vol. 107. Jg., pp. 293-295, 2000.
      [BibTeX]
      @article{koch-etal:00,
      title = {Transformation R{\"a}umlicher Variabler {{Koordinaten}}},
      volume = {107. Jg.},
      journal = {Allgemeine Vermessungs-Nachrichten},
      author = {Koch, K.R. and Fr{\"o}hlich, H. and Br{\"o}ker, G.},
      year = {2000},
      pages = {293-295},
      owner = {swd}
      }

    • K. R. Koch, Einführung in Die Bayes-Statistik, Berlin, Heidelberg: {Springer–Verlag}, 2000.
      [BibTeX]
      @book{koch:00,
      address = {Berlin, Heidelberg},
      title = {Einf{\"u}hrung in Die {{Bayes}}-{{Statistik}}},
      publisher = {{Springer--Verlag}},
      author = {Koch, K.R.},
      year = {2000},
      owner = {swd}
      }

    • K. R. Koch, Einführung in Die Bayes-Statistik, Berlin: {Springer}, 2000.
      [BibTeX]
      @book{koch:00b,
      address = {Berlin},
      title = {Einf{\"u}hrung in Die {{Bayes}}-{{Statistik}}},
      publisher = {{Springer}},
      author = {Koch, K.R.},
      year = {2000},
      owner = {swd}
      }

    • K. R. Koch, Konfidenzregionen Für Robuste Parameterschätzungen Mit Hilfe Der Bayes-Statistik, Darmstadt: {Schriftenreihe Fachrichtung Geodäsie, Fachbereich Bauingenieurwesen und Geodäsie, Technische Universität}, 2000.
      [BibTeX]
      @book{koch:00c,
      address = {Darmstadt},
      title = {Konfidenzregionen F{\"u}r Robuste {{Parametersch{\"a}tzungen}} Mit {{Hilfe}} Der {{Bayes}}-{{Statistik}}},
      publisher = {{Schriftenreihe Fachrichtung Geod{\"a}sie, Fachbereich Bauingenieurwesen und Geod{\"a}sie, Technische Universit{\"a}t}},
      author = {Koch, K.R.},
      year = {2000},
      owner = {swd},
      note = {Heft 10}
      }

    • K. R. Koch, “Numerische Verfahren in Der Bayes-Statistik,” ZfV, vol. 125, pp. 408-414, 2000.
      [BibTeX]
      @article{koch:00d,
      title = {Numerische {{Verfahren}} in Der {{Bayes}}-{{Statistik}}},
      volume = {125},
      journal = {ZfV},
      author = {Koch, K.R.},
      year = {2000},
      pages = {408-414},
      owner = {swd}
      }

    • K. R. Koch, “Some Basics of Bayesian Statistics,” Geodezija ir Kartografija, vol. 26, pp. 147-151, 2000.
      [BibTeX]
      @article{koch:00e,
      title = {Some {{Basics}} of {{Bayesian Statistics}}},
      volume = {26},
      journal = {Geodezija ir Kartografija},
      author = {Koch, K.R.},
      year = {2000},
      pages = {147-151},
      owner = {swd}
      }

    • R. Pail and W. -D. Schuh, “Effects of Inhomogeneous Data Coverage on Spectral Analysis,” in Towards an Integrated Global Geodetic Observing System (IGGOS), IAG Symposia, Berlin – Heidelberg, 2000, pp. 209-213.