Collaborative Localization: Enhancing WiFi-Based Position Estimation with Neighborhood Links in Clusters
碩士 === 國立臺灣大學 === 資訊工程學研究所 === 94 === Location-aware services can benefit from accurate and reliable indoor location tracking. The widespread adoption of 802.11x wireless LAN as the network infrastructure creates the opportunity to deploy WiFi-based location services with few additional hardware cos...
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ndltd-TW-094NTU053920422015-12-16T04:38:20Z http://ndltd.ncl.edu.tw/handle/82026265806196279991 Collaborative Localization: Enhancing WiFi-Based Position Estimation with Neighborhood Links in Clusters 合作定位:利用人群間鄰近連結改善無線網路定位系統之準確性 Ji-Rung Chiang 蔣季融 碩士 國立臺灣大學 資訊工程學研究所 94 Location-aware services can benefit from accurate and reliable indoor location tracking. The widespread adoption of 802.11x wireless LAN as the network infrastructure creates the opportunity to deploy WiFi-based location services with few additional hardware costs. While recent research has demonstrated adequate performance, localization error increases significantly in crowded and dynamic situations due to electromagnetic interferences. This paper proposes collaborative localization as an approach to enhance position estimation by leveraging more accurate location information from nearby neighbors within the same cluster. The current implementation utilizes ZigBee radio as the neighbor-detection sensor. This paper introduces the basic model and algorithm for collaborative localization. We also report experiments to evaluate its performance under a variety of clustering scenarios. Our results have shown 28.2-56% accuracy improvement over the baseline system Ekahau, a commercial WiFi localization system. 朱浩華 2006 學位論文 ; thesis 27 en_US |
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碩士 === 國立臺灣大學 === 資訊工程學研究所 === 94 === Location-aware services can benefit from accurate and reliable indoor location tracking. The widespread adoption of 802.11x wireless LAN as the network infrastructure creates the opportunity to deploy WiFi-based location services with few additional hardware costs. While recent research has demonstrated adequate performance, localization error increases significantly in crowded and dynamic situations due to electromagnetic interferences. This paper proposes collaborative localization as an approach to enhance position estimation by leveraging more accurate location information from nearby neighbors within the same cluster. The current implementation utilizes ZigBee radio as the neighbor-detection sensor. This paper introduces the basic model and algorithm for collaborative localization. We also report experiments to evaluate its performance under a variety of clustering scenarios. Our results have shown 28.2-56% accuracy improvement over the baseline system Ekahau, a commercial WiFi localization system.
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朱浩華 |
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朱浩華 Ji-Rung Chiang 蔣季融 |
author |
Ji-Rung Chiang 蔣季融 |
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Ji-Rung Chiang 蔣季融 Collaborative Localization: Enhancing WiFi-Based Position Estimation with Neighborhood Links in Clusters |
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Ji-Rung Chiang |
title |
Collaborative Localization: Enhancing WiFi-Based Position Estimation with Neighborhood Links in Clusters |
title_short |
Collaborative Localization: Enhancing WiFi-Based Position Estimation with Neighborhood Links in Clusters |
title_full |
Collaborative Localization: Enhancing WiFi-Based Position Estimation with Neighborhood Links in Clusters |
title_fullStr |
Collaborative Localization: Enhancing WiFi-Based Position Estimation with Neighborhood Links in Clusters |
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Collaborative Localization: Enhancing WiFi-Based Position Estimation with Neighborhood Links in Clusters |
title_sort |
collaborative localization: enhancing wifi-based position estimation with neighborhood links in clusters |
publishDate |
2006 |
url |
http://ndltd.ncl.edu.tw/handle/82026265806196279991 |
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