Abstract

Abstract. Gravity field models may be derived from kinematic orbit positions of Low Earth Orbiting satellites equipped with onboard GPS (Global Positioning System) receivers. An accurate description of the stochastic behaviour of the kinematic positions plays a key role to calculate high quality gravity field solutions. In the Celestial Mechanics Approach (CMA) kinematic positions are used as pseudo-observations to estimate orbit parameters and gravity field coefficients simultaneously. So far, a simplified stochastic model based on epoch-wise covariance information, which may be efficiently derived in the kinematic point positioning process, has been applied. We extend this model by using the fully populated covariance matrix, covering correlations over 50 min. As white noise is generally assumed for the original GPS carrier phase observations, this purely formal variance propagation cannot describe the full noise characteristics introduced by the original observations. Therefore, we sophisticate our model by deriving empirical covariances from the residuals of an orbit fit of the kinematic positions. We process GRACE (Gravity Recovery And Climate Experiment) GPS data of April 2007 to derive gravity field solutions up to degree and order 70. Two different orbit parametrisations, a purely dynamic orbit and a reduced-dynamic orbit with constrained piecewise constant accelerations, are adopted. The resulting gravity fields are solved on a monthly basis using daily orbital arcs. Extending the stochastic model from utilising epoch-wise covariance information to an empirical model, leads to a – expressed in terms of formal errors – more realistic gravity field solution.

Highlights

  • Various Low Earth Orbiting (LEO) satellites are equipped with a GNSS (Global Navigation Satellite System) receiver, which may be used for navigational purposes and Precise Orbit Determination (POD) and for gravity field recovery

  • We focus on kinematic positions derived from GRACE Global Positioning System (GPS) data to reconstruct orbits and estimate gravity fields simultaneously by applying the Celestial Mechanics Approach (CMA, Beutler et al, 2010)

  • Kinematic positions are widely used pseudo-observations in gravity field determination and their stochastic behaviour plays a crucial role when assessing the quality of gravity field solutions

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Summary

Introduction

Various Low Earth Orbiting (LEO) satellites are equipped with a GNSS (Global Navigation Satellite System) receiver, which may be used for navigational purposes and Precise Orbit Determination (POD) and for gravity field recovery. Kinematic orbit positions are obtained in a precise point positioning process (Švehla and Rothacher, 2005) They are widely used as pseudo-observations in the context of gravity field determination, first demonstrated by Gerlach et al (2003). We focus on kinematic positions derived from GRACE GPS data to reconstruct orbits and estimate gravity fields simultaneously by applying the Celestial Mechanics Approach (CMA, Beutler et al, 2010). A simplified stochastic model based on epoch-wise covariance information, derived in the kinematic point positioning process, has been applied in the CMA. We extend this model by using the fully populated covariance matrix as Jäggi et al (2011b) did, covering correlations over 50 min, and refine it by the use of empirical covariances based on the residuals of an orbit fit of the kinematic positions. Biased K-band range data are used as independent observations to validate the distance changes between the two GRACE satellites derived from the reconstructed orbits

Gravity field recovery
Stochastic noise modelling
Formal variance propagation
Epoch-wise covariance information
Covariance information over-arching epochs
Empirical covariances
Findings
Undifferenced ambiguity fixed positions
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