跳到主要內容

臺灣博碩士論文加值系統

(34.204.180.223) 您好!臺灣時間:2021/08/01 17:14
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:詹富凱
研究生(外文):Fu-Kai Chan
論文名稱:應用模糊粒子濾波演算法於行動感測網路之定位技術研究
論文名稱(外文):Fuzzy Particle Filter for Distributed Positioning in Mobile Wireless Sensor Networks
指導教授:溫志煜
學位類別:碩士
校院名稱:國立中興大學
系所名稱:電機工程學系所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2010
畢業學年度:98
語文別:英文
論文頁數:48
中文關鍵詞:無線感測網路模糊控制粒子濾波器
外文關鍵詞:Wireless Sensor Networksfuzzy controlParticle Filtering
相關次數:
  • 被引用被引用:0
  • 點閱點閱:101
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
近年來無線感測網路自我感知定位系統已經漸漸在我們日常生活中扮演相當重要的角色。本篇研究論文提出一個可應用於直視性(line-of-sight)環境下之分散式定位系統。此系統利用分散式訊號處理與網路的擴充性做為定位基礎。在運算過程中,不需要使用到含有GPS功能的感測器,只需利用感測器訊號間距離與角度資訊(TOA/AOA)來進行錯誤校正與定位估計。在定位完之後,我們使用模糊理論來降低定位上的誤差。這篇論文闡述了定位方法的建立,也詳加考慮現實環境應用的可能性,同時藉由模擬與數值分析來驗證與探討其演算法之可行性。

Location-awareness is crucial and becoming increasingly important to many applications in wireless sensor networks. This paper presents a network-based positioning system and outlines recent work in which we have developed an efficient principled approach to localize a mobile sensor using an TOA/AOA hybrid positioning scheme employing multiple seeds in the line-of-sight scenario. Based on the initial position estimate, a fuzzy algorithm is used to reduce positioning error. The proposed algorithm exploits the information flow while coping with distributed signal processing and the requirements of network scalability. The feasibility of the proposed scheme is shown to be effective under certain assumptions and the analysis is supported by simulation and numerical studies.

1. INTRODUCTION 1
2. LITERATURE REVIEW 4
3. MOBILE POSITIONING SYSTEM 5
3.1. Signal Measurement 5
3.1.1. Non-Line-of Sight (NLOS) problem 6
3.1.2. Maximum Likelihood Algorithm 6
3.1.3. Selective NLOS based technique 8
3.2. AOA-aided TOA Positioning Algorithm (ATPA) 9
3.2.1. AOA-Aided TOA Measurement 10
3.2.2. Geometrical Positioning with Particle Filtering 12
3.3. Cramer-Rao Lower Bound 15
3.3.1. Cramer-Rao Lower Bounds of TDOA 15
3.3.2. Cramer-Rao Lower Bounds of TOA 17
3.3.3. Cramer-Rao Lower Bounds of Joint TOA/AOA 17
3.4. Adaptive Fuzzy Control 19
3.4.1. Fuzzy Control Method 20
3.4.2. Gradient Descent Learning 22
3.4.3. Constructive Fuzzy Rules 24
3.4.4. Defuzzifier Method 26
4. SIMULATION AND NUMERICAlL RESULTS 27
4.1. Result of AOA-aided TOA Positioning Algorithm 27
4.1.1. The Effect of Mobility 27
4.1.2. The Effect of Uncertainty of Angle Estimation 29
4.1.3. The Effect of Measurement Noise of Distance Estimation 31
4.1.4. The Effect of Number of Seeds 32
4.2. Result of Adaptive Fuzzy Control Algorithm 34
4.2.1. Comparison Between MCMC and Adaptive Fuzzy Control Algorithm (using AOA/TOA to localize target) 35
4.2.2. Comparison Between MCMC and Adaptive Fuzzy Control Algorithm (using TOA to localize target) 36
5. CONCLUSION AND FEATURE WORKS 45
REFERENCES 46


[1] Y. T. Chan, H. Y. C. Hang, and P. C. Ching, “Exact and approximate maximum
likelihood localization algorithms,” IEEE Trans. Veh. Technol., vol. 55, no. 1, pp.
10-16, Jan. 2006.
[2] C. Cheng and A. Sahai, “Estimation bounds for localization,” in Proc. IEEE Int. Conf. Sensor and Ad-Hoc Communications and Networks (SECON), Santa Clara, CA, Oct. 2004, pp. 415-424
[3] I. Guvenc and C. C. Chong, “A Survey on TOA Based Wireless Localization and NLOS Mitigation Techniques,” in IEEE Communications Surveys and Tutorials, no. 3, July 2009.
[4] P. Zou, Z. Huang, J.Lu, “Passive Stationary Target Positioning Using Adaptive Particle Filter with TDOA and FDOA Measurements,” in IEEE Communication and 5th International Symposium. pp. 435-465. 2004.
[5] P.N. Pathirana, N. Bulusu, A.V. Savkin, and S. Jha, “Node Localization Using Mobile Robots in Delay-Tolerant Sensor Networks,” IEEE Trans. on Mobile Computing, vol. 4, no. 3, pp. 285-296, 2005.
[6] M. Sichitiu and V. Ramadurai, “Localization of Wireless Sensor Networks with a Mobile Beacon,” in Proc. of the 1st IEEE MASS, 2004.
[7] L. Hu and D. Evans, “Localization for Mobile Sensor Networks,” in Proc. of the 10th ACM MobiCom, 2004.
[8] R. Cesbron and R. Arnott, “Locating GSM mobiles using antenna array,” Electron. Lett., vol. 34, pp. 1539-1540, Aug. 1998.
[9] H. C. So and E. M. K. Shiu, “Performance of TOA-AOA hybrid mobile location,” IEICE Trans. Fundamentals, vol. E86-A, no. 8, pp. 2136-2138, Aug. 2003.
[10] P. Deng and P.-Z. Fan, “An AOA assisted TOA positioning system,” Proc. International Conference on Communication Technology, vol. 2, pp. 1501-1504, 2000.
[11] S. Venkatraman, J. Caffery, Jr., and H.-R. You, “A novel ToA location algorithm using LoS range estimation for NLoS environments,” IEEE Transactions on Vehicular Technology, vol. 53, no. 5, pp. 1515-1524,2004.
[12] N. Deligiannis, S. Louvros, and S. Kotsopoulos, “Optimizing Location Positioning Using Hybrid TOA-AOA Techniques in Mobile Cellular Networks,” Proc. of Mobimedia’07, Aug. 2007.
[13] Y.-T. Chan, W.-Y. Tsui, H.-C. So, and P.-C. Ching, “Time-of-arrival based localization under NLOS conditions,” IEEE Transactions on Vehicular Technology, vol. 55, no. 1, pp. 17-24, 2006.
[14] F. Gustafsson and F. Gunnarsson, “Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements,” IEEE Signal Processing Magazine, vol. 22, no. 4, pp. 41-53, 2005.
[15] A. H. Sayed, A. Tarighat, and N. Khajehnouri, “Network-based wireless location: challenges faced in developing techniques for accurate wireless location information,” IEEE Signal Processing Magazine, vol. 22, no. 4, pp. 24-40, 2005.
[16] J. Luo, H. V. Shukla, J.-P. Hubaux, “Non-Interactive Location Surveying for Sensor Networks with Mobility-Differentiated TOA,” in Proc. of the 25th IEEE INFOCOM, April 2006.
[17] H. Tang, Y.-W. Park, and T.-S. Qiu, “A TOA-AOA-Based NLOS Error Mitigation Method for Location Estimation,” EURASIP Journal on Advances in Signal Processing, vol. 8, Article ID 682528, 14 pages, 2008.
[18] C.-Y. Wen, R. D. Morris, and W. A. Sethares, “Distance Estimation Using Bidirectional Communications Without Synchronous Clocking,” IEEE Transactions on Signal Processing, vol. 55, no. 5, pp. 1927-1939, May 2007.
[19] N. J. Gordon, D. J. Salmond, A. F. M. Smith, “Novel approach to nonlinear/non-Gaussian Bayesian state estimation,” IEEE Proceedings For Radar and Signal Processing, Vol. 12, No. 2, pp. 107-113, Apr. 1993.
[20] J. Hightower and G. Borriello, “Particle Filters for Location Estimation in Ubiquitous Computing: A Case Study,” in Proc. of the Sixth International Conference on Ubiquitous Computing, pp. 88-106, Sep. 2004.
[21] R. Ware and F. Lad, “Approximating the Distribution for Sum of Product of Normal Variables,” the research report of the Mathematics and Statistics department at Canterbury University, 2003.
[22] R. Parthiban and A. Menon, “A Fuzzy Logic Algorithm for Minimizing Error (FLAME) in Wireless Sensor Networks,” Proc. IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Singapore, paper FA3.5, July, 2009
[23] Y. Shi, M. Mizumoto, N. Yubazaki, M. Otani A, “learning algorithm for tuning fuzzy rules based on the gradient descent method, ” Proceedings of the Fifth IEEE International Conference on Fuzzy Systems (FUZZ-IEEE''96), New Orleans, USA, Vol.1, pp.55-61, 1996 (with, and).
[24] S. Chib and E. Greenberg, “Understanding the Metropolis-Hastings algorithm,” The American Statistician 49: 327-335, 1995.


QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
1. 簡茂發(1981)。我國國小及國中學生的智力發展。教育心理學報,14,125-148。
2. 林建豪(2006)國小學童身體質量指數、身體型態、基本運動能力與學業成績之相關研究。嘉大體育健康休閒期刊,5,96-109。
3. 蔡忠昌、劉蕙綾(2006)。運動對於腦部功能的影響:多上體育課會影響學業成績嗎。大專體育,87,184-190。
4. 阮志聰(1989)。幼兒智力與運動能力相關之研究。國教學報,2,251-277。
5. 謝錦城(2000)。體適能與全人健康的理念。學校體育,10,442-457。
6. 蔡天富(1997)。健康體適能教學之概念分析。研習資訊,14(4),55-64。
7. 呂勝瑛(1994)。高智商兒童的七十年追蹤研究。資優教育季刊,51,35-37。
8. 方進隆(1995)。體適能與全人健康。中華體育季刊,9卷,62-69。
9. 塗紫吟(2008)。運動參與對學業表現及情緒智力之影響。大專體育,95,82-87。
10. 陳全壽、劉宗翰、張振崗(2004)。我國體適能政策指標之建議。運動生理暨體能學報,1,1-11。
11. 張靜文、姜義村(1999)。學齡前幼兒體適能檢測之探討。大專體育雙月刊,41,135-138。
12. 洪維振(2003)。肥胖學童身體組成與體適能相關之研究。北體學報,11,217-223。
13. 洪嘉文(2000)。學校體育再造之探討。體育學報,29,59-70。
14. 邱慶瑞(2003)。學業成績好壞與體適能的表現比較:以臺北市永春高中為例。北體學報,11,173-179。
15. 林貴福(1991):臺北市國小學童身高與體重對體適能發展的影響。亞洲體育季刊,14,27-39。