跳到主要內容

臺灣博碩士論文加值系統

(44.221.66.130) 您好!臺灣時間:2024/06/24 05:11
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

: 
twitterline
研究生:陳柏諭
研究生(外文):Bo-Yu Chen
論文名稱:基於模糊IMM-EKF 算法運用TOA 和RSS的數據融合做移動定位估測
論文名稱(外文):Fuzzy-Based IMM-EKF Algorithm Using Data Fusion of TOA and RSS for Mobile Location Estimation
指導教授:何天讚
指導教授(外文):Tan-Jan Ho
學位類別:碩士
校院名稱:中原大學
系所名稱:電機工程研究所
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:2012
畢業學年度:100
語文別:中文
論文頁數:67
中文關鍵詞:非視距交互式多模型接收訊號強度擴展卡爾曼濾波器到達時間
外文關鍵詞:extended Kalman filterinteracting multiple modelNLOSreceived signal strengthtime of arrival
相關次數:
  • 被引用被引用:0
  • 點閱點閱:317
  • 評分評分:
  • 下載下載:1
  • 收藏至我的研究室書目清單書目收藏:0
本文提出了一種移動定位估測,使用到達時間(TOA)和接收訊
號強度(RSS)的數據融合算法。該算法結合了模糊自適應技術和基於交互多模型擴展卡爾曼濾波器(IMM-EKF)。為了改善城市環境中非視距(NLOS)的定位估測性能,IMM-EKF 算法透過模糊邏輯規則,自適應調整過程雜訊協方差。模擬結果顯示所提出的方法較傳統之IMM-EKF、TOA 或RSS 具有較優越的性能。

This thesis, presents an algorithm for mobile location estimation by using the data fusion of time of arrival (TOA) and the received signal strength (RSS). The proposed algorithm is a combination of the fuzzy adaptive technique and the extended Kalman filter-based interacting multiple model (IMM-EKF) method. Process noise covariances in the IMM-EKF algorithm are adaptively tuned via fuzzy-logic rules for improving the non-line-of-sight (NLOS) location estimation performance in urban environments. Simulations show that the proposed algorithm has better performance than the IMM-EKF,the TOA and the RSS methods.
目錄
摘要 ..................................................................................................................... Ⅰ
Abstract ............................................................................................................. Ⅱ
誌謝 ..................................................................................................................... Ⅲ
目錄 ..................................................................................................................... Ⅳ
圖目錄 ................................................................................................................. Ⅵ
表目錄 ................................................................................................................. Ⅷ
第一章 緒論 ...................................................................................................... 1
1-1 背景與研究動機 .................................................................................. 1
1-2 研究方法 .............................................................................................. 2
1-3 本文章節提要 ...................................................................................... 3
第二章 定位系統 .............................................................................................. 5
2-1 定位系統之簡介 .................................................................................. 5
2-2 定位系統的架構與原理 ...................................................................... 8
2-3 到達時間定位法 .................................................................................. 12
2-4 到達時間差定位法 .............................................................................. 13
2-5 到達角度定位法 .................................................................................. 14
2-6 接收訊號強度定位法 .......................................................................... 15
第三章 模糊控制系統 ...................................................................................... 17
3-1 模糊理論簡介 ...................................................................................... 17
3-2 模糊系統之架構與原理 ...................................................................... 18
第四章 基於模糊IMM-EKF 用於目標估測 ................................................... 25
4-1 測量模型 .............................................................................................. 25
4-2 IMM-EKF ............................................................................................. 30
4-3 T-S 模糊系統 ....................................................................................... 35
第五章 模擬結果與分析 .................................................................................. 40
第六章 結論 ...................................................................................................... 51
第七章 未來研究方向 ...................................................................................... 52
附錄一 三角定位法 .......................................................................................... 53
參考文獻 ............................................................................................................. 56
個人簡歷 ............................................................................................................. 59

圖目錄
圖2.1 全球衛星定位系統軌道分佈圖 .............................................................. 8
圖2.2 全球衛星定位系統的系統結構 .............................................................. 8
圖2.3 GSM 行動網路架構 ................................................................................ 10
圖2.4 TOA 定位示意圖 ..................................................................................... 13
圖2.5 TDOA 定位示意圖 .................................................................................. 14
圖2.6 AOA 定位示意圖 .................................................................................... 15
圖3.1 模糊邏輯控制器基本架構 ..................................................................... 19
圖3.2 隸屬函數圖形 ......................................................................................... 20
圖4.1 MS 移動示意圖 ....................................................................................... 25
圖4.2 馬可夫切換模型 ..................................................................................... 25
圖4.3 IMM-EKF 流程圖 ................................................................................... 34
圖4.4 功率的隸屬函數 ..................................................................................... 36
圖4.5 速度的隸屬函數 ..................................................................................... 37
圖5.1 Scenario 1 和Case 1 情況下之方法比較 ............................................. 42
圖5.2 Scenario 1 和Case 2 情況下之方法比較 ............................................. 43
圖5.3 Scenario 2 和Case 1 情況下之方法比較 ............................................. 44
圖5.4 Scenario 2 和Case 2 情況下之方法比較 ............................................. 45
圖5.5 Scenario 3 和Case 1 情況下之方法比較 ............................................. 46
圖5.6 Scenario 3 和Case 2 情況下之方法比較 ............................................. 47
圖5.5 Scenario 4 和Case 1 情況下之方法比較 ............................................. 48
圖5.6 Scenario 4 和Case 2 情況下之方法比較 ............................................. 49

表目錄
表2.1 四種方法之優缺點比較 ......................................................................... 16
表3.1 模糊控制器規則庫 ................................................................................. 22
表4.1 LOS 情況下的規則表 ............................................................................. 38
表4.2 NLOS 情況下的規則表 .......................................................................... 38
表5.1 Scenario 1 和Case 1 情況下移動定位估測誤差 ................................. 42
表5.2 Scenario 1 和Case 2 情況下移動定位估測誤差 ................................. 43
表5.3 Scenario 2 和Case 1 情況下移動定位估測誤差 ................................. 44
表5.4 Scenario 2 和Case 2 情況下移動定位估測誤差 ................................. 45
表5.5 Scenario 3 和Case 1 情況下移動定位估測誤差 ................................. 46
表5.6 Scenario 3 和Case 2 情況下移動定位估測誤差 ................................. 47
表5.7 Scenario 4 和Case 1 情況下移動定位估測誤差 ................................. 48
表5.8 Scenario 4 和Case 2 情況下移動定位估測誤差 ................................. 49
[1] K. J. Krizman, T. E. Biedka, and T. S.Rappaport, “Wireless position location: fundamentals, implementation strategies, and sources of error,” in Proc. IEEE Vehicular Technology Conference 1997, vol. 2, pp. 919-923.
[2] A. N. Zaki, and A. O. Fapojuwo, “Optimal and Efficient Graph-Based Resource Allocation Algorithms for Multiservice Frame-Based OFDMA Networks,” in IEEE Trans.on Mobile Computing, vol. 10, no. 8, pp.1175-1186, Aug. 2011.
[3] Y. Wen, Y. Lu, J. Yan, Z. Zhou, K. M. von Deneen, and P. Shi, “An Algorithm for License Plate Recognition Applied to Intelligent Transportation System,” in IEEE Trans. on Intelligent Transportation Systems, vol. 12, no. 3 ,pp. 830–845, Sep. 2011.
[4] A. L. Randall and R. C. Walter, “Overview of the small unit operations situational awareness system,” in Proc. IEEE Military Commun. Conf.(MILCOM), vol. 1, pp. 169–173, Oct. 2003.
[5] W. Guan, Z. Deng, Y. Yu and Y. Ge, “A NLOS MITIGATION METHOD FOR CDMA2000 MOBILE LOCATION,” in IEEE Network Infrastructure and Digital Content, 2010, pp. 668–672.
[6] C. Li and Z. Weihua, “Nonline-of-Sight Error Mitigation in Mobile Location,” in IEEE Trans. on Wireless Commun., vol. 4, no. 2, pp. 560–573,Mar. 2005.
[7] C. Fritsche, A. Klein and D. Wurtz, “Hybrid GPS/GSM Localization of Mobile Terminals using the Extended Kalman Filter,” in IEEE Proceeding of the 6th Workshop on Positioning, Navigation and Commun. 2009(WPNC’09), pp. 189–194.
[8] C. E. Seah and I. Hwang, “Algorithm for Performance Analysis of the IMM Algorithm,” in IEEE Trans. on Aerospace and Electronic Systems, vol. 47,no. 2, pp. 1114–11124, Apr. 2011.
[9] X. Wang, Z. Wang, and B. O’Dea, “A TOA-based Location Algorithm Reducing the Errors due to Non-Line-of-Sight (NLOS) Propagation,” in IEEE Trans. Vehicular Technology, vol. 52, pp. 112-116, Jan. 2003.
[10] C. Y. Yang, B. S. Chen, and F. K. Liao, “Mobile Location Estimator Using Fuzzy-Based IMM and Data Fusion,” in IEEE Trans. on mobile computing,Oct. 2010, vol. 9, no. 10, pp. 1424–1435.
[11] B. S. Chen, C. Y. Yang, F. K. Liao, and J. F. Liao, “Mobile Location Estimator in a Rough Wireless Environment Using Extended Kalman-Based IMM and Data Fusion,” in IEEE Trans. on Vehicular Technology, Mar.2009, vol. 58, no. 3, pp. 1157–1169.
[12] T. S. Rappaport, J. H. Reed, and B. D.Woerner, “Position Location Using Wireless Communications on Highways of the Future,” in IEEE Commun.
Mag., vol. 34, no. 10, pp. 33–41, Oct. 1996.
[13] X. Li, “A Selective Model to Suppress NLOS Signals in Angle-of-Arrival (AOA) Location Estimation,” in IEEE Indoor and Mobile Radio Commun.,vol. 1, pp. 461–465, Sep. 1998.
[14] A. S. Paul, E. A. Wan, “RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers,” in IEEE Journal of Selected Topics in Signal Processing, vol. 3, no. 5, pp. 860–873, Oct. 2009.
[15] R. Babuška, Fuzzy Modeling for Control, Kluwer Academic Publishers,Boston, 1998.
[16] M. L. Hadjili, and V. Wertz, “Takagi–Sugeno Fuzzy Modeling Incorporating Input Variables Selection,” in IEEE Trans. on Fuzzy Systems, vol. 10, no. 6,pp. 728–742, Dec. 2002.
[17] 安守中, GPS定位原理及應用,全華科技圖書股份有限公司,2005年11月
[18] G.. L. Stuber, Principles of mobile communication, Boston : Kluwer Academic, c2001.
[19] T-J Ho, and B-S Chen, “Novel extended Viterbi-based multiple-model algorithms for state estimation of discrete-time systems with Markov jump parameters,” IEEE Trans. Signal Processing, vol. 54, no.2, pp. 393-404,2006.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top