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Abstract

The DORIS technique (Doppler Orbitography by Radiopositioning Integrated on Satellite) is a French satellite system used for the determination of satellite orbits and for positioning. With orbits estimated with a precision better than a centimeter on the radial component, DORIS is important for space altimetry to monitor sea level rise, one of the key indicators of climate change. The processing of spatial geodesy measurements in general requires modeling involving the estimation of many parameters by least squares or by an equivalent estimation method. A limiting factor in performing the estimation, regardless of the physical validity of the chosen model, is to ensure that no parameter of the model can be written as a linear combination of the other parameters, otherwise the model matrix is singular and the normal matrix non-invertible. The situation becomes more complicated when the model matrix is non-singular but close to being singular, leading to possible multicollinearity problems: the estimates of a parameter can thus be questioned if it is close to a linear combination of other parameters. These multicollinearity effects explain, among other things, why estimating the origin of the terrestrial reference frame via GNSS is impossible. In this poster, we evaluate to what extent the DORIS data processing can be affected by multicollinearity effects. We will analyze the estimated parameters for single satellite calculations with different satellites and in a multi-satellite computation in order to test mathematically whether the parameter estimates are reasonable. In particular, we will review the frame parameters (origin and TRF scale).