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A comparative survey of WLAN location fingerprinting methods

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A comparative survey of WLAN location fingerprinting methods. / Honkavirta, V.; Perälä, T.; Ali-Löytty, S.; Piche, R.

Proceedings of the 6th Workshop on Positioning, Navigation and Communication 2009 WPNC'09, March 19, 2009, Hannover, Germany. 2009. p. 243-251.

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

Harvard

Honkavirta, V, Perälä, T, Ali-Löytty, S & Piche, R 2009, A comparative survey of WLAN location fingerprinting methods. in Proceedings of the 6th Workshop on Positioning, Navigation and Communication 2009 WPNC'09, March 19, 2009, Hannover, Germany. pp. 243-251.

APA

Honkavirta, V., Perälä, T., Ali-Löytty, S., & Piche, R. (2009). A comparative survey of WLAN location fingerprinting methods. In Proceedings of the 6th Workshop on Positioning, Navigation and Communication 2009 WPNC'09, March 19, 2009, Hannover, Germany (pp. 243-251)

Vancouver

Honkavirta V, Perälä T, Ali-Löytty S, Piche R. A comparative survey of WLAN location fingerprinting methods. In Proceedings of the 6th Workshop on Positioning, Navigation and Communication 2009 WPNC'09, March 19, 2009, Hannover, Germany. 2009. p. 243-251

Author

Honkavirta, V. ; Perälä, T. ; Ali-Löytty, S. ; Piche, R. / A comparative survey of WLAN location fingerprinting methods. Proceedings of the 6th Workshop on Positioning, Navigation and Communication 2009 WPNC'09, March 19, 2009, Hannover, Germany. 2009. pp. 243-251

Bibtex - Download

@inproceedings{2e054c0105674305beed527cc2434bb4,
title = "A comparative survey of WLAN location fingerprinting methods",
abstract = "The term “location fingerprinting” covers a wide variety of methods for determining receiver position using databases of radio signal strength measurements from different sources. In this work we present a survey of location fingerprinting methods, including deterministic and probabilistic methods for static estimation, as well as filtering methods based on Bayesian filter and Kalman filter. We present a unified mathematical formulation of radio map database and location estimation, point out the equivalence of some methods from the literature, and present some new variants. A set of tests in an indoor positioning scenario using WLAN signal strengths is performed to determine the influence of different calibration and location method parameters. In the tests, the probabilistic method with the kernel function approximation of signal strength histograms was the best static positioning method. Moreover, all filters improved the results significantly over the static methods.",
author = "V. Honkavirta and T. Per{\"a}l{\"a} and S. Ali-L{\"o}ytty and R. Piche",
note = "Contribution: organisation=mat,FACT1=1",
year = "2009",
language = "English",
isbn = "978-1-4244-3292-9",
pages = "243--251",
booktitle = "Proceedings of the 6th Workshop on Positioning, Navigation and Communication 2009 WPNC'09, March 19, 2009, Hannover, Germany",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - A comparative survey of WLAN location fingerprinting methods

AU - Honkavirta, V.

AU - Perälä, T.

AU - Ali-Löytty, S.

AU - Piche, R.

N1 - Contribution: organisation=mat,FACT1=1

PY - 2009

Y1 - 2009

N2 - The term “location fingerprinting” covers a wide variety of methods for determining receiver position using databases of radio signal strength measurements from different sources. In this work we present a survey of location fingerprinting methods, including deterministic and probabilistic methods for static estimation, as well as filtering methods based on Bayesian filter and Kalman filter. We present a unified mathematical formulation of radio map database and location estimation, point out the equivalence of some methods from the literature, and present some new variants. A set of tests in an indoor positioning scenario using WLAN signal strengths is performed to determine the influence of different calibration and location method parameters. In the tests, the probabilistic method with the kernel function approximation of signal strength histograms was the best static positioning method. Moreover, all filters improved the results significantly over the static methods.

AB - The term “location fingerprinting” covers a wide variety of methods for determining receiver position using databases of radio signal strength measurements from different sources. In this work we present a survey of location fingerprinting methods, including deterministic and probabilistic methods for static estimation, as well as filtering methods based on Bayesian filter and Kalman filter. We present a unified mathematical formulation of radio map database and location estimation, point out the equivalence of some methods from the literature, and present some new variants. A set of tests in an indoor positioning scenario using WLAN signal strengths is performed to determine the influence of different calibration and location method parameters. In the tests, the probabilistic method with the kernel function approximation of signal strength histograms was the best static positioning method. Moreover, all filters improved the results significantly over the static methods.

M3 - Conference contribution

SN - 978-1-4244-3292-9

SP - 243

EP - 251

BT - Proceedings of the 6th Workshop on Positioning, Navigation and Communication 2009 WPNC'09, March 19, 2009, Hannover, Germany

ER -