الفهرس 
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Abstract
Introduction : Pseudorange multipath and noise mitigation is still a remaining problem in PPP solutions. If multipath and noise were well mitigated from the pseudoranges, the accurate estimates of float ambiguities will be achieved rapidly, thus there was a reduction in PPP convergence period. The research problem : Traditional PPP suffers from slow convergence that requires a long observation period for the solution reached a steady state or a specific accuracy. One of the slow convergence’s causes is the initialization of carrier phase ambiguities from imprecise and noisy pseudorange observations. If pseudorange observations were made more precise, they will rapidly constrain the carrier phase ambiguities, thus rapid convergence in PPP will be achieved. Pseudorange multipath and noise have the most destructive effect in PPP error budget. Research objectives : The main objective is Reduction of PPP convergence time by good management of pseudorange multipath and noise. Steps of study : Two different methods are used : (1) the multipath linear combination by TEQC software and (2) weighting scheme based on TEQC multipath observable. TEQC software is used to build multipath corrections based on the multipath observable for 7-day dataset from 75 IGS stations. The results indicate improvements in convergence time for 14 % and 28.5 % of the dataset using the multipath observable method and the weighting based on the multipath observable, respectively. The study concludes : Mitigation of pseudorange multipath and noise by functional and stochastic modelling results in good initialization of carrier-phase ambiguities which in turn improves PPP convergence period. Cycle slips has a great impact on the proposed methods therefore, it will more attention in future work.