Detecting and processing Global Navigation Satellite System (GNSS) signals indoors and in urban canyons, have gained a great deal of attention due to the problems of very weak signals and hostile environments. The detection of GNSS signals is generally based on the application of a statistical test, derived from the maximum likelihood theory. The work presented here considers a new approach to the detection of weak GNSS signals using a Bayesian technique within a scenario where the search space size is already reduced to a few tens of cells using some kind of assisted information. The search space cells are considered as candidate cells, where each candidate cell is associated with a code delay and a Doppler frequency. For each candidate cell, a posteriori probability is propagated for a fixed number of operation cycles. At the end of the process, the maximum a posterior (MAP) criterion is used to select the correct cell. Simulation results are presented indicating that the proposed method provides a significant performance advantage over other reference schemes. They include a noncoherent integration scheme and another scheme which also utilizes the posterior probabilities as decision statistics but differs in the mechanism of probability propagation.


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    Titel :

    A novel acquisition strategy for weak GNSS signals based on map criterion


    Beteiligte:


    Erscheinungsdatum :

    2014-07-01


    Format / Umfang :

    1896175 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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