Efficient differential code bias and ionosphere modeling and their impact on the network-based GPS positioning

One of the major error sources in using Global Positioning System (GPS) measurements for modeling the ionosphere is the receiver differential code bias (DCB). Therefore, the determination of the receiver DCB is important, and to date, it has been done mostly using the single-layer ionospheric model assumption. In this dissertation, a new and efficient algorithm using the geometry conditions between the satellite and the tracking receivers is proposed to determine the receiver DCB using permanent reference stations. In this method, an assumption that ionosphere is represented by a single-layer model is not required, which makes DCB computation independent on the pre-selected ionosphere model. In addition, this method is simple, accurate and computationally efficient. The principal idea is that the magnitude of the signal delay caused by the ionosphere is, under normal conditions, highly dependent on the geometric range between the satellite and the receiver. The proposed algorithm was tested with the Ohio Continuously Operating Reference Stations (CORS) and the Transantarctic Mountains Deformation (TAMDEF) sub-network data. The results show that quality comparable to the traditional DCB estimation method is obtainable with greater computational efficiency and simple algorithmic implementation.; Currently, fast and accurate long baseline positioning in both rapid-static and kinematic mode is a challenging topic, but positional accuracy can be improved with the help of the network-derived external ionospheric corrections. To provide not only ionospheric corrections, but also their variances, satellite-by-satellite interpolation for the ionospheric delays is performed using the least-squares collocation (LSC) method. Satellite-by-satellite interpolation has the advantage in that the vertical projection used in single-layer ionospheric model is not required. Also, more reliable user positioning and the corresponding accuracy assessment can be obtained by providing not only external ionospheric corrections but also their variances. The rover positioning with and without the external ionospheric delays in both rapid-static and kinematic mode was performed and analyzed. The numerical results indicate that the improvement in the positioning quality is achieved using the proposed method. A 23% improvement in mean time-to-fix was observed with the Ohio CORS network in the rapid-static mode, while a 27% improvement was obtained in the kinematic mode. With the Antarctic TAMDEF network, 10% and 18% improvements in mean time-to-fix in rapid-static and kinematic modes, respectively, were achieved. The improvement in the positioning quality of the TAMDEF network was relatively low because the number of stations in the network was not sufficient to properly capture the local variations of the ionosphere, which is more variable in a small scale, as compared to mid-latitudes.