Gaussian Mixture Modeling for Location Positioning in Wireless LAN

碩士 === 輔仁大學 === 電子工程學系 === 93 === Location positioning techniques are getting important in mobile computing. A novel approach for the location determination by WLAN signal strength is proposed in this paper. Our method receives the RSSI signal strength from wireless access point. The probability dis...

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Main Authors: Li-Wei Liao, 廖立韡
Other Authors: Yuan-Kai Wang
Format: Others
Language:zh-TW
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/16676829045124817024
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spelling ndltd-TW-093FJU004280372015-10-13T11:39:44Z http://ndltd.ncl.edu.tw/handle/16676829045124817024 Gaussian Mixture Modeling for Location Positioning in Wireless LAN 以高斯混合模型進行無線區域網路之位置定位 Li-Wei Liao 廖立韡 碩士 輔仁大學 電子工程學系 93 Location positioning techniques are getting important in mobile computing. A novel approach for the location determination by WLAN signal strength is proposed in this paper. Our method receives the RSSI signal strength from wireless access point. The probability distribution of RSSI is statistically modeled by Gaussian mixture models. The modeling is achieved by expectation maximization. By the assumption of signal independence among access points, the computation of Gaussian mixture in three dimensions is greatly reduced. The signal model and the signal we real received is compared and more than 95% correctness is obtained. User location is determined by maximum likelihood. Yuan-Kai Wang 王元凱 2005 學位論文 ; thesis 73 zh-TW
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description 碩士 === 輔仁大學 === 電子工程學系 === 93 === Location positioning techniques are getting important in mobile computing. A novel approach for the location determination by WLAN signal strength is proposed in this paper. Our method receives the RSSI signal strength from wireless access point. The probability distribution of RSSI is statistically modeled by Gaussian mixture models. The modeling is achieved by expectation maximization. By the assumption of signal independence among access points, the computation of Gaussian mixture in three dimensions is greatly reduced. The signal model and the signal we real received is compared and more than 95% correctness is obtained. User location is determined by maximum likelihood.
author2 Yuan-Kai Wang
author_facet Yuan-Kai Wang
Li-Wei Liao
廖立韡
author Li-Wei Liao
廖立韡
spellingShingle Li-Wei Liao
廖立韡
Gaussian Mixture Modeling for Location Positioning in Wireless LAN
author_sort Li-Wei Liao
title Gaussian Mixture Modeling for Location Positioning in Wireless LAN
title_short Gaussian Mixture Modeling for Location Positioning in Wireless LAN
title_full Gaussian Mixture Modeling for Location Positioning in Wireless LAN
title_fullStr Gaussian Mixture Modeling for Location Positioning in Wireless LAN
title_full_unstemmed Gaussian Mixture Modeling for Location Positioning in Wireless LAN
title_sort gaussian mixture modeling for location positioning in wireless lan
publishDate 2005
url http://ndltd.ncl.edu.tw/handle/16676829045124817024
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