Accurate carrier-phase integer ambiguity resolution is fundamental to high-precision global navigation satellite systems (GNSSs). Real-time GNSSs typically resolve the ambiguities by a combination of recursive estimators and integer least-squares solvers, which need to be reset when satellites are added or cycle slip occurs. In this article, we propose a mixture Kalman filter solution to integer ambiguity resolution. By marginalizing out the set of ambiguities and exploiting a likelihood proposal for generating the ambiguities, we can bound the possible values to a tight and dense set of integers. Thus, we extract the state and integer estimates from a mixture Kalman filter. The proposed approach yields an integrated method to detect cycle slip and initialize new satellites. Numerical analysis and experimental results indicate that the proposed method achieves reliable position estimates, repeatedly finds the correct integers in cases when other methods may fail, and is more robust to cycle slip.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Integer Ambiguity Resolution by Mixture Kalman Filter for Improved GNSS Precision


    Beteiligte:


    Erscheinungsdatum :

    01.08.2020


    Format / Umfang :

    1077153 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Integer Least-Squares Statistics for Three Frequency GPS/GNSS Ambiguity Resolution

    Teunissen, P. / American Institute of Aeronautics and Astronautics | British Library Conference Proceedings | 2000



    Improved HLLL Lattice Basis Reduction Algorithm to Solve GNSS Integer Ambiguity

    Kezhao Li / Chendong Tian / Yingxiang Jiao et al. | DOAJ | 2023

    Freier Zugriff

    Improved Integer Ambiguity Resolution Technique for Fixed Arrays

    Jonathan Wolfe / Jason Speyer | AIAA | 2005