Designing robust carrier tracking algorithms that are operable in strident environmental conditions for global navigation satellite systems (GNSS) receivers is the discern task. Major contribution in weakening the GNSS signals are ionospheric scintillations. The effect of scintillation can be known by amplitude scintillation index S4 and phase scintillation index sf parameters. The proposed fuzzy logic based adaptive extended Kalman filter (AEKF) method helps in modelling the signal amplitude and phase dynamically by Auto-Regressive Exogenous (ARX) analysis using Sugeno fuzzy logic inference system. The algorithm gave good performance evaluation for synthetic Cornell scintillation monitor (CSM) data and real-time strong scintillated PRN 12 L1 C/A data on October 24th, 2012 around 21:30 h, Brazil local time collected by GNSS software navigation receiver (GSNR’x). Fuzzy logic algorithm is implemented for selecting the ARX orders based on estimated amplitude and phase ionospheric scintillation observations. Fuzzy based AEKF algorithm has the capability to mitigate ionospheric scintillations under both geomagnetic quiet and disturbed conditions.


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    Title :

    Fuzzy Logic-based Adaptive Extended Kalman Filter Algorithm for GNSS Receivers



    Publication date :

    2018-10-31


    Remarks:

    doi:10.14429/dsj.68.12313
    Defence Science Journal; Vol 68 No 6; 560-565 ; 0976-464X ; 0011-748X



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    DDC:    629 / 006




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