Gross Error Compensation for Gravity Field Analysis Based on Kinematic Orbit Data

Götzelmann, Martin; Keller, Wolfgang; Reubelt, T.

doi:10.1007/s00190-006-0061-9

Cited by 13 publications

(2 citation statements)

References 19 publications

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“…Of course, other methods might also be applicable and advisable in specific geodetic problems, the more so M-estimation has found a variety of geodetic applications, e.g. in deformation analysis [84,[90][91][92][93][94], geotechnical analysis [95], coordinate transformation [76,82], detection and compensation of gross and systematic errors [96][97][98], GNSS data processing [60,64,[99][100][101], or marine navigation [102,103].…”

Section: M-estimationmentioning

confidence: 99%

Robust procedures in processing measurements in geodesy and surveying: a review

Duchnowski,

Wyszkowska

2024

Meas. Sci. Technol.

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Outlying observations are undesirable but possible elements of geodetic measurements. In such a context, the primary and trivial solution is to repeat “suspected” observations. The question arises: what if the measurements cannot be performed again, or if one cannot flag outliers easily and efficiently? In such a case, one should process data by applying methods that consider the possible occurrence of outlying observations. Historically, except for some previous attempts, the statistical approach to robust estimation originates in the 60s of the 20th century and refers to the pioneer papers of Huber, Tukey, Hampel, Hodges, and Lehmann. Also, the statistical procedures known as data snooping (data dredging) were developed at a similar time. It took not a long time before robust procedures were implemented for processing geodetic observations or adjustment of observation systems. The first works of Baarda and Pope encouraged other scientists or surveyors to elaborate robust procedures adapted for geodetic or surveying problems, which resulted in their rapid development in the last two decades of the 20th century. The question for the 21st century is whether robustness is still an important issue relating to modern measurement technologies and numerical data processing. One should realize that modern geodetic techniques do not decrease the probability of outlier occurrence. Considering measurement systems that yield big data, it is almost certain that outliers occur somewhere. The paper reviews different approaches to robust processing of geodetic observations, from the data snooping methods, random sampling, M-estimation, R-estimation, and Msplit estimation to robust estimation of the variance coefficient. Such a variety reflects different natures, origins, or properties of outliers and the apparent fact that there is no best and most efficient and universal robust approach. The methods presented are indeed the basis for future solutions based on, e.g., machine learning.

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Section: M-estimationmentioning

confidence: 99%

Robust procedures in processing measurements in geodesy and surveying: a review

Duchnowski,

Wyszkowska

2024

Meas. Sci. Technol.

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“…However, experience tells us that a set of observations is, in general, contaminated by outliers. As the least-squares method tries to minimize the square of the residuals (e T Q −1 y e), such outliers can have a signiÀcant effect on the estimated gravity Àeld parameters; see, e.g., Götzelmann et al [2006]. Moreover, they will affect a possible adjustment of the stochastic model using VCE.…”

Section: Outlier Detection and Robust Estimationmentioning

confidence: 99%

Functional and stochastic modelling of satellite gravity data

Loon¹

2008

Publications on Geodesy

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been of great value to this work and to my own personal development as a researcher. Moreover, he initiated the software development of the energy balance approach, the variance component estimation and the inversion of the GPS site displacements.Many thanks go my promotor Roland Klees. His feedback and support, especially since Jürgen Kusche left our group, are highly appreciated. Furthermore, I would like to thank all my colleagues at the Physical and Space Geodesy group. Special thanks to my room mate Bas Alberts for all the fun and fruitful discussions we had during our MSc and PhD periods. I will not forget the conversations with Relly van Wingaarden on Barbie dolls, horses and Chinese climbing walls. Moreover, she has been of great support throughout the years for all the non-scientiÀc tasks. I should also mention Mark-Willem Jansen for the discussions we had on the inversion of GPS and GRACE observations and for all the small talks we had on different subjects. Many thanks go to Rene Reudink for all the technical support, Xianglin Liu for the company during the many hours we worked together in the weekends and evenings, and Shizhuo Liu for all the funny conversations we had throughout the years.I would like to thank the members of the committee for proofreading this thesis. Special thanks to Michael Sideris for his constructive feedback on editorial issues. The CHAMP satellite data was kindly provided by the IAPG in Munich, the GRACE data was downloaded from the CSR data base and the Swiss GPS/levelling data was provided by Urs Marti from the Federal OfÀce of Topography Swisstopo.However, this thesis would never have been completed without the support of my family and friends. I will not forget all the nice words I received during the period of illness of my sister Barbara. I am lucky that I had plenty of possibilities to relax; playing volleyball, the funny activities at Scouting Halsteren, and my trips to Africa.I would like to thank my parents for their endless support, but most importantly for creating a place and atmosphere I consider home. The last words of thanks go to my sister Barbara. Her strength in difÀcult periods has been an example for many, including me.

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Harmonic Analysis of the Earth’s Gravitational Field from Kinematic CHAMP Orbits based on Numerically Derived Satellite Accelerations

Reubelt

Götzelmann

Grafarend

Observation of the Earth System From Space

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Gross Error Compensation for Gravity Field Analysis Based on Kinematic Orbit Data

Cited by 13 publications

References 19 publications

Robust procedures in processing measurements in geodesy and surveying: a review

Robust procedures in processing measurements in geodesy and surveying: a review

Functional and stochastic modelling of satellite gravity data

Harmonic Analysis of the Earth’s Gravitational Field from Kinematic CHAMP Orbits based on Numerically Derived Satellite Accelerations

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