Kalman Filter Algorithm for Medium-Range Real-Time Kinematic Positioning with One Reference Station

In order to achieve real-time kinematic (RTK) accurate positioning for medium-range baselines and weaken the effects of double-difference tropospheric delay and ionospheric delay between stations and satellites, dry tropospheric delay was computed with the Hopfield model, while double-difference tropospheric wet delay was estimated with a relative tropospheric zenith delay (RTZD) parameter. The double-difference ionospheric delay was estimated with relative ionospheric zenith delay (RIZD) between two stations. A Kalman filter algorithm was proposed by taking position parameters, relative tropospheric zenith delay, relative ionospheric zenith delay and double-difference ambiguities as state variables to be estimated. The experimental results show that the proposed algorithm only needs a few of epochs to initialize, and the mean square error of one epoch is less than 2 and 5 cm in the horizontal and vertical directions, respectively.