Modified leaky LMS algorithms applied to satellite positioning

J. P. Montillet, Kegen Yu

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    6 Citations (Scopus)

    Abstract

    With the recent advances in the theory of fractional Brownian motion (fBm), this model is used to describe the position coordinate estimates of Global Navigation Satellite System (GNSS) receivers that have long-range dependencies. The Modified Leaky Least Mean Squares (ML-LMS) algorithms are proposed to filter the long time series of the position coordinate estimates, which uses the Hurst parameter estimates to update the filter tap weights. Simulation results using field measurements demonstrate that these proposed modified leaky least mean squares algorithms can outperform the classical LMS filter considerably in terms of accuracy (mean squared error) and convergence. We also deal with the case study where our proposed algorithms outperform the leaky LMS. The algorithms are tested on simulated and real measurements.

    Original languageEnglish
    Title of host publication2014 IEEE 80th Vehicular Technology Conference, VTC2014-Fall, Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781479944491, 9781479944491
    DOIs
    Publication statusPublished - 24 Nov 2014
    Event80th IEEE Vehicular Technology Conference, VTC 2014-Fall - Vancouver, Canada
    Duration: 14 Sept 201417 Sept 2014

    Publication series

    NameIEEE Vehicular Technology Conference
    ISSN (Print)1550-2252

    Conference

    Conference80th IEEE Vehicular Technology Conference, VTC 2014-Fall
    Country/TerritoryCanada
    CityVancouver
    Period14/09/1417/09/14

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