Multi-stage satellite phase and code bias estimation

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 multi-path 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.