Frequency-dependent data weighting in global gravity field modeling from satellite data contaminated by non-stationary noise |
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| Authors: | P Ditmar R Klees X Liu |
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| Institution: | (1) Delft Institute of Earth Observation and Space Systems (DEOS), Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1, 2629 HS Delft, The Netherlands |
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| Abstract: | Satellite data that are used to model the global gravity field of the Earth are typically corrupted by correlated noise, which
can be related to a frequency dependence of the data accuracy. We show an opportunity to take such noise into account by using
a proper noise covariance matrix in the estimation procedure. If the dependence of noise on frequency is not known a priori,
it can be estimated on the basis of a posteriori residuals. The methodology can be applied to data with gaps. Non-stationarity
of noise can also be dealt with, provided that the necessary a priori information exists. The proposed methodology is illustrated
with CHAllenging Mini-satellite Payload (CHAMP) data processing. It is shown, in particular, that the usage of a proper noise
model can make the measurements of non-gravitational satellite accelerations unnecessarily. This opens the door for high-quality
modeling of the Earth’s gravity field on the basis of observed orbits of non-dedicated satellites (i.e., satellites without
an on-board accelerometer). Furthermore, the processing of data from dedicated satellite missions – GRACE (Gravity Recovery
and Climate Experiment) and GOCE (Gravity field and steady-state Ocean Circulation Explorer) – may also benefit from the proposed
methodology. |
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| Keywords: | Earth’ s gravity field Colored noise Covariance matrix estimation CHAMP (CHAllenging Mini-satellite Payload) Satellite-borne accelerometer |
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