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A Comparison of Bayesian Localization Methods in the Presence of Outliers

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Otsikko2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017
KustantajaIEEE
Sivut1546-1551
Sivumäärä6
ISBN (elektroninen)9781509043729
DOI - pysyväislinkit
TilaJulkaistu - kesäkuuta 2017
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Wireless Communications and Mobile Computing Conference -
Kesto: 1 tammikuuta 2000 → …

Julkaisusarja

Nimi
ISSN (elektroninen)2376-6506

Conference

ConferenceInternational Wireless Communications and Mobile Computing Conference
Ajanjakso1/01/00 → …

Tiivistelmä

Localization of a user in a wireless network is challenging in the presence of malfunctioning or malicious reference nodes, since if they are not accounted for, large localization errors can ensue. We evaluate three Bayesian methods to statistically identify outliers during localization: an exact method, an expectation maximization (EM) method proposed earlier, and a new method based on Variational Bayesian EM (VBEM). Simulation results indicate similar performance for the latter two schemes, with the VBEM algorithm able to provide a statistical description of the user location, rather than an estimate as in the simpler EM case. In contrast to previous studies, we find that there is a significant gap between the approximate methods and the exact method, the cause of which is discussed.