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標題: 一個協同式無線裝置定位演算法之設計
A Collaborative Algorithm Design for Wireless Device Localization System
作者: 劉耀凱
Liu, Yao-Kai
關鍵字: RSS
access point
location determination
出版社: 資訊科學與工程學系所
引用: [1] A. Harter, A. Hopper, and P. Steggles, et al.(1999) The Anatomy of a Context-Aware application, in Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking, pp. 59-68. [2] N.B. Priyantha, A. Chakraborty, and H. Balakrishnan, (2000)The cricket location-support system, in the Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, ACM Press, pp. 32-43. [3] J. Werb, and C. Lanzl, (1998)Designing a Positioning System for Finding Things and People Indoors, IEEE Spectrum, Vol. 35, pp.71-78. [4] P.Bahl, V.N. Padmanabhan, and A. Balachandran (2000) Enhancements to the RADAR User Location and Tracking System, Microsoft Research Technical Report: MSR-TR-00-12. [5] P.Krishnan., A.S.Krishnakumar., Ju. Wen-Hua, Mallows. Colin, and Ganu. Sachin (2004) A System for LEASE: Location Estimation Assisted by Stationary Emitters for Indoor RF Wireless Networks, IEEE Infocom March, Vol. 2, pp.1001- 1011. [6] P. Krishnan., A.S.Krishnakumar. and Ganu. Sachin (2004) Infrastructure-based location estimation in WLAN networks, IEEE March, pp. 21-25. [7] P. Krishnan, A. S. Krishnakumar and Martin Kappes (2004) Estimating Signal Strength Coverage for a Wireless Access Points, IEEE CNF, Vol 5, pp. 3264 - 3269. [8] Marcu. Marius, Fuicu. Sebastian, Girban. Anania and Popa. Mircea (2007) Experimental Test Cases for Wireless Positioning Systems, IEEE September, pp. 530-537. [9] Gwon. Youngjune and Jain. Ravi (2004) Error Characteristics and Calibration-free Techniques for Wireless LAN-based Location Estimation, ACM Section 1, pp. 2-9. [10] [11] [12] Widyawan, Martin Klepal and St´ephane Beauregard.(2008) A Novel Backtracking Particle Filter for Pattern Matching Indoor Localization, ACM September, pp.79-83 [13] Widyawan, M. Klepal, and S. Beauregard. (2008) A backtracking particle filter for fusing building plans with pdr displacement data. In Proceedings of the 5th Workshop on Positioning, Navigation and Communication (WPNC 2008), Hannover, Germany, March 27 2008.
摘要: 由於無線網路的普及,運用無線網路訊號強度來定位無線裝置的系統,也越來越受到重視。然而,在定位系統的運作過程當中,無線訊號強度分佈圖(Radio Map)的資料如何有效取得始終是一個大問題。有些研究採用實地測量的方式,但這種方式需要非常大的人力,而且測出來的數據會受到實測點當時的環境影響;部份則採取訊號衰減的數學模型來推導訊號強度,但這樣的方式容易忽略環境的影響,其準確度不高。本研究提出一個協同式的無線裝置定位演算法,整合了實地測量及數學推導法的優點。在我們提出來的方法當中,系統布建的AP會去測量其它AP的訊號強度,藉此數據去動態調整訊號衰減方程式的環境參數。在預測無線裝置位置的階段,我們也發展了一個可以接受非理想訊號強度值的定位演算法,藉此提升定位的準確度。由於本系統需要所有布建AP的協同合作,因此我們將之命名為協同式的無線裝置定位演算法,預期在未來,將能替無線數位生活的應用,提供新的助力。
With the wide-spread deployment of wireless local area networks (WLAN), the location determination system based on WLAN has become a hot research area. Most WLAN localization systems are based on the received signal strength (RSS) and assume that RSS values have the same reliability. However, stronger RSS values are always more stable and have higher reliability. This study proposes a novel localization algorithm that can smartly utilize the reliability of RSS to improve the accuracy of localization. This thesis focuses on fundamental system deployment aspects of location estimation in 802.11-based wireless networks. Estimating the signal strength coverage of a wireless access point (AP), given its location at a site, is essential in many applications, e.g., for determining optimal AP placement. We use measurements from several fixed APs in a novel way to compute a signal coverage model for an AP at a random location. Our technique automatically takes into account the signal strength propagation characteristics of the site and also allows for an efficient deployment. We will present experimental results in the future that validate the practicality of the proposed technique.
其他識別: U0005-2507200919041400
Appears in Collections:資訊科學與工程學系所



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