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Noise Filtering Augmentation of the Helmert Transformation for the Mapping of GNSS-Derived Position Time Series to a Target Frame

  • Miltiadis Chatzinikos
  • Christopher Kotsakis
Part of the International Association of Geodesy Symposia book series (IAG SYMPOSIA, volume 147)

Abstract

The generation of position time series in geodetic networks is often based on the successive forward implementation of the Helmert transformation (HT) to daily/weekly solutions using the transformation parameters obtained from a separate least-squares adjustment over a selected set of reference stations. An overlooked problem with this approach is that the noise of the daily/weekly solutions is fully absorbed into the transformed station positions, or even amplified if we consider the additional uncertainty of the estimated Helmert parameters. Its filtering is therefore a desirable task which could enhance the geophysical content of geodetic time series to be analyzed in a global secular frame. To accommodate the need for such filtering, we present in this paper an epoch-wise stacking approach for the HT-based alignment of a series of daily/weekly frames to a common secular frame via an integrated estimation process. The resulting transformation formulae differ from the classic HT solution in terms of Kalman-like corrections, and they lead to an improved solution in the sense of minimizing the error variances of the transformed positions in the target frame.

Keywords

Daily/weekly solutions Frame alignment GNSS networks Helmert transformation Noise filtering Position time series 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Geodesy and SurveyingAristotle University of ThessalonikiThessalonikiGreece
  2. 2.Royal Observatory of BelgiumBrusselsBelgium

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