Bayesian-based localization in inhomogeneous transmission media: Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013

E. S. Nadimi; V. Blanes-Vidal; P. M. Johansen

doi:10.1145/2513228.2513291

Bayesian-based localization in inhomogeneous transmission media: Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013

E. S. Nadimi, V. Blanes-Vidal, P. M. Johansen

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review

Abstract

In this paper, we propose a novel robust probabilistic approach based on the Bayesian inference using received-signal-strength (RSS) measurements with varying path-loss exponent. We derived the probability density function (pdf) of the distance between any two sensors in the network with heterogeneous transmission medium as a function of the given RSS measurements and the characteristics of the heterogeneous medium. The results of this study show that the localization mean square error (MSE) of the Bayesian-based method outperformed all other existing localization approaches. © 2013 ACM.

Originalsprog	Engelsk
Titel	Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013
Antal sider	6
Forlag	Association for Computing Machinery
Publikationsdato	2013
Sider	226-231
ISBN (Trykt)	978-145032348-2
DOI	https://doi.org/10.1145/2513228.2513291
Status	Udgivet - 2013
Begivenhed	Research in Adaptive and Convergent Systems - Montreal, Canada Varighed: 1. okt. 2013 → 4. okt. 2013

Konference

Konference	Research in Adaptive and Convergent Systems
Land/Område	Canada
By	Montreal
Periode	01/10/2013 → 04/10/2013

Emneord

bayesian inference heterogeneous RF transmission medium wireless body-area sensor networks

Dokumenter og links

10.1145/2513228.2513291

http://www.scopus.com/inward/record.url?eid=2-s2.0-84891437561&partnerID=40&md5=d1a3ab5e83215b4d67f23af10fc8b428

SDU link

Tjek adgangen til materialet i Syddansk Universitetsbiblioteks søgemaskine

Citationsformater

Nadimi, E. S., Blanes-Vidal, V., & Johansen, P. M. (2013). Bayesian-based localization in inhomogeneous transmission media: Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013. I Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013 (s. 226-231). Association for Computing Machinery. https://doi.org/10.1145/2513228.2513291

@inproceedings{2ec1db2a50184d74a1b3be93d11f0f05,

title = "Bayesian-based localization in inhomogeneous transmission media: Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013",

abstract = "In this paper, we propose a novel robust probabilistic approach based on the Bayesian inference using received-signal-strength (RSS) measurements with varying path-loss exponent. We derived the probability density function (pdf) of the distance between any two sensors in the network with heterogeneous transmission medium as a function of the given RSS measurements and the characteristics of the heterogeneous medium. The results of this study show that the localization mean square error (MSE) of the Bayesian-based method outperformed all other existing localization approaches.",

keywords = "bayesian inference heterogeneous RF transmission medium wireless body-area sensor networks, bayesian inference, heterogeneous RF transmission medium, wireless body-area sensor networks",

author = "Nadimi, {E. S.} and V. Blanes-Vidal and Johansen, {P. M.}",

year = "2013",

doi = "10.1145/2513228.2513291",

language = "English",

isbn = "978-145032348-2",

pages = "226--231",

booktitle = "Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013",

publisher = "Association for Computing Machinery",

address = "United States",

note = "Research in Adaptive and Convergent Systems ; Conference date: 01-10-2013 Through 04-10-2013",

}

Nadimi, ES , Blanes-Vidal, V & Johansen, PM 2013, Bayesian-based localization in inhomogeneous transmission media: Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013. i Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013. Association for Computing Machinery, s. 226-231, Research in Adaptive and Convergent Systems, Montreal, Canada, 01/10/2013. https://doi.org/10.1145/2513228.2513291

Bayesian-based localization in inhomogeneous transmission media: Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013. / Nadimi, E. S.; Blanes-Vidal, V.; Johansen, P. M.
Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013. Association for Computing Machinery, 2013. s. 226-231.

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review

TY - GEN

T1 - Bayesian-based localization in inhomogeneous transmission media

T2 - Research in Adaptive and Convergent Systems

AU - Nadimi, E. S.

AU - Blanes-Vidal, V.

AU - Johansen, P. M.

PY - 2013

Y1 - 2013

N2 - In this paper, we propose a novel robust probabilistic approach based on the Bayesian inference using received-signal-strength (RSS) measurements with varying path-loss exponent. We derived the probability density function (pdf) of the distance between any two sensors in the network with heterogeneous transmission medium as a function of the given RSS measurements and the characteristics of the heterogeneous medium. The results of this study show that the localization mean square error (MSE) of the Bayesian-based method outperformed all other existing localization approaches.

AB - In this paper, we propose a novel robust probabilistic approach based on the Bayesian inference using received-signal-strength (RSS) measurements with varying path-loss exponent. We derived the probability density function (pdf) of the distance between any two sensors in the network with heterogeneous transmission medium as a function of the given RSS measurements and the characteristics of the heterogeneous medium. The results of this study show that the localization mean square error (MSE) of the Bayesian-based method outperformed all other existing localization approaches.

KW - bayesian inference heterogeneous RF transmission medium wireless body-area sensor networks

KW - bayesian inference

KW - heterogeneous RF transmission medium

KW - wireless body-area sensor networks

U2 - 10.1145/2513228.2513291

DO - 10.1145/2513228.2513291

M3 - Article in proceedings

SN - 978-145032348-2

SP - 226

EP - 231

BT - Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013

PB - Association for Computing Machinery

Y2 - 1 October 2013 through 4 October 2013

ER -

Bayesian-based localization in inhomogeneous transmission media: Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013

Abstract

Konference

Emneord

Dokumenter og links

SDU link

Fingeraftryk

Citationsformater