Signal Strength – Based Positioning Algorithm Using Gaussian Mixture Model for IEEE 802.11 WLAN

碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 93 === In the last decade, there has been a rapid growth in the area of Location-Based Service (LBS). LBS can actively push location-dependent information to mobile users according to their predefined profiles. Location system has been identified as an important comp...

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Bibliographic Details
Main Authors: Yueh-Tung Chen, 陳嶽東
Other Authors: Sheng-Tzong Cheng
Format: Others
Language:en_US
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/39598387333829292343
Description
Summary:碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 93 === In the last decade, there has been a rapid growth in the area of Location-Based Service (LBS). LBS can actively push location-dependent information to mobile users according to their predefined profiles. Location system has been identified as an important component of emerging mobile applications for a long time. The Global Positioning System (GPS) is currently the actual system for location sensing in outdoor wireless environments. However, GPS does not work well in indoor environments and requires dedicated hardware. Because of adopting the large number of existing wireless networks and requires no additional hardware, the proposed system is able to operate in outdoor environments as well as in indoor environments. The most popular Wireless Location Area Network (WLAN) technology nowadays based on the IEEE 802.11. WLAN has been widely deployed for LBS. In addition, most researches have focused on precise indoor location for IEEE 802.11 WLAN which adopt the received signal strength (RSS) that varies with location from different Access Points (APs). Because of the Radio Frequency (RF) signals are affected by noise, interference, multi-path effect and random movement in the environment, we introduce Gaussian Mixture Model (GMM) approximated signal propagation via EM algorithm to solve multi-path effect. The experiment demonstrates the effectiveness of proposed signal strength based Positioning algorithm.