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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43792完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 孫雅麗 | |
| dc.contributor.author | Yun-Chiao Sung | en |
| dc.contributor.author | 宋雲喬 | zh_TW |
| dc.date.accessioned | 2021-06-15T02:28:48Z | - |
| dc.date.available | 2009-08-21 | |
| dc.date.copyright | 2009-08-21 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-08-16 | |
| dc.identifier.citation | [1] T. Roos, P. Myllymki, H. Tirri, P. Misikangas, and J. Sievnen. “A probabilistic approach to wlan user location estimation.” International Journal of Wireless Information Networks, 9(3):155–164, July 2002.
[2] P. Bahl and V. N. Padmanabhan. “RADAR: An In-building RF-based User Location and Tracking System.” IEEE INFOCOM, 2:775--784, Mar 2000. [3] Gwon, Y., Jain, R., and Kawahara, T. “Robust Indoor Location Estimation of Stationary and Mobile Users”. INFOCOM ’04. Hong Kong, China. [4] Azadeh Kushki, Konstantinos N. Plataniotis,” Kernel-based Positioning in Wireless Local Area Networks” ,IEEE Transactions on Mobile Computing 2007 [5] Y. Gwon and R. Jain. “Error characteristics and calibration-free techniques for wireless lan-based location estimation.” In MobiWac ’04: Proceedings of the second international workshop on Mobility management & wireless access protocols, pages 2–9, Oct 2004. [6] R. Singh, L. Macchi, C. Regazzoni, and K. Plataniotis, “A statistical modeling based location determination method using fusion in WLAN,” in Proceedings of the International Workshop on Wireless Ad-hoc Networks, 2005. [7] Wang, Peter, Vauqhan, Wu.Chih-Hao “Mobile Location Analysis Using WLAN Measurements” Global Telecommunications Conference, Nov 2006. GLOBECOM ‘06.IEEE [8] Sachin Ganu ,A. S. Krishnakumar, P. Krishnan ,”Infrastructure-based location estimation in WLAN networks” , WCNC 2004 [9] Siddhartha Saha, Kamalika Chaudhuri, Dheeraj Sanghi, Pravin Bhagwat, “Location Determination of a Mobile Device Using IEEE 802.11b Access Point Signals” , WCNC 2003 - IEEE Wireless Communications and Networking Conference [10] Luis Felipe M. de Moraes and Bruno Astuto A. Nunes “Calibration-free WLAN location system based on dynamic mapping of signal strength “.Proceedings of the 4th ACM international workshop on Mobility management and wireless access 2006 [11] Emery, M. and Denko, M.K. “IEEE 802.11 WLAN Based Real-Time Location Tracking in Indoor and Outdoor Environments” Electrical and Computer Engineering, 2007 CCECE 2007. Canadian Conference [12] FCC: Guidelines for Testing and Verifying the Accuracy Wireless E911 Location Systems, April 12,2000, OET BULLETIN No.71 [13] R. Want, A. Hopper, V. Falcao, J. Gibbons. 'The Active Badge Location System,' ACM Transactions on Information Systems, Vol. 10, No. 1, January 1992, pp 91-102. (ORL Technical Report 92.1) [14] Nissanka B. Priyantha , Anit Chakraborty , Hari Balakrishnan, The Cricket location-support system, Proceedings of the 6th annual international conference on Mobile computing and networking, p.32-43, August 06-11, 2000, Boston, Massachusetts, United States [15] Paul Castro, Patrick Chiu, Ted Kremenek, Richard R. Muntz, “A Probabilistic Room Location Service for Wireless Networked Environments,” UbiComp ’01: Proceedings of the 3rd international conference on Ubiquitous Computing. [16] Inssider webpage, http://www.metageek.net/products/inssider [17] SAS webpage, http://www.sas.com/ [18] Weka webpage, http://www.cs.waikato.ac.nz/ml/weka/ [19] Paramvir Bahl and Venkata N. Padmanabhan, Enhancements to the RADAR User Location and Tracking System, Microsoft Research, February 2000, Technical Report MSR-TR-2000-12 [20] Clustering method research from Wikipedia | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43792 | - |
| dc.description.abstract | 在過去的十年間，定位研究逐漸發展為一項重要的研究領域，應用在許多地理資訊相關的服務應用上。GPS技術發明之後，室外環境的定位服務已經可以達到可接受的定位效能，然而在室內環境方面，大樓阻隔了GPS訊號與衛星之間的傳輸，因而使的定位效能不佳。許多技術開始被拿來研究發展於室內定位，其中，由於無線區域網路發展健全，具備普遍性與便利性，因此被拿來作為室內定位研究的主要技術。然而，由於室內環境的變異性大且複雜度高，存在不確定性的環境干擾，因此室內定位仍有相當大的困難需要克服。
在本篇論文研究中，我們在台大教學館三樓建立了一套基礎的無線區域網路定位系統，並且針對室內環境干擾的問題做分析研究。透過對環境分成不同的區塊以及參考使用者過去的移動資訊，我們提出了針對環境干擾的辨識以及修正的機制。經由大量的實驗證明，我們提出的機制可以有效的減少環境干擾所帶來的定位誤差，並且在複雜度高的室內環境提昇定位精準度。 | zh_TW |
| dc.description.abstract | In past decade, positioning-based service has become a crucial researching field in many location-aware applications. As the invention of GPS technology, positioning in outdoor receives quite an acceptable performance, but poor in indoor cause of blocking signal from the GPS satellite inside the building. Many technologies have been applied as the solution in indoor environment. WLAN-based system becomes the dominated researching direction in indoor positioning for the reason of wide availability and ubiquitous coverage in large environments. However, in indoor environment, there exists a lot of unpredicted environmental interference, which make the indoor positioning more difficult and decrease the positioning accuracy.
In this work, we establish a basic indoor WLAN positioning system, and focus on the problem of new environmental interference occurring in our target environment. We propose an interference-recognition and revision scheme with help of proposed radio-map sections and user tracking record for reducing the influence of environmental interference. From plenty of experiments, we demonstrate the effectiveness of our proposed scheme and improve the positioning accuracy in complex indoor environment. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T02:28:48Z (GMT). No. of bitstreams: 1 ntu-98-R96725014-1.pdf: 3948122 bytes, checksum: 289eef8479ca22f773bf96fc017b143f (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | Contents
謝詞 I Abstract II 中文摘要 III Contents A List of Figures C List of Tables D 1. Introduction 1 1.1 Background 1 1.2 Motivation 2 1.3 Goal 2 2. Related Work 4 3. Basic Indoor Positioning Experiment 9 3.1 Experiment Testbed 9 3.2 Indoor Positioning Process 11 3.2.1 Offline Phase 11 3.2.1.1 Environment Investigation 12 3.2.1.2 Choosing Survey Points 13 3.2.1.3 Calibration 14 3.2.1.4 Data Processing 17 3.2.2 Run-Time Phase 18 3.2.2.1 Real-Time RSS Sampling 19 3.2.2.2 Location Estimation 20 3.2.2.3 Location Prediction 22 3.3 Basic Performance Evaluation 22 4. Environmental Interference 25 4.1 Problem Description 25 4.2 Interference Types 26 5. Interference Recognition and Revision Scheme 28 5.1 Radio-Map Sections 28 5.1.1 PCA Clustering 29 5.1.1.1 Clustering Description 29 5.1.1.2 PCA Clustering Verification 32 5.1.2 K-Means Clustering 34 5.1.2.1 Clustering Description 34 5.1.2.2 K-Means Clustering Verification 35 5.2 Interference Recognition Scheme 38 5.2.1 Interference Recognition 40 5.2.1.1 Step 1 41 5.2.1.2 Step 2 42 5.2.1.3 Step 3 44 5.2.1.4 Step 4 46 5.2.2 Revise RSS Data 47 6. Performance Evaluation 49 7. Conclusion and Future Work 59 Reference 61 | |
| dc.language.iso | zh-TW | |
| dc.subject | 干擾修正 | zh_TW |
| dc.subject | 無線區域網路定位 | zh_TW |
| dc.subject | Radio-Map | zh_TW |
| dc.subject | 環境干擾 | zh_TW |
| dc.subject | 干擾辨識 | zh_TW |
| dc.subject | Environmental Interference | en |
| dc.subject | Interference Revision | en |
| dc.subject | Interference Recognition | en |
| dc.subject | WLAN-based positioning | en |
| dc.subject | Radio-Map | en |
| dc.title | 室內無線區域網路定位與環境擾動敏感度分析 | zh_TW |
| dc.title | Indoor Positioning in the WLAN Environment with Sensitive Analysis of Environmental Interference | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳孟彰,林盈達 | |
| dc.subject.keyword | 無線區域網路定位,Radio-Map,環境干擾,干擾辨識,干擾修正, | zh_TW |
| dc.subject.keyword | WLAN-based positioning,Radio-Map,Environmental Interference,Interference Recognition,Interference Revision, | en |
| dc.relation.page | 63 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2009-08-17 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| 顯示於系所單位： | 資訊管理學系 | |
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