臺灣博碩士論文加值系統

此篇論文將針對傳統室內定位方式的缺點去改善，並結合兩種傳統以收訊強度為基礎的室內定位不同方式的優點，一方面可以不需要預先大量的測量許多不同位置上的收訊強度，而是利用線上階段的訊號交集範圍的結果來做為訓練資料，另一方面可以隨著時間來增加精準度(降低誤差距離)。更重要的是，將針對訊號波動及障礙物的問題深入探討並設計為提出演算法中的一部份，在此稱作「以訊號交集為基礎之指紋辦識混合定位方法」。最後將經由實際建置觀測無線網路基地台及實作此定位系統來驗證這個方法。在實驗的過程，我們將會討論實際實作在真實環境下遇到的一些問題並比較提出的方法相較於傳統的方法的優缺點。

In this paper, we proposed a novel method that contains the advantages of two kinds of RSSI-based localization methods, RSSI Triangulation and RSSI Fingerprinting methods, to improve some disadvantages of traditional RSSI-based localization methods. The advantage of the former is that we could determine the possible region of the wireless device without collecting a large amount of training data and making a great training effort. However, in most case Triangulation method cannot determine the position of the user precisely and usually leads to a larger error distance. As for the latter, RSSI fingerprinting method wastes a lot of time and human resource to collect all possible RSSI in all possible regions. On the contrary, it always gets more precise result. This paper combines the advantage of these two schemes. The proposed scheme doesn’t have to pre-collect so much RSSI records and makes use of the results of signal coverage overlapping method as the input of RSSI fingerprinting method in the online phase.

CHAPTER 1: INTRODUCTION............................................1
1-1.Issues of Localization..............................1
1-2. Outdoor Localization...............................2
1-3. Indoor Localization................................4
CHAPTER 2: RELATED WORK.................................8
2-1. Angle of Arrival System(AOA System)................8
2-2. Time (Difference) of Arrival System...............10
2-3. Receive Signal Strength Indication System ........14
a. Triangulation Methods...............................15
b. Finger Printing Methods.............................20
CHAPTER 3: LOCALIZATION ALGORITHM......................21
3-1. Preliminary.......................................22
3-2. Observation.......................................31
3-3. Proposed Scheme Architecture......................33
3-4.Localization Algorithm.............................34
3-5.Weighted Localization Algorithm ...................41
CHAPTER 4: FIELD EXPERIMENTS ..........................45
4-1. Field Experiment in NCTU..........................45
4-2. Hardware & Software...............................46
4-3. Factors that Affects Experiments..................50
CHAPTER 5: EVALUATION..................................51
CHAPTER 6: CONCLUSION..................................57
Reference..............................................58

[1] http://en.wikipedia.org/wiki/Global_Positioning_System
[2] http://en.wikipedia.org/wiki/GPS_Phone
[3] http://en.wikipedia.org/wiki/Satellite_navigation_system
[4] Ekahau, Wifi Positioning Engine, http://www.ekahau.com/
[5] P. Rong and M.L. Sichitiu. “Angle of Arrival Localization for Wireless Sensor Networks,” in Proc. of Sensor and Ad Hoc Communications and Networks, 2006. vol. 1, pp. 374-382, Sept. 2006
[6] Nissanka B. Priyantha, Anit Chakraborty, and Hari Balakrishnan, “The Cricket Location-Support System,” 6th ACM International Conference on Mobile Computing and Networking (ACM MOBICOM), Boston, MA, August 2000
[7] P. Bahl and V. N. Padmanabhan, “RADAR: An In-Building RF-Based User Location and Tracking System,” in Infocom 2000, pp 775–784, 2000.
[8] http://en.wikipedia.org/wiki/Received_Signal_Strength_Indication
[9] S Meguerdichian, S Slijepcevic, V Karayan, “Localized algorithms in wireless ad-hoc networks: location discovery and sensor exposure,” Symposium on Mobile ad hoc networking & computing, 2001
[10] X Shen, JW and Mark, J Ye, “Mobile location estimation in cellular networks using fuzzy logic,” Vehicular Technology Conference, 2000. IEEE VTS-Fall VTC, Vol.5, Sept. 2000
[11] S Valaee, B Champagne, P Kabal, “Localization of wideband signals using least-squares and totalleast-squares approaches,” IEEE Transactions on Signal Processing, 1999
[12] TS Stamoulakatos, ED Sykas, “Hidden Markov modeling and macroscopic traffic filtering supporting location-based services, ” Wireless Communications and Mobile Computing, 2007
[13] LBreiman, JH Friedman, R Olshen,” Classification and regression trees,” 1984
[14] D-LINK Product : WiFi Wireless Access Point, DAP-1353 http://www.dlinktw.com.tw/product_view.asp?subMenuCode=&sno=LPFMHS
[15] B O’Hara, A Petrick, “The IEEE 802.11 Handbook: A Designer’s Companion,” 1999
[16] Mustafa Ergen Ergenm, “IEEE 802.11 Tutorial,” 1999
[17] Mangold, Berlemann, “QoS Support as Utility for Coexisting Wireless LANs,” 2002
[18] Bruce Potter, “802.11 Security,” O’Reilly & Associates Inc
[19] Nikita Borisov , Ian Goldberg , David Wagner, “Intercepting Mobile Communications: The Insecurity of 802.11,” Proceedings of the 7th annual international conference on Mobile computing and networking, 2001
[20] N. Cam-Winget, R Housley, D Wagner,Jesse Walker “Security flaws in 802.11 data link protocols,” Communications of the ACM ,Volume 46 , Issue 5 , May 2003
[21] X Yuan, OT Wright, H Yu, KA Williams, "Laboratory design for wireless network attacks," Proceedings of the 5th annual conference on Information security curriculum development, 2008
[22] K Swiat, " The travelling menace: rogue hotspots," Computer Fraud & Security, 2006
[23] http://www.aircrack-ng.org/doku.php?id=Airodump-ng
[24] PE Danielsson, "Euclidean distance mapping," Computer Graphics and image processing, 1980
[25] H Breu, J Gil, D Kirkpatrick, M Werman, "Linear time Euclidean distance transform algorithms," IEEE Transactions on Pattern Analysis and Machine, 1995
[26] I Ragnemalm (Linkoping Univ),"The Euclidean distance transform in arbitrary dimensions," International Conference on Image Processing and its Applications, 1992
[27] http://www.itl.nist.gov/div897/sqg/dads/HTML/euclidndstnc.html