Dynamic Multipath Estimation by Sequential Monte Carlo Methods

Michael Lentmaier, Bernhard Krach, Thanawat Thiasiriphet

    Research output: Contribution to conferencePaper, not in proceedingpeer-review

    10 Citations (SciVal)

    Abstract

    : A sequential Bayesian estimation algorithm for multipath mitigation is presented, with an underlying movement model that is especially designed for dynamic channel scenarios. In order to facilitate efficient integration into receiver tracking loops it builds upon complexity reduction concepts that previously have been applied within Maximum Likelihood (ML) estimators. To demonstrate its capabilities under different GNSS signal conditions, simulation results are presented for both artificially generated random channels and high resolution channel impulse responses recorded during a measurement campaign.
    Original languageEnglish
    Pages1712-1721
    Publication statusPublished - 2007
    EventInternational Technical Meeting of the Institute of Navigation Satellite Division, (ION GNSS), 2007 - Forth Worth, TX, United States
    Duration: 2007 Sep 252007 Sep 28

    Conference

    ConferenceInternational Technical Meeting of the Institute of Navigation Satellite Division, (ION GNSS), 2007
    Country/TerritoryUnited States
    CityForth Worth, TX
    Period2007/09/252007/09/28

    Subject classification (UKÄ)

    • Electrical Engineering, Electronic Engineering, Information Engineering

    Keywords

    • GNSS
    • positioning
    • multipath mitigation

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