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Abstract
Title 1: A Kalman-filter-based approach to combining independent Earth-orientation series Abstract 1: An approach, based upon the use of a Kalman-filter, that is currently employed at the Jet Propulsion Laboratory (JPL) for combining independent measurements of the Earth' s orientation , is presented. Since changes in the Earth's orientation can be described as a randomly excited stochastic process, the uncertainty in our knowledge of the Earth's orientation grows rapidly in the absence of measurements. The Kalman-filter methodology allows for an objective accounting of this uncertainty growth, thereby facilitating the intercomparison of measurements taken at different epochs (not necessarily uniformly spaced in time) and with different precision. As an example of this approach to combining Earth-orientation series, a description is given of a combination, SPACE95, that has been generated recently at JPL. Title 2:Kalman-filtering with Coloured Measurement Noise for Deformation Analysis Abstract 2: Kalman filter is an important tool for deformation analysis combining information on object behaviour and measurement quantities. It is applicable to the four well-known deformation models. Kalman filtering usually requires white measurement and process noise. Due to electronic measurement devices with high sampling rate used nowadays, time dependent systematic deviations arise in neighbouring epochs in a similar way, resulting in auto-correlation. Especially in case of GPS measurements deviations due to multipath and signal propagation are changing slowly, and thus the assumption of white noise is not justified. To eliminate this deficiency within a shaping filter the state vector in Kalman filter is augmented and thus formulating an adequate noise process. In this paper the modification of Kalman-Filter algorithm with a shaping filter for coloured measurement noise is presented together with an example for deformation analysis using GPS measurements. The differences to an approach neglecting auto-correlation are shown.


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