Received signal strength calibration for wireless local area network localization

Simple item page
dc.contributor.authorFelix, Diego
dc.contributor.supervisorMcGuire, Michael Liam
dc.date.accessioned2010-08-11T16:19:10Z
dc.date.available2010-08-11T16:19:10Z
dc.date.copyright2010en
dc.date.issued2010-08-11T16:19:10Z
dc.degree.departmentDepartment of Electrical and Computer Engineering
dc.degree.levelMaster of Applied Science M.A.Sc.en
dc.description.abstractTerminal localization for indoor Wireless Local Area Networks (WLAN) is critical for the deployment of location-aware computing inside of buildings. The purpose of this research work is not to develop a novel WLAN terminal location estimation technique or algorithm, but rather to tackle challenges in survey data collection and in calibration of multiple mobile terminal Received Signal Strength (RSS) data. Three major challenges are addressed in this thesis: first, to decrease the influence of outliers introduced in the distance measurements by Non-Line-of-Sight (NLoS) propagation when a ultrasonic sensor network is used for data collection; second, to obtain high localization accuracy in the presence of fluctuations of the RSS measurements caused by multipath fading; and third, to determine an automated calibration method to reduce large variations in RSS levels when different mobile devices need to be located. In this thesis, a robust window function is developed to mitigate the influence of outliers in survey terminal localization. Furthermore, spatial filtering of the RSS signals to reduce the effect of the distance-varying portion of noise is proposed. Two different survey point geometries are tested with the noise reduction technique: survey points arranged in sets of tight clusters and survey points uniformly distributed over the network area. Finally, an affine transformation is introduced as RSS calibration method between mobile devices to decrease the effect of RSS level variation and an automated calibration procedure based on the Expectation-Maximization (EM) algorithm is developed. The results show that the mean distance error in the survey terminal localization is well within an acceptable range for data collection. In addition, when the spatial averaging noise reduction filter is used the location accuracy improves by 16% and by 18% when the filter is applied to a clustered survey set as opposed to a straight-line survey set. Lastly, the location accuracy is within 2m when an affine function is used for RSS calibration and the automated calibration algorithm converged to the optimal transformation parameters after it was iterated for 11 locations.en
dc.identifier.bibliographicCitationD. Arora, D. Felix, and M. McGuire, "Reducing the error in mobile location estimation using robust window functions," in IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PacRim), August 2009.en
dc.identifier.bibliographicCitationD. Felix, E. Hyun, M. McGuire, M. Sima, "Denoising by Spatial Domain Averaging for Wireless Local Area Network Terminal Localization", in International Conference on Communications, Control and Signal Processing (ICCCSP), October 2010.en
dc.identifier.urihttp://hdl.handle.net/1828/2939
dc.languageEnglisheng
dc.language.isoenen
dc.rightsAvailable to the World Wide Weben
dc.subjectLocalizationen
dc.subjectWireless LANen
dc.subjectRobust statisticsen
dc.subjectHuber windowen
dc.subjectNoise Removalen
dc.subjectCalibrationen
dc.subjectHandset Localizationen
dc.subjectExpectation Maximizationen
dc.subject.lcshUVic Subject Index::Sciences and Engineering::Engineering::Electrical engineeringen
dc.titleReceived signal strength calibration for wireless local area network localizationen
dc.typeThesisen

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
FELIX_Diego_MASc_Thesis.pdf
Size:
548.42 KB
Format:
Adobe Portable Document Format
Description:
main thesis file
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.82 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Electronic Theses and Dissertations (ETD)
 
University of Victoria Libraries

We acknowledge and respect the Lək̓ʷəŋən (Songhees and Esquimalt) Peoples on whose territory the university stands, and the Lək̓ʷəŋən and W̱SÁNEĆ Peoples whose historical relationships with the land continue to this day.