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    政大機構典藏 > 理學院 > 資訊科學系 > 學位論文 >  Item 140.119/32673
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/32673

    Title: 利用動態訊號資料庫以減少測量數之無線網路定位系統
    Reducing Calibration Effort for WLAN Locating System with Dynamic Radio Map
    Authors: 簡盧德
    Chien Lu,Te
    Contributors: 蔡子傑
    Chien Lu,Te
    Keywords: 定位
    signal strength
    radio map
    Date: 2007
    Issue Date: 2009-09-17 14:01:46 (UTC+8)
    Abstract: 隨著無線網路的興起,許多相關的研究議題也應運而生,利用無線網路(WLAN)對於使用者位置的判斷與追蹤就是其中相當熱門的一塊。經過近幾年的發展,室內WLAN定位誤差的進步空間已達到極限,其原因主要出在無線訊號傳播的物理性質所產生的侷限。然而,大部分擁有良好精準度的定位系統是建立在不切實際的人力成本上,故我們將著眼點放在如何減少收集大量訊號所耗費的人力,同時保持不錯的精準度。取得AP位置所消耗的人力資源也是我們考慮的一環。

    Following the raise of Wireless LAN networks, there are a lot of relative research issues in today’s life. Tracking and locating mobile users in RF-based WLAN (IEEE 802.11) is a very important issue in location-based applications area. The error distances of indoor WLAN locating was decreased to approximately 1.5 meter in recent years. However, the improvement in accuracy was limited due to the nature of radio propagation. Many researches which contain precise accuracy were based on an impractical effort of collecting too much signal data which we usually called “calibration” in this area. So this thesis focuses on how to reduce the calibration efforts without losing too much accuracy. Confirming the allocation of access points is another kind of calibration effort we concerned.

    As a consequence, we proposed a new locating system: first we calibrated few points and utilized inferring AP’s position and interpolation to complete radio map. During location estimation phase, radio map could be updated dynamically using learning mechanism modeled by HMM and other algorithms. In the experimental results, we proved our system maintained a comparable accuracy under reducing much calibration effort than other two locating systems. Besides, we analyzed the performance of our system with elder radio map and in two different experimental environments.
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    [2] P. Bahl, A. Balachandran, and V. Padmanabhan , “Enhancements to the RADAR user location and tracking system” ,Technical report, Microsoft Research, February 2000.
    [3] Isaac K Adusei and K.Kyamakya and Klaus Jobmann, “Mobile Positions Technologies in Cellular Networks: An Evaluation of their Performance Metrics”, in MILCOM 2002, Oct 2002, pp. 1239-1244.
    [4] Ali Taheri Arvinder Singh Emmanuel Agu, “Location Fingerprinting on Infrastructure 802.11Wireless Local Area Networks (WLANs) using Locus”, Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks (LCN’04).
    [5] Andreas Haeberlen, Eliot Flannery, Andrew M. Ladd, Algis Rudys, Dan S. Wallach, Lydia E. Kavraki, “Practical Robust Localization over Large-Scale 802.11 Wireless Networks”, MobiCom’04, Sept. 26-Oct. 1, 2004, Philadelphia, Pennsylvania, USA.
    [6] Ankur Agiwal, Parakram Khandpur, Huzur Saran, “LOCATOR - Location Estimation System For Wireless LANs”, WMASH’04, October 1, 2004, Philadelphia, Pennsylvania, USA.
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    [8] J. Krumm and J. C. Platt, “Minimizing calibration effort for an indoor 802.11 device location measurement system”, Technical report, Microsoft Research, 2003.
    [9] Ming-Hui Jin, Eric Hsiao-Kuang Wu, Yu-Ting Wang, Chin-Hua Hsu, “802.11-based Positioning System for Context Aware Applications”, Globecom2003.
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    [11] Moustafa A. Youssef, Ashok Agrawala, A. Udaya Shankar, “WLAN Location Determination via Clustering and Probability Distributions”, in IEEE PerCom’03.
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    [16] Tzu-Chieh Tsai, S-H Kao, and C-L Li, “In-building 802.11b Locating System Based on Wireless Channel Propagation Models”, in 10th Mobile Computing Workshop, 2004.
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    [23] X. Huang et. al., (2001) Spoken Language Processing, Chapter 8
    [24] Tzu-Chieh Tsai, Cheng-Lin Li, “Reducing Calibration Effort for WLAN Location System Using Segment Technique with Autocorrelation”, in IEEE ChinaCOMM, October 2006.
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    [27] M. berna, B. Lisien, B. Sellner, G. Gordon, F. Pfenning, and S. Thrun, “A learning algorithm for localizing people based on wireless signal strength that uses labeled and unlabeled data”, in IJCAI’03, Acapulco, Mexico, August 2003.
    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0094753002
    Data Type: thesis
    Appears in Collections:[資訊科學系] 學位論文

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