Multi-Stage Satellite Phase and Code Bias Estimation

Abstract

Precise point positioning with satellite navigation signals requires knowledge of satellite code and phase biases. In this paper, a new multi-stage method is proposed for estimating of these biases using measurements from a geodetic network. The method first subtracts all available a priori knowledge on orbits, satellite clocks and multipath from the measurements to reduce their dynamics. Secondly, satellite phase biases, ionospheric delays, carrier phase integer ambiguities and the geometry combining all non-dispersive parameters are jointly estimated in a Kalman filter. Finally, the a posteriori geometry estimates are refined in a second Kalman filter for the computation of orbital errors, code biases and tropospheric delays. As the first Kalman filter introduces time correlation, a generalized Kalman filter for colored measurement noise is applied in the second stage. The proposed algorithm is applied to dual frequency GPS measurements from a local geodetic network in Germany. A remarkable bias stability with variations of less than 3 cm over 4 hours is observed.