الفهرس 
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Abstract
Global navigation satellite systems (GNSS) have been widely used in navigation and positioning in the last few decades. The techniques of GNSS and very long Baseline Interferometry (VLBI) offer geodesy the potential of estimating distances on the earth with uncertainties of few millimeters. Differential GPS combines group delay measurements at two broadly separated frequency bands to estimate instrument delay. Measurements of Global Positioning Satellite System receivers are affected by systematic offsets associated to grouping and phase delays of the signal generation and processing chain. One of the important significant factors affecting the ionosphere Total Electron Content evaluation accuracy is the hardware Differential Code Biases (DCB) present in both Global Positioning System satellites and receivers. The resulting code and phase biases rely on the transmission frequency and the in use signal modulation. The International GNSS Service (IGS) Analysis Centers have regularly provided DCB calculates for GNSS satellites and IGS ground receivers, but the DCBs for national and local network receivers are not provided. Most DCB estimates are found on the assumption that the DCB values of GPS satellites or receivers are steady over 1 day or 1 month while in fact they are often changing in hours or 1 day. The DCBs, as the interior delay difference between the two frequencies, have to be regarded as when estimating the accuracy positioning. Several meters of error can happen if the effect of the DCBs is ignored. Therefore, the DCBs should be estimated and removed for all GNSS application estimates and for all precise positioning applications. The DCB values differ between different GNSS satellites and ground receivers. DCB have three main components; the differential code bias of the satellite (SDCB) and receiver (RDCB) and the difference between delays on L1 and L2 frequencies. The current research concentrates on The RDCB and L1, L2 delay differences effect. The RDCB depends on the type of observation and the char¬acteristics of the hardware. The SDCB can be got using the International GNSS Service (IGS) analysis centers, but the RDCB for national and local network receivers are not provided. Therefore, estimating the RDCB accurately is a vital factor investigated by researchers. This thesis analyzes that GNSS receiver DCB and its effect on position es¬timation accuracy. The data from nine permanent GPS sites of the National Research Institute of Astronomy and Geophysics (NRIAG) were used for the estimation of the receiver DCB for Trimble 5700 and NetR5. Data analysis is carried out using Bernese software. To study the effect of DCB on the GPS coordinate’ accuracy, the data are processed using three different strategies. The first processing way is carried out using a special MATLAB code to estimate DCB. The estimated DCB values are considered as known input in Bernese. The second strategy uses Bernese software to estimate the DCB along with the local ionosphere. Ignoring the DCB in the solution is the third method. The results of the three strategies solutions are compared to find the best strategy. The criteria used here to evaluate the three solutions are based on ratio of ambiguity resolutions, standard deviations, error ellipse, closure errors, and root mean square errors. The results showed that the estimated mean value of the receiver differential code biases varied from -28 ns (nanosecond) to 39 ns. It is clear from the results that differential code biases values for Egyptian sites do not differ much with latitude and longitude, excluding at Aswan and Abu-Simpel. Differential code biases values enlarge gradually with increasing height. As for the effect of DCBs on positioning accuracy, the results indicate that the worst solution is obtained when ignoring the DCB. Both Bernese estimation and DCB estimated using M-code solutions are similar and gives good results. For example, the ratio of un-resolved ambiguity for baseline between Arish and Marsa-Alam is about 0.3096 for Bernese estimated DCB as it is about 0.5643 while ignoring DCB. Therefore it is suggested to consider the DCB when processing GPS data for precise applications.