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題名 適用於大範圍的合作式定位方法
A large scale cooperative localization method
作者 鄧偉敦
Teng, Wei Tun
貢獻者 蔡子傑
Tsai, Tzu Chieh
鄧偉敦
Teng, Wei Tun
關鍵詞 定位
WiFi
全球定位系統
異質
合作
大範圍
localization
WiFi
GPS
heterogeneous
cooperative
large scale
日期 2010
上傳時間 4-Sep-2013 17:09:40 (UTC+8)
摘要 近來幾年智慧型手機和適地性服務已經變得非常熱門。 智慧型手機必須有辦法知道使用者的位置，因此精準的定位技術就變得重要。 至今人們只能夠在特定的環境利用某些定位方法，就像是GPS只能用於室外的空間。 但是人們總是生活於大範圍的環境像是校園、都市和觀光區，這種大範圍的環境包含了室內和室外的空間。
大範圍的環境下，單一定位技術未必到處都可用，因此我們結合了GPS、WiFi和物聯網定位提出了一個異質式定位演算法。 我們提出“定位可能性”來選擇比較“可靠”(可能)的定位方法。 除此之外，利用較可靠的鄰近使用者與自己之間的WiFi訊號強度可更進一步改善定位的精準度。特別針對某些使用者在沒有任何可用的定位方法時更有幫助。這個方法被稱為“合作式定位”。
最後，我們用模擬來評估我們演算法的精準度。 因為訊號強度每分每秒都在波動，因此我們測量實際的訊號強度和GPS放入模擬器，讓實驗結果變得更真實。 最後我們也證明我們的演算法可以做在手機上而且更精準。
Smart phones and Location Based Services (LBSs) have become very popular in recent years. To this end, the smart phone needs to know the locations of users. Therefore, an accurate localization technique is important. To date people can use some localization systems in some specific areas. For instance, GPS can only be used in the outdoor space. However, people always live in large scale environments like campus, urban and tourist areas. The large scale environments should include indoor and outdoor space.
For large scale environment, a single location technique is not always available everywhere. Therefore, we proposed a heterogeneous localization algorithm which combines GPS, WiFi and Internet Of Things (IOT) localizations. We proposed “localization possibility” for each localization methods. This algorithm use localization possibility to select the most “reliable” (possible) one. Besides, the more reliable nearby users can further enhance the localization by measuring the relative WiFi signal strength. It helps especially for those users who have no any available localization methods. This method is called “cooperative localization”.
Finally, we evaluated the accuracy of our algorithms by simulation. Because signal strength fluctuates from minute to minute, we measured empirical data and put into the simulator to make our experimental results more real. Finally, we also verify that our idea can be implemented on smart phones and our algorithm is more accurate.
參考文獻 [1] J. Hightower, R. Want, and G. Borriello, “SpotON: An indoor 3D location sensing technology based on RF signal strength,” Univ. Washington, Seattle, Tech. Rep. UW CSE 2000–02-02, Feb. 2000.
[2] L. M. Ni,Y. Liu,Y. C. Lau, and A. P. Patil, “LANDMARC: Indoor location sensing using active RFID,” Wireless Netw., vol. 10, no. 6, pp. 701–710, Nov. 2004.
[3] Bahl, P., Padmanabhan, V.N.: “Radar an in-building RF-based user location and tracking system.” In: INFOCOM 2000, Tel Aviv, Israel, pp. 775–784 (2000)
[4] M. Youssef and A. K. Agrawala, “Handling samples correlation in the Horus system,” IEEE INFOCOM 2004, Hong Kong, vol. 2, pp. 1023–1031, Mar. 2004.
[5] Ekahau, Inc. Ekahau Positioning Engine 2.0. http://www.ekahau.com/
[6] Haeberlen, A.; Flannery, E.; Ladd, A.; Rudys, A.; Wallach, D.;and Kavraki, L. “Practical robust localization over largescale 802.11 wireless networks.” In Proc. of the Tenth ACM International Conference on Mobile Computing and Networking 2004.
[7] H. Lemelson, S. Schnaufer and W. Effelsberg, “Automatic Identification of Fingerprint Regions for Quick and Reliable Location Estimation.” Pervasive Computing and Communications Workshops (PERCOM Workshops) 2010.
[8] Dik Lun Lee and Qiuxia Chen, “A Model-Based WiFi Localization Method”, The Hong Kong University of Science and Technology, INFOSCALE 2007 June 6-8, 2007, Suzhou, China, ACM 2007.
[9] R. Hansen and B Thomsen, “Efficient and Accurate WLAN Positioning with Weighted Graphs”, MOBILIGHT 2009, LNICST 13, pp. 372–386, 2009.
[10] O. Baala, Y. Zheng, A. Caminada. "The Impact of AP Placement in WLAN-Based Indoor Positioning System," Proceedings of the 8th International Conference on Networks, Cancun, Mexico, pp.12-17, 2009.
[11] P. Bolliger, K. Partridge, M. Chu, and M. Langheinrich. “Improving Location Fingerprinting through Motion Detection and Asynchronous Interval Labeling.” In Proc. Location and Context Awareness, pp. 37–51, Tokyo, Japan, May 2009.
[12] Bolliger, P.: Redpin – “adaptive, zero-configuration indoor localization through user collaboration.” In: Workshop on Mobile Entity Localization and Tracking in GPS less Environment Computing and Communication Systems (MELT), San Francisco(2008)
[13] V. Honkavirta, T. Perala, S. Ali-Loytty, and R. Piche. “A comparative survey of wlan location fingerprinting methods.” In Proc. 6th Workshop on Positioning, Navigation and Communication WPNC 2009, pp. 243–251, 2009.
[14] Hendrik Lemelson, Stephan Kopf, Thomas King, Wolfgang Effelsberg, "Improvements for 802.11-Based Location Fingerprinting Systems," compsac, vol. 1, pp.21-28, 2009 33rd Annual IEEE International Computer Software and Applications Conference, 2009
[15] Liu, H., H. Darabi, P. Banerjee, and J. Liu, "Survey of wireless indoor positioning techniques and systems," IEEE Transactions on systems, Man, and Cybernetics — Part C: Applications and Reviews, Vol. 37, No. 6, November 2007.
[16] Chan L-W, Chiang J-R, Chen Y-C, Ke C-N, Hsu J, Chu H-H (2006) “Collaborative localization—enhancing WiFi-based position estimation with neighborhood links in clusters.”, in Proceedings of the International conference on Pervasive Computing (PERVASIVE 2006), pp. 50–66
[17] N. Banerjee, S. Agarwal, P. Bahl, R. Chandra, A. Wolman, and M. Corner. “Virtual compass: relative positioning to sense mobile social interactions.” In Pervasive, 2010.
[18] ORBI positioning system. http://ssrc.nccu.edu.tw/orbi/
[19] News clip for ORBI. http://mag.udn.com/mag/digital/storypage.jsp?f_MAIN_ID=320&f_SUB_ID=4996&f_ART_ID=321825
[20] H. Lemelson, M. B. Kjærgaard, R. Hansen, and T. King. “Error Estimation for Indoor 802.11 Location Fingerprinting.” In Proc. Location and Context Awareness, pp. 138–155, Tokyo, Japan, May 2009.
描述 碩士
國立政治大學
資訊科學學系
98753038
99
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0098753038
資料類型 thesis
dc.contributor.advisor 蔡子傑zh_TW
dc.contributor.advisor Tsai, Tzu Chiehen_US
dc.contributor.author (Authors) 鄧偉敦zh_TW
dc.contributor.author (Authors) Teng, Wei Tunen_US
dc.creator (作者) 鄧偉敦zh_TW
dc.creator (作者) Teng, Wei Tunen_US
dc.date (日期) 2010en_US
dc.date.accessioned 4-Sep-2013 17:09:40 (UTC+8)-
dc.date.available 4-Sep-2013 17:09:40 (UTC+8)-
dc.date.issued (上傳時間) 4-Sep-2013 17:09:40 (UTC+8)-
dc.identifier (Other Identifiers) G0098753038en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/60258-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學學系zh_TW
dc.description (描述) 98753038zh_TW
dc.description (描述) 99zh_TW
dc.description.abstract (摘要) 近來幾年智慧型手機和適地性服務已經變得非常熱門。 智慧型手機必須有辦法知道使用者的位置，因此精準的定位技術就變得重要。 至今人們只能夠在特定的環境利用某些定位方法，就像是GPS只能用於室外的空間。 但是人們總是生活於大範圍的環境像是校園、都市和觀光區，這種大範圍的環境包含了室內和室外的空間。
大範圍的環境下，單一定位技術未必到處都可用，因此我們結合了GPS、WiFi和物聯網定位提出了一個異質式定位演算法。 我們提出“定位可能性”來選擇比較“可靠”(可能)的定位方法。 除此之外，利用較可靠的鄰近使用者與自己之間的WiFi訊號強度可更進一步改善定位的精準度。特別針對某些使用者在沒有任何可用的定位方法時更有幫助。這個方法被稱為“合作式定位”。
最後，我們用模擬來評估我們演算法的精準度。 因為訊號強度每分每秒都在波動，因此我們測量實際的訊號強度和GPS放入模擬器，讓實驗結果變得更真實。 最後我們也證明我們的演算法可以做在手機上而且更精準。		zh_TW
dc.description.abstract (摘要) Smart phones and Location Based Services (LBSs) have become very popular in recent years. To this end, the smart phone needs to know the locations of users. Therefore, an accurate localization technique is important. To date people can use some localization systems in some specific areas. For instance, GPS can only be used in the outdoor space. However, people always live in large scale environments like campus, urban and tourist areas. The large scale environments should include indoor and outdoor space.
For large scale environment, a single location technique is not always available everywhere. Therefore, we proposed a heterogeneous localization algorithm which combines GPS, WiFi and Internet Of Things (IOT) localizations. We proposed “localization possibility” for each localization methods. This algorithm use localization possibility to select the most “reliable” (possible) one. Besides, the more reliable nearby users can further enhance the localization by measuring the relative WiFi signal strength. It helps especially for those users who have no any available localization methods. This method is called “cooperative localization”.
Finally, we evaluated the accuracy of our algorithms by simulation. Because signal strength fluctuates from minute to minute, we measured empirical data and put into the simulator to make our experimental results more real. Finally, we also verify that our idea can be implemented on smart phones and our algorithm is more accurate.		en_US
dc.description.tableofcontents CHAPTER 1 Introduction 1
1.1 Background 1
1.2 Motivation 2
1.3 Organization 3
CHAPTER 2 Related Work 4
2.1 Collaborative localization [16] 6
2.2 Virtual Compass [17] 8
CHAPTER 3 Localization Algorithm 10
3.1 WiFi localization 10
3.2 Heterogeneous localization 16
3.3 Cooperative localization 22
CHAPTER 4 Experimental Evaluation 25
4.1 Simulation setup 25
4.2 Simulation result 31
4.3 Implementation setup 36
4.4 Implementation result 37
CHAPTER5 Conclusions 42
Reference 43		zh_TW
dc.format.extent 4676704 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0098753038en_US
dc.subject (關鍵詞) 定位zh_TW
dc.subject (關鍵詞) WiFizh_TW
dc.subject (關鍵詞) 全球定位系統zh_TW
dc.subject (關鍵詞) 異質zh_TW
dc.subject (關鍵詞) 合作zh_TW
dc.subject (關鍵詞) 大範圍zh_TW
dc.subject (關鍵詞) localizationen_US
dc.subject (關鍵詞) WiFien_US
dc.subject (關鍵詞) GPSen_US
dc.subject (關鍵詞) heterogeneousen_US
dc.subject (關鍵詞) cooperativeen_US
dc.subject (關鍵詞) large scaleen_US
dc.title (題名) 適用於大範圍的合作式定位方法zh_TW
dc.title (題名) A large scale cooperative localization methoden_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) [1] J. Hightower, R. Want, and G. Borriello, “SpotON: An indoor 3D location sensing technology based on RF signal strength,” Univ. Washington, Seattle, Tech. Rep. UW CSE 2000–02-02, Feb. 2000.
[2] L. M. Ni,Y. Liu,Y. C. Lau, and A. P. Patil, “LANDMARC: Indoor location sensing using active RFID,” Wireless Netw., vol. 10, no. 6, pp. 701–710, Nov. 2004.
[3] Bahl, P., Padmanabhan, V.N.: “Radar an in-building RF-based user location and tracking system.” In: INFOCOM 2000, Tel Aviv, Israel, pp. 775–784 (2000)
[4] M. Youssef and A. K. Agrawala, “Handling samples correlation in the Horus system,” IEEE INFOCOM 2004, Hong Kong, vol. 2, pp. 1023–1031, Mar. 2004.
[5] Ekahau, Inc. Ekahau Positioning Engine 2.0. http://www.ekahau.com/
[6] Haeberlen, A.; Flannery, E.; Ladd, A.; Rudys, A.; Wallach, D.;and Kavraki, L. “Practical robust localization over largescale 802.11 wireless networks.” In Proc. of the Tenth ACM International Conference on Mobile Computing and Networking 2004.
[7] H. Lemelson, S. Schnaufer and W. Effelsberg, “Automatic Identification of Fingerprint Regions for Quick and Reliable Location Estimation.” Pervasive Computing and Communications Workshops (PERCOM Workshops) 2010.
[8] Dik Lun Lee and Qiuxia Chen, “A Model-Based WiFi Localization Method”, The Hong Kong University of Science and Technology, INFOSCALE 2007 June 6-8, 2007, Suzhou, China, ACM 2007.
[9] R. Hansen and B Thomsen, “Efficient and Accurate WLAN Positioning with Weighted Graphs”, MOBILIGHT 2009, LNICST 13, pp. 372–386, 2009.
[10] O. Baala, Y. Zheng, A. Caminada. "The Impact of AP Placement in WLAN-Based Indoor Positioning System," Proceedings of the 8th International Conference on Networks, Cancun, Mexico, pp.12-17, 2009.
[11] P. Bolliger, K. Partridge, M. Chu, and M. Langheinrich. “Improving Location Fingerprinting through Motion Detection and Asynchronous Interval Labeling.” In Proc. Location and Context Awareness, pp. 37–51, Tokyo, Japan, May 2009.
[12] Bolliger, P.: Redpin – “adaptive, zero-configuration indoor localization through user collaboration.” In: Workshop on Mobile Entity Localization and Tracking in GPS less Environment Computing and Communication Systems (MELT), San Francisco(2008)
[13] V. Honkavirta, T. Perala, S. Ali-Loytty, and R. Piche. “A comparative survey of wlan location fingerprinting methods.” In Proc. 6th Workshop on Positioning, Navigation and Communication WPNC 2009, pp. 243–251, 2009.
[14] Hendrik Lemelson, Stephan Kopf, Thomas King, Wolfgang Effelsberg, "Improvements for 802.11-Based Location Fingerprinting Systems," compsac, vol. 1, pp.21-28, 2009 33rd Annual IEEE International Computer Software and Applications Conference, 2009
[15] Liu, H., H. Darabi, P. Banerjee, and J. Liu, "Survey of wireless indoor positioning techniques and systems," IEEE Transactions on systems, Man, and Cybernetics — Part C: Applications and Reviews, Vol. 37, No. 6, November 2007.
[16] Chan L-W, Chiang J-R, Chen Y-C, Ke C-N, Hsu J, Chu H-H (2006) “Collaborative localization—enhancing WiFi-based position estimation with neighborhood links in clusters.”, in Proceedings of the International conference on Pervasive Computing (PERVASIVE 2006), pp. 50–66
[17] N. Banerjee, S. Agarwal, P. Bahl, R. Chandra, A. Wolman, and M. Corner. “Virtual compass: relative positioning to sense mobile social interactions.” In Pervasive, 2010.
[18] ORBI positioning system. http://ssrc.nccu.edu.tw/orbi/
[19] News clip for ORBI. http://mag.udn.com/mag/digital/storypage.jsp?f_MAIN_ID=320&f_SUB_ID=4996&f_ART_ID=321825
[20] H. Lemelson, M. B. Kjærgaard, R. Hansen, and T. King. “Error Estimation for Indoor 802.11 Location Fingerprinting.” In Proc. Location and Context Awareness, pp. 138–155, Tokyo, Japan, May 2009.		zh_TW