@ARTICLE{Osada_Edward_A_2005,
 author={Osada, Edward and Kryński, Jan and Owczarek, Magdalena},
 volume={vol. 54},
 number={No 3},
 journal={Geodesy and Cartography},
 pages={99-117},
 howpublished={online},
 year={2005},
 publisher={Commitee on Geodesy PAS},
 abstract={An increased use of global navigation techniques for positioning, and in particular for height determination, led to a growing need for precise models of height reference surface, i.e. geoid or quasigeoid. Geoid or quasigeoid heights at a cm accuracy level, provided on growing number ofGPS/levelling sites, can not only be used for quality control of gravimetric geoid but they also can be integrated with gravity data for geoid/quasigeoid modelling. Such a model is of particular use for surveying practice. A method of quasigeoid modelling based on GPS/levelling data with support of geopotential model and gravity data was developed. The components of height anomaly are modelled with the deterministic part that consists of height anomaly based on EGM96 geopotential model and Molodensky's integral, as well as the polynomial representing trend, and from the stochastic part represented by the isotropic covariance function. Model parameters, i.e. polynomial coefficients and covariance function parameters are determined in a single process of robust estimation, resistant to the outlying measurements. The method was verified using almost a thousand height anomalies from the sites of the EUREF-POL, POLREF, EUVN'97 and WSSG (Military Satellite Geodetic Network) networks in Poland as well as geopotential model refined with gravity data in l' x l' grid. The estimated average mean square error of quasigeoid height is at the level of O.Ol m. The outlying measurements were efficiently detected.},
 type={Article},
 title={A robust method of quasigeoid modelling in Poland based on GPS/levelling data with support of gravity data},
 URL={http://journals.pan.pl/Content/121289/PDF/3_GK__VOL_54_NO_3_2005_Osada_Odporna_metoda.pdf},
 keywords={quasigeoid, GPS/levelling, collocations, robust estimation},
}