Schwarz, Klaus-Peter P.Hammada, Youcef2005-07-292005-07-291996Hammada, Y. (1996). A comparison of filtering techniques for airborne gravimetry (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/225910612129144http://hdl.handle.net/1880/29502Bibliography: p. 99-103.Three different filtering techniques for the estimation of the gravity disturbance are theoretically outlined and numerically tested. The first approach, finite impulse response lowpass filtering, is a frequency domain method. The two other approaches, Kalman filtering and deterministic model filtering, are model based methods. An airborne gravity data set is used to compare these methods numerically. This comparison is based on an error measure, the root mean square error between the estimate and the reference. The reference is obtained by upward continuating a grid of surface free-air gravity anomalies and a terrain model. The lowpass filter provided the best estimation accuracy of the gravity disturbance and works equally well for any type of area. The deterministic model filter is better than the Kalman filter for smooth areas but is very sensitive to rapid changes of the gravity field. Kalman filtering requires an accurate covariance function of the gravity field of the flown area, and is very sensitive to its uncertainties.xv, 103 leaves ; 30 cm.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.QB 334 H36 1996Gravity - MeasurementKalman filteringmaster thesis10.11575/PRISM/22591QB 334 H36 1996