Comprehensive survey of similarity measures for ranked based location fingerprinting algorithm

Georgy Minaev, Ari Visa, Robert Piche

    Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

    10 Sitaatiot (Scopus)
    201 Lataukset (Pure)

    Abstrakti

    Ranked Based Fingerprinting uses only ordering indices instead of actual Wi-Fi RSS values in order to make the algorithm insensitive to devices. A key component of the RBF algorithm is a similarity measure which is used to compare and find the closest ranked fingerprints. Previous papers study a few similarity measures; here we study 49 similarity measures in a test with a benchmark with publicly available indoor positioning database. For different similarity measures the positioning accuracy varies from 15.80 m to 55.22 m. The top 3 similarity measures are Lorentzian, Hamming and Jaccard. Hamming and Jaccard similarity measures have been studied in other papers while Lorenzian had not been studied with that kind of problems.
    AlkuperäiskieliEnglanti
    OtsikkoIndoor Positioning and Indoor Navigation (IPIN), 2017 International Conference on
    KustantajaIEEE
    Sivumäärä4
    ISBN (elektroninen)978-1-5090-6299-7
    DOI - pysyväislinkit
    TilaJulkaistu - 2017
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
    TapahtumaInternational Conference on Indoor Positioning and Indoor Navigation -
    Kesto: 1 tammik. 1900 → …

    Julkaisusarja

    Nimi
    ISSN (elektroninen)2471-917X

    Conference

    ConferenceInternational Conference on Indoor Positioning and Indoor Navigation
    Ajanjakso1/01/00 → …

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