%0 Book
%T Machine Learning calibration of satellite platform magnetometer data
%A Styp-Rekowski, Kevin
%D 2024
%C Rostock
%C Universität Rostock
%G English
%F 1928701426
%O vorgelegt von Kevin Marcel Styp-Rekowski
%O Enthält Zeitschriftenartikel
%O GutachterInnen: Claudia Stolle (IAP Kühlungsborn) ; Odej Kao (TU Berlin) ; Alexander Grayver (Universität zu Köln)
%O Dissertation Universität Rostock 2024 Kumulative Dissertation
%X This research explores the evolution of Earth's magnetic field, emphasizing the importance of accurate data for analysis and prediction. The dissertation introduces a novel Machine Learning-based approach to enhance the calibration of platform magnetometers on non-dedicated satellites, addressing the challenges of their rough calibration. The methodology, applied to the GOCE and GRACE-FO missions, significantly improves data accuracy, enabling scientific application. This work increases data availability for geomagnetic studies and sets the stage for future applications in satellite missions.<eng>
%L 004
%9 theses
%9 Text
%9 Hochschulschrift
%R 10.18453/rosdok_id00004838
%U https://purl.uni-rostock.de/rosdok/id00004838
%U https://nbn-resolving.org/urn:nbn:de:gbv:28-rosdok_id00004838-8
%U https://d-nb.info/1369498756/34
%U https://doi.org/10.18453/rosdok_id00004838