AbstractWith the development of Ambiguity Resolution for Precise Point Positioning (PPP-AR) over the past years, there are three representative PPP-AR methods up to now: Fractional Cycle Bias (FCB) method, Integer Recovery Clock (IRC) method and Decoupled Satellite Clock (DSC) method. In all these methods, satellite products are generated from a global or regional reference network and then broadcast to users for ambiguity fixing. Positioning accuracy with short-time observations can be significantly improved after ambiguities are correctly fixed; nevertheless, high-accuracy satellite products are the prerequisite of reliable ambiguity resolution. Therefore, quality control for PPP-AR at network end is of great significance. In this paper, FCB and IRC estimation methods based on Ionosphere-Free PPP (IF-PPP) and Uncombined PPP (U-PPP) are investigated. In addition, quality control strategy for FCB and IRC estimation is proposed. Data sets from International GNSS Service (IGS) network and CORSnet-NSW in Australia are used to validate and demonstrate the performance of the proposed method. The results indicate that reliable PPP-AR can be achieved with the estimated FCB and IRC products, similar PPP-AR performance is revealed with IF-PPP and U-PPP. After ambiguities are successfully fixed, positioning accuracy in the east, north and up directions can reach 0.7, 0.9 and 3.1cm, respectively, which is a considerable improvement as compared with ambiguity-float PPP solution. Moreover, the FCB method slightly outperforms the IRC method due to the better reliability of FCB estimation. In addition, accurate ionospheric delay can be derived from a regional reference network to enhance the model strength of U-PPP, thus the Time-To-First-Fix (TTFF) can be further shortened. Even instantaneous ambiguity fixing is achievable and the positioning accuracy can reach 0.1, 1.2 and 0.4cm.


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    Titel :

    Statistical analysis and quality control for GPS fractional cycle bias and integer recovery clock estimation with raw and combined observation models


    Beteiligte:
    Cheng, Shuyang (Autor:in) / Wang, Jinling (Autor:in) / Peng, Wenjie (Autor:in)

    Erschienen in:

    Advances in Space Research ; 60 , 12 ; 2648-2659


    Erscheinungsdatum :

    2017-06-28


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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