Modern Global Navigation Satellite Systems (GNSS) are going to provide new signals with longer PRN codes and higher chipping rates, which aim to improve the positioning performance with respect to the current GPS. However, these new characteristics also cost GNSS receivers a high computational complexity. Due to their attractive acquisition time performance, matched filter (MF) correlators promise to be a good choice for GNSS signal acquisition engines. Existing methods to evaluate GNSS signal acquisition engine performance parameters, viz. detection probabilities and mean acquisition time, assume that the detections among the neighboring test cells are independent. However in a matched filter correlator, depending on the spacing between the test cells, due to the correlation of the local code with the noise component in the received signal at different time instances within a chip period, there can exist strong correlations, which affect these performance parameters. Also, the presence of cell correlations influences the acquisition threshold setting, which is a critical design parameter. This paper provides a detailed analysis of the significance of the cell-correlation phenomenon in MF correlators for the two widely used signal families in GNSS, namely BPSK and BOC, in particular BPSK(1) and BOC(1,1). Justifying the theoretical analysis with Monte Carlo simulations, it is shown that the maximum error in estimating the mean acquisition time without considering the cell-correlation phenomenon is shown to be about 10% for the BPSK(1) and about 12% for the BOC(1,1) signal.


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    Titel :

    Significance of Cell-Correlation Phenomenon in GNSS Matched Filter Acquisition Engines


    Beteiligte:
    Tung Hai Ta, (Autor:in) / Shivaramaiah, N. C. (Autor:in) / Dempster, A. G. (Autor:in) / Presti, L. L. (Autor:in)


    Erscheinungsdatum :

    2012-04-01


    Format / Umfang :

    12701150 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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