Gaussian mixture filter allowing negative weights and its application to positioning using signal strength measurements

Philipp Muller, Simo Ali-Löytty, Marzieh Dashti, Henri Nurminen, Robert Piche

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

    7 Citations (Scopus)
    35 Downloads (Pure)

    Abstract

    This paper proposes a novel Gaussian Mixture Filter (GMF) that allows components with negative weights. In case of a ring-shaped likelihood function, the new filter keeps the number of components low by approximating the likelihood as a Gaussian mixture (GM) of two components, one with positive and the other with negative weight. In this article, the filter is applied to positioning with received signal strength (RSS) based range measurements. The filter is tested using simulated measurements, and the tests indicate that the new GMF outperforms the Extended Kalman Filter (EKF) in both accuracy and consistency.
    Translated title of the contributionGaussian mixture filter allowing negative weights and its application to positioning using signal strength measurements
    Original languageEnglish
    Title of host publicationProceedings of WPNC 2012, 9th Workshop on Positioning, Navigation and Communication, March 15-16, 2012, Dresden, Germany
    Place of PublicationPiscataway, NJ
    Pages71-76
    DOIs
    Publication statusPublished - 2012
    Publication typeA4 Article in a conference publication

    Publication series

    NameWorkshop on Positioning, Navigation and Communication

    Publication forum classification

    • No publication forum level

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