利用長期無線區域網路訊號量測之精準室內定位系統

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：68

、訪客IP：3.147.27.210

姓名

李孟鑫(Meng-shin Li) 查詢紙本館藏

畢業系所

通訊工程學系

論文名稱

利用長期無線區域網路訊號量測之精準室內定位系統
(Precise Indoor Positioning System Using Long Term WLAN Signal Measurement)

相關論文

★ 利用智慧天線系統實現精準室內定位技術	★ 電力線通訊之競爭存取與路由方法設計與實現
★ 設計與實作基於GRAPES函式庫之P2P即時串流系統	★ 利用離散餘弦基礎之聲音浮水印達到室內定位技術
★ 利用虛擬指紋建置法之智慧型天線系統實現精準室內定位技術	★ 即時影像串流自適應播放系統之研究
★ 利用模糊邏輯控制器於蜂巢式網路降低位置管理機制成本	★ 基於支持向量機及模糊推理之地震預警系統研製
★ 基於行動裝置之分散式多人會議系統	★ 以分群為基礎之3D無線與光學網路晶片頻道存取方法
★ 基於收前先聽LBR機制之授權型輔助接入LAA架構下於異質網路中暴露節點之研究	★ 支援跳頻之IEEE 802.15.4 ZigBee無線隨身網路機制設計與實現
★ 應用於IEEE 802.16行動無線都會網路省電模式參數設定之智慧策略	★ IEEE 802.15.4 ZigBee 無線隨身網路高效能路由演算法分析與設計
★ 應用於IEEE 802.16無線寬頻都會網路之具調適性自動重傳請求回報機制	★ 無線感測網路為基礎之空間平面圖自動建構之技術

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

隨著全球衛星定位系統（GPS）與全球導航衛星系統（GLONASS）逐步增加新的頻段和更新衛星，以及伽利略（Galileo）、北斗二號（CNSS）、準天頂衛星系統（QZSS）與歐洲同步衛星導航覆蓋服務（EGNOS）等新興衛星導航的建置，全球導航衛星系統技術已日趨成熟。近幾年來全球導航衛星系統的存在也更為人所知，並已經逐漸成為全球最重要的導航系統。由於全球導航衛星系統接收器的成本大幅降低，其應用領域也越來越廣泛，也同樣刺激手機內建全球導航衛星系統接收器和定位服務的需求。如個人導航裝置(PND)及手機等產品都將全球衛星定位系統功能納入其中，希望能提供個人用戶多樣的行動定位服務(LBS)。
然而，當在建築物密集的都市範圍、室內區域或是存在非直視性傳輸 ( NLoS ) 的環境，因為任何一種衛星系統存著直視性傳輸 ( Line of Sight, LoS ) 限制，導致定位技術結果會嚴重降低定位的精準度。由於都會區無線區域網路基地台日益普及，過去已有諸多文獻採用廣為應用發展的無線區域網路 ( WLAN ) ，目前文獻的室內定位技術主要有無線區域網路(Wi-Fi)、藍芽(Bluetooth)、無線射頻辨識系統(RFID)、超音波以及超寬頻(UWB)等數種無線技術，這些技術均具可於非直視(NLoS)的條件下運作的特性，因此不會有室內接收不到訊號的問題。而本論文利用IEEE 802.11作為位置評估的解決方式。不幸地，不穩定的訊號強度，導致無線網路定位技術無法提供高精準度的結果，因此影響了實際定位用途，使得定位的設備或是用戶屢次引導錯誤的結果，而無法提供設備或是用戶所在的位置。為了解決這個問題，本論文以一個新穎的室內定位解決方式，提供高精準度的非即時位置的評估。
本論文針對不需要即時性定位的應用，例如儀器設備監控、固定家庭自動化感測器等，提出利用長時間量測之無線區域網路訊號來解決訊號強度的不穩定性並獲得精準定位資訊。

摘要(英)

With frequency channel expansion, device renovation of global positioning system (GPS) and global navigation satellite system (GLONASS), and the deployment of new satellite navigation such as global navigation satellite system (CNSS), quasi-zenith satellite system (QZSS) and European geostationary navigation overlay service (EGNOS), the outdoor positioning technology has become the well-known navigation system in the world. In recent years, GPS has become the most important navigation system in the world. Moreover, it stimulates the need of cell phone with build-in GPS module. Because the GPS technique is designed for personal navigation device (PND), cell phone and electronic products, and it can provide various kinds of location-based service (LBS) for users.
However, the accuracy of satellite-based positioning significantly degrades when the receiver is located in the urban area, i.e., the non-line-of-sight (NLoS) environment, or inside the building. In order to solve this problem, the widely deployed wireless network becomes a potential solution. There are many wireless technologies (e.g., Wi-Fi, Bluetooth, RFID and Ultra-wide-band) could support indoor positioning. This paper chooses IEEE 802.11 wireless local area network (WLAN) technology as the position estimating solution. Unfortunately, the WLAN-based positioning technology usually cannot provide accurate positioning results due to sophisticated environment. Hence the users are frequently misguided and unable to reach the place they want to get. In order to resolve this issue, we propose an indoor-positioning solution to obtain precisely estimated position, which is particularly used for non-real-time applications such as invaluable equipment property monitoring, fixed wireless measuring sensors and so on.
This paper proposes the methodology using long-term wireless measurement to prevent the issue of time variance of signal strengths. Therefore, the precise locations of monitored devices could be acquired.

關鍵字(中)

★ 直線性傳輸
★ 非直線性傳輸
★ 位置評估
★ 訊號強度

關鍵字(英)

★ Signal Strength
★ Wi-Fi
★ Signature
★ LoS
★ NLoS

論文目次

碩博士論文電子檔授權書 ..................................................................................................... i
摘要 ............................................................................................................................... ii
ABSTRACT ......................................................................................................................... iv
TABLE OF CONTENTS ...................................................................................................... vi
LIST OF FIGURES ............................................................................................................ viii
LIST OF TABLES ................................................................................................................. x
1. Introduction .................................................................................................................... 1
1-1 Development of Location Based Service (LBS) ...................................................... 1
1-2 RTLS and NRTLS .................................................................................................. 2
1-3 Problem Description ............................................................................................... 3
1-3-1 Instable Signal Strengths ..................................................................................... 3
1-3-2 LoS and NLoS .................................................................................................... 3
1-4 Thesis Organization ................................................................................................ 5
2. Related Works ................................................................................................................ 6
2-1 Estimation of Location Related Parameters ............................................................. 6
2-2 Global Position System – Trilateration.................................................................... 9
2-3 RADAR - Fingerprinting ...................................................................................... 10
2-4 Rule-based Location Method ................................................................................ 12
3. Long Term WLAN Signal Measurement Technology ................................................... 14
3-1 Experimental Testbed and Data Collection ........................................................... 14
3-2 Received Signal Strength Measurements with Averaging Method......................... 16
3-3 Eliminate Noise of RSS Using Kalman Filter ....................................................... 18
3-4 Identification and Analysis with NLoS and LoS and Post-processing Signal Strength Data .......................................................................................................................... 21
4. Location Estimation and Pattern Matching .................................................................... 28
5. Performance Evaluation ................................................................................................ 30
6. Conclusions .................................................................................................................. 37
References ........................................................................................................................... 38

參考文獻

[1] J. Caffery, Jr., and G. Stuber, “Subscriber location in CDMA cellular networks,” In Proceedings of IEEE Transactions on Vehicular Technology, vol. 47, pp. 406–416, August 2002.
[2] K. A. Grajski and E. Kirk, “Towards a Mobile Multimedia Age-Location-Based Services: A Case Study,” In Proceedings of Wireless Personal Communications, vol. 26, no. 2-3, pp. 105–116, August 2006.
[3] Location Technologies for GSM, GPRS and UMTS Network. White Paper of Snap Track Inc., USA, 2003.
[4] P. Castro, P. Chiu, T. Kremenek, and R. Muntz, “A Probabilistic Room Location Service for Wireless Networked Environments,” In Proceedings of International Conference on Ubiquitous Computing, vol. 2201, pp. 18–34, January 2001.
[5] J. J. Pan, Q. Yang, and S. J. Pan, “Online Co-Localization in Indoor Wireless Networks by Dimension Reduction,” In Proceedings of American Association for Artificial Intelligence, vol. 2, pp. 1102–1107, 2007.
[6] A. M. Ladd, K. E. Bekris, A. Rudys, L. E. Kavraki, and D. S. Wallach, “Robotics-Based Location Sensing Using Wireless Ethernet,” In Proceedings of Wireless Networks, vol. 11, no. 1-2, pp. 189–204, February 2005.
[7] J. Letchner, D. Fox, and A. LaMarca, “Large-scale localization from wireless signal strength,” In Proceedings of American Association for Artificial Intelligence, vol. 1, pp. 15–20, 2005.
[8] M. Fleck, M. Frid, T. Kindberg, E. OBrien-Strain, R. Rajani, and M. Spasojevic, “Rememberer: A Tool for Capturing Museum Visits,” In Proceedings of Ubiquitous Computing, vol. 2498, pp. 379–385, September 2002.
[9] B. Brown, I. MacColl, M. Chalmers, A. Galani, C. Randell, and A. Steed, “Lessons from the lighthouse: collaboration in a shared mixed reality system,” In Proceedings of ACM, pp. 577–585, April 2003.
[10] A. Madhavapeddy and A. Tse, “A Study of Bluetooth Propagation Using Accurate Indoor Location Mapping,” In Proceedings of Ubiquitous Computing, vol. 3660, pp. 105–122, August 2005.
[11] C.-Y. Chang, K.-P. Shih, C.-H. Hsu and H.-C. Chen, “Location-aware Multicasting Protocol for Bluetooth Location Networks,” In Proceedings of Information Sciences, vol.177, pp.3161–3177, 2007.
[12] R. Roberts, “IEEE P802.15 Wireless Personal Area Networks: Ranging Subcommittee Final Report,” Tech. Rep., Ranging Subcommittee of TG4a, 2004.
[13] K. W. Cheung, H. C. So, W.-K. Ma, and Y. T. Chan, “A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality,” In Proceedings of EURASIP, vol. 2006, pp.1–23, 2006.
[14] P. Bahl and V. N. Padmanabhan, “RADAR: An In-Building RF-BASED User Location and Tracking System,” In Proceedings of IEEE INFOCOM, vol. 2, pp. 775–784, March 2000.
[15] P. Castro, P. Chiu, T. Kremenek, and R. Muntz, “A Probabilistic Room Location Service for Wireless Networked Environments,” In Proceedings of Ubiquitous Computing, vol. 2201, pp. 18–34, 2001.
[16] A.-M. Ladd, K.-E. Bekris, A. Rudys, G. Marceau, L.-E. Kavraki, and D.-S. Wallach, “Robotics-Based Location Sensing Uses Wireless Ethernet,” In Proceedings of ACM International Conference on Mobile Computing and Networking, pp. 227–238, 2002.
[17] J. Letchner, D. Fox, and A. LaMarca, “Large-scale localization from wireless signal strength,” In Proceedings of American Association for Artificial Intelligence, vol. 1, pp. 15–20, 2005.
[18] S. R. Saunders, “Antennas and Propagation for Wireless Communication Systems Concept and Design,” tech. rep., New York, USA: John Wiley and Sons, 1999.
[19] S. Y. Seidel and T. S. Rapport, “914 MHz path loss prediction models for indoor wireless communications in multicolored buildings,” In Proceedings of Transactions on Antennas and Propagation, vol. 2, pp. 207–217, February 1992.
[20] “Android developers.” Available http://developer.android.com/sdk/index.html.
[21] Y. Bar-Shalom, X. R. Li, and T. Kirubarajan, Estimation with Application to Tracking and Navigation. New York: John Wiley and Sons, inc., 2001.
[22] E. Brookner, Tracking and Kalman Filtering Made Easy. New York: John Wiley and Sons, 1998.
[23] S. T. Sheu, M. S. Li, and Y. H. Tsai, “In-Door Long-Term Positioning Technology,” In Proceedings of CSCIST, July 2010.
[24] S. T. Sheu, M. S. Li, Y. H. Tsai and P. M. Lin, “In-door Wireless Positioning Technology,” In Proceedings of Chinacom, August 2010.
[25] Q. Chen, D.-L. Lee and W.-C. Lee, “Rule-Based WiFi Localization Methods,” In Proceedings of International Conference on Embedded and Ubiquitous Computing, vol. 1, pp. 252–258, January 2009.

指導教授

許獻聰(Shiann-Tsong Sheu)

審核日期

2010-7-26

推文