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Graph-Based Map Matching for Indoor Positioning

Tutkimustuotosvertaisarvioitu

Standard

Graph-Based Map Matching for Indoor Positioning. / Koivisto, Mike; Nurminen, Henri; Ali-Löytty, Simo; Piche, Robert.

10th International Conference on Information, Communications and Signal Processing (ICICS). IEEE, 2015.

Tutkimustuotosvertaisarvioitu

Harvard

Koivisto, M, Nurminen, H, Ali-Löytty, S & Piche, R 2015, Graph-Based Map Matching for Indoor Positioning. julkaisussa 10th International Conference on Information, Communications and Signal Processing (ICICS). IEEE, International Conference on Information, Communications and Signal Processing, 1/01/00. https://doi.org/10.1109/ICICS.2015.7459983

APA

Koivisto, M., Nurminen, H., Ali-Löytty, S., & Piche, R. (2015). Graph-Based Map Matching for Indoor Positioning. teoksessa 10th International Conference on Information, Communications and Signal Processing (ICICS) IEEE. https://doi.org/10.1109/ICICS.2015.7459983

Vancouver

Koivisto M, Nurminen H, Ali-Löytty S, Piche R. Graph-Based Map Matching for Indoor Positioning. julkaisussa 10th International Conference on Information, Communications and Signal Processing (ICICS). IEEE. 2015 https://doi.org/10.1109/ICICS.2015.7459983

Author

Koivisto, Mike ; Nurminen, Henri ; Ali-Löytty, Simo ; Piche, Robert. / Graph-Based Map Matching for Indoor Positioning. 10th International Conference on Information, Communications and Signal Processing (ICICS). IEEE, 2015.

Bibtex - Lataa

@inproceedings{916736f13a28456088df2589f8e3de31,
title = "Graph-Based Map Matching for Indoor Positioning",
abstract = "This article presents a probabilistic motion model that is based on an economical graph-based indoor map representation, such that the motion of the user is constrained according to the floor plan of a building. The floor plan is modeled as a combination of links and open space polygons that are connected by nodes. In the authors’ earlier work the link transition probabilities in this graph are proportional to the total link lengths that are the total lengths of the subgraphs accessible by choosing the considered link option, and this article extends this model to include open space polygons as well. A particle filter using the extended motion model in which all particles are constrained according to the map structure is presented. Furthermore, wireless local area network and Bluetooth Low Energy positioning tests show that the proposed algorithm outperforms comparison methods especially if the measurement rate is low.",
keywords = "Indoor positioning, particle filter, motion model, map matching, graph",
author = "Mike Koivisto and Henri Nurminen and Simo Ali-L{\"o}ytty and Robert Piche",
note = "ISBN of the USB proceedings. Will appear in IEEE Xplore. ORG=ase,0.8 ORG=mat,0.2",
year = "2015",
month = "12",
day = "1",
doi = "10.1109/ICICS.2015.7459983",
language = "English",
booktitle = "10th International Conference on Information, Communications and Signal Processing (ICICS)",
publisher = "IEEE",

}

RIS (suitable for import to EndNote) - Lataa

TY - GEN

T1 - Graph-Based Map Matching for Indoor Positioning

AU - Koivisto, Mike

AU - Nurminen, Henri

AU - Ali-Löytty, Simo

AU - Piche, Robert

N1 - ISBN of the USB proceedings. Will appear in IEEE Xplore. ORG=ase,0.8 ORG=mat,0.2

PY - 2015/12/1

Y1 - 2015/12/1

N2 - This article presents a probabilistic motion model that is based on an economical graph-based indoor map representation, such that the motion of the user is constrained according to the floor plan of a building. The floor plan is modeled as a combination of links and open space polygons that are connected by nodes. In the authors’ earlier work the link transition probabilities in this graph are proportional to the total link lengths that are the total lengths of the subgraphs accessible by choosing the considered link option, and this article extends this model to include open space polygons as well. A particle filter using the extended motion model in which all particles are constrained according to the map structure is presented. Furthermore, wireless local area network and Bluetooth Low Energy positioning tests show that the proposed algorithm outperforms comparison methods especially if the measurement rate is low.

AB - This article presents a probabilistic motion model that is based on an economical graph-based indoor map representation, such that the motion of the user is constrained according to the floor plan of a building. The floor plan is modeled as a combination of links and open space polygons that are connected by nodes. In the authors’ earlier work the link transition probabilities in this graph are proportional to the total link lengths that are the total lengths of the subgraphs accessible by choosing the considered link option, and this article extends this model to include open space polygons as well. A particle filter using the extended motion model in which all particles are constrained according to the map structure is presented. Furthermore, wireless local area network and Bluetooth Low Energy positioning tests show that the proposed algorithm outperforms comparison methods especially if the measurement rate is low.

KW - Indoor positioning

KW - particle filter

KW - motion model

KW - map matching

KW - graph

U2 - 10.1109/ICICS.2015.7459983

DO - 10.1109/ICICS.2015.7459983

M3 - Conference contribution

BT - 10th International Conference on Information, Communications and Signal Processing (ICICS)

PB - IEEE

ER -