Statistical path loss parameter estimation and positioning using RSS measurements

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

    19 Citations (Scopus)
    17 Downloads (Pure)

    Abstract

    An efficient Bayesian method for off-line estimation of the position and the path loss model parameters of a base station is presented. Two versions of three different on-line positioning methods are tested using real data collected from a cellular network. The tests confirm the superiority of the methods that use the estimated path loss parameter distributions compared to the conventional methods that only use point estimates for the path loss parameters. Taking the uncertainties into account is computationally demanding, but the Gauss–Newton optimization methods is shown to provide a good approximation with computational load that is reasonable for many real-time solutions.
    Translated title of the contributionStatistical path loss parameter estimation and positioning using RSS measurements
    Original languageEnglish
    Title of host publicationUbiquitous Positioning, Indoor Navigation and Location-Based Services, UPINLBS, 3-4 October 2012, Helsinki
    Place of PublicationPiscataway, NJ
    PublisherIEEE
    Pages1-8
    Number of pages8
    ISBN (Electronic)978-1-4673-1909-6
    ISBN (Print)978-1-4673-1908-9
    DOIs
    Publication statusPublished - 2012
    Publication typeA4 Article in conference proceedings

    Publication series

    NameUbiquitous Positioning, Indoor Navigation and Location-Based Services

    Publication forum classification

    • No publication forum level

    Fingerprint

    Dive into the research topics of 'Statistical path loss parameter estimation and positioning using RSS measurements'. Together they form a unique fingerprint.

    Cite this