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Motion Model for Positioning with Graph-Based Indoor Map

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

Julkaisun otsikon käännösMotion Model for Positioning with Graph-Based Indoor Map
AlkuperäiskieliEnglanti
Otsikko2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 27-30 Oct. 2014, Busan, South Korea
JulkaisupaikkaPiscataway, NJ
KustantajaIEEE
Sivut646-655
Sivumäärä10
ISBN (elektroninen)978-1-4673-8054-6
DOI - pysyväislinkit
TilaJulkaistu - 2015
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Conference on Indoor Positioning and Indoor Navigation -
Kesto: 1 tammikuuta 1900 → …

Conference

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

Tiivistelmä

This article presents a training-free probabilistic pedestrian motion model that uses indoor map information represented as a set of links that are connected by nodes. This kind of structure can be modelled as a graph. In the proposed model, as a position estimate reaches a link end, the choice probabilities of the next link are proportional to the total link lengths (TLL), the total lengths of the subgraphs accessible by choosing the considered link alternative. The TLLs can be computed off-line using only the graph, and they can be updated if training data are available. A particle filter in which all the particles move on the links following the TLL-based motion model is formulated. The TLL-based motion model has advantageous theoretical properties compared to the conventional models. Furthermore, the real-data WLAN positioning tests show that the positioning accuracy of the algorithm is similar or in many cases better than that of the conventional algorithms. The TLL-based model is found to be advantageous especially if position measurements are used infrequently, with 10-second or more time intervals.

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