Fuzzy inference with parameter identification for indoor WLAN positioning

M. Alakhras; M. Oussalah; M. I. Hussein

Fuzzy inference with parameter identification for indoor WLAN positioning

M. Alakhras, M. Oussalah, M. I. Hussein

Department of Electrical and Communication Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

This paper considers the fuzzy inference as position estimator for WLAN indoor environments, based on received signal strength measurements RSS. The proposal algorithm includes a fuzzy inference which uses the k-nearest neighbor classification in signal space, where the position of target node is calculated as a weighted combination of nearest fingerprints, where the weights are estimated using enhanced Takagi-Sugeno fuzzy controller with multivariable inputs and parameter identification with constrained optimization. The new developed technique is proposed to enhance the accuracy of position estimation in WLAN indoor environments.

Original language	English
Title of host publication	WCE 2015 - World Congress on Engineering 2015
Publisher	Newswood Limited
Pages	641-648
Number of pages	8
Volume	2217
ISBN (Electronic)	9789881925343
Publication status	Published - 2015
Event	2015 World Congress on Engineering, WCE 2015 - London, United Kingdom Duration: Jul 1 2015 → Jul 3 2015

Other

Other	2015 World Congress on Engineering, WCE 2015
Country/Territory	United Kingdom
City	London
Period	7/1/15 → 7/3/15

Keywords

Clustering
Fuzzy logic
RSS
WLAN indoor positioning

ASJC Scopus subject areas

Computer Science (miscellaneous)

Cite this

@inproceedings{dcad5e61e05d46f2a4dc670472c07c97,

title = "Fuzzy inference with parameter identification for indoor WLAN positioning",

abstract = "This paper considers the fuzzy inference as position estimator for WLAN indoor environments, based on received signal strength measurements RSS. The proposal algorithm includes a fuzzy inference which uses the k-nearest neighbor classification in signal space, where the position of target node is calculated as a weighted combination of nearest fingerprints, where the weights are estimated using enhanced Takagi-Sugeno fuzzy controller with multivariable inputs and parameter identification with constrained optimization. The new developed technique is proposed to enhance the accuracy of position estimation in WLAN indoor environments.",

keywords = "Clustering, Fuzzy logic, RSS, WLAN indoor positioning",

author = "M. Alakhras and M. Oussalah and Hussein, {M. I.}",

year = "2015",

language = "English",

volume = "2217",

pages = "641--648",

booktitle = "WCE 2015 - World Congress on Engineering 2015",

publisher = "Newswood Limited",

note = "2015 World Congress on Engineering, WCE 2015 ; Conference date: 01-07-2015 Through 03-07-2015",

}

TY - GEN

T1 - Fuzzy inference with parameter identification for indoor WLAN positioning

AU - Alakhras, M.

AU - Oussalah, M.

AU - Hussein, M. I.

PY - 2015

Y1 - 2015

N2 - This paper considers the fuzzy inference as position estimator for WLAN indoor environments, based on received signal strength measurements RSS. The proposal algorithm includes a fuzzy inference which uses the k-nearest neighbor classification in signal space, where the position of target node is calculated as a weighted combination of nearest fingerprints, where the weights are estimated using enhanced Takagi-Sugeno fuzzy controller with multivariable inputs and parameter identification with constrained optimization. The new developed technique is proposed to enhance the accuracy of position estimation in WLAN indoor environments.

AB - This paper considers the fuzzy inference as position estimator for WLAN indoor environments, based on received signal strength measurements RSS. The proposal algorithm includes a fuzzy inference which uses the k-nearest neighbor classification in signal space, where the position of target node is calculated as a weighted combination of nearest fingerprints, where the weights are estimated using enhanced Takagi-Sugeno fuzzy controller with multivariable inputs and parameter identification with constrained optimization. The new developed technique is proposed to enhance the accuracy of position estimation in WLAN indoor environments.

KW - Clustering

KW - Fuzzy logic

KW - RSS

KW - WLAN indoor positioning

UR - http://www.scopus.com/inward/record.url?scp=84991203883&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84991203883&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84991203883

VL - 2217

SP - 641

EP - 648

BT - WCE 2015 - World Congress on Engineering 2015

PB - Newswood Limited

T2 - 2015 World Congress on Engineering, WCE 2015

Y2 - 1 July 2015 through 3 July 2015

ER -

Fuzzy inference with parameter identification for indoor WLAN positioning

Abstract

Other

Keywords

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this