Total Electron Content (TEC) is one of the most important factors in monitoring the variable structure of ionosphere. Global Positioning System (GPS) is a useful and affordable instrument in TEC prediction through ground receivers. In this research, Vertical Total Electron Content (VTEC) is calculated in a GPS station using code observations and an approach is introduced for precise, and local modeling of this quantity. For doing this, a geometry-free combination of P1 and P2 observables is made and TEC for every satellite in an epoch is obtained using this combination and Differential Code Biases (DCB) of satellite and receiver. The calculated parameter shows total electron content in the direction of signal propagation in ionosphere layer. Besides, a mapping function is used for transforming TEC to VTEC. For doing this transformation, there are various mapping functions the common examples of which are geometric mapping function and empirical mapping function. In order to increase the precision and reduce systematic errors of calculations, the geometric mapping function is used. After calculation of VTEC for every satellite, it is necessary to obtain the amount of VTEC in zenith direction of the station. For doing this, a weighted function is used that inversely relates to the elevation angle of the satellite. The proposed weighted function provides an optimum and precise formula for calculation of VTEC in zenith direction of the station. In order to investigate the accuracy of calculations, all of the results are compared with the VTEC grids of International GNSS Service (IGS), and finally, the conclusions for every specific method are shown like weighted average, normal average and nearest vertex. In other words, IGS ionospheric products are considered as accurate and precise VTEC and the results are compared with these VTECs. As everybody knows, IGS VTECs are produced in a grid and thus, for calculation of VTEC in a specific point, mathematical approaches like weighted average of VTECs in surrounded vertexes of the point should be used. Conclusions illustrate the calculation of VTEC using proposed approach has a good adaption with the weighted average of VTECs around the Ankara grid station. The other results are also illustrated in diagrams. In addition, the periodic behavior of ionosphere at different times are also modeled, and the method is improved for optimum estimation of VTEC at various times. The only thing that is important is the local nature of this method, which is useful in one cell of IGS ionospheric network only.

In high dynamic conditions, using vector tracking loops instead of scalar tracking loops in GPS receivers is proved as an efficient method to compensate the performance. The Minimum Mean Squared Error detector as a multiuser detector is applied in the vector tracking loop for more reliability and efficiency. The Kalman filter does the two tasks of tracking and extracting the navigation data after applying the multiuser detection on the correlator outputs. The covariance analysis is performed to study the effect of applying a multiuser detector along with a vector tracking loop against the conventional one. The covariance analysis is performed and the variance in the pseudorange-rate estimates produced by the two architectures of conventional vector tracking and the one with multiuser detector are used as the performance criteria. The steady state, state covariance of the Kalman filter of vector tracking loop is calculated. Comparing the psuedorange rate variances obtained from covariance analysis of each method shows improved performance of the new joint receiver of vector and multiuser detector.