As wireless devices become more common, the ability to position a wireless
device has become a topic of importance. Accurate positioning through
technologies such as the Global Positioning System is possible for outdoor
environments. Indoor environments pose a different challenge, and research
continues to position users indoors. Due to the prevalence of wireless local
area networks (WLANs) in many indoor spaces, it is prudent to determine
their capabilities for the purposes of positioning. Signal strength and time
based positioning systems have been studied for WLANs. Direction or angle
of arrival (AOA) based positioning will be possible with multiple antenna
arrays, such as those included with upcoming devices based on the IEEE
802.11n standard. The potential performance of such a system is evaluated.
The positioning performance of such a system depends on the accuracy
of the AOA estimation as well as the positioning algorithm. Two different
maximum-likelihood (ML) derived algorithms are used to determine the
AOA of the mobile user: a specialized simple ML algorithm, and the space-
alternating generalized expectation-maximization (SAGE) channel parameter estimation algorithm. The algorithms are used to determine the error
in estimating AOAs through the use of real wireless signals captured in an
indoor office environment.
The statistics of the AOA error are used in a positioning simulation
to predict the positioning performance. A least squares (LS) technique as
well as the popular extended Kalman filter (EKF) are used to combine the
AOAs to determine position. The position simulation shows that AOA-
based positioning using WLANs indoors has the potential to position a
wireless user with an accuracy of about 2 m. This is comparable to other
positioning systems previously developed for WLANs. / Applied Science, Faculty of / Engineering, School of (Okanagan) / Graduate
| Identifer | oai:union.ndltd.org:UBC/oai:circle.library.ubc.ca:2429/2792 |
| Date | 11 1900 |
| Creators | Wong, Carl Monway |
| Publisher | University of British Columbia |
| Source Sets | University of British Columbia |
| Language | English |
| Detected Language | English |
| Type | Text, Thesis/Dissertation |
| Format | 2099293 bytes, application/pdf |
| Rights | Attribution-NonCommercial-NoDerivatives 4.0 International, http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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