臺灣博碩士論文加值系統

隨著新世代行動通訊網路的發展，小細胞基站的應用受到更廣泛的重視，對於道路移動目標的定位與追蹤，也可透過小細胞基站網路的佈建達到效能的提升。本論文中，我們探討以\ LTE(Long Term Evolution) 通訊網路為基礎，應用於道路定位系統的基地台佈建方式。我們以\ OTDOA (Observation Time Difference of Arrival)具封閉解之最小平方定位法來估測移動目標之位置，並且計算該位置之幾何精度稀釋值\ (GDOP) 經轉換為適應性卡爾曼濾波器\ (Adaptive Kalman Filter)之量測雜訊矩陣，進行疊代計算。針對兩種不同的基地台佈建方式，交錯式佈建法以及非交錯式佈建法，我們探討使用幾何精度稀釋對於定位與追蹤效能的影響。\\
假設小細胞基站佈建於道路兩側，其涵蓋之道路區域為矩形，以各種不同之基地台佈建方式，依據本道路模型進行模擬，使用\ OTDOA 進行具封閉解之最小平方定位法，球面交點法之定位結果計算出\ GDOP值代入適應性卡爾曼濾波器進行目標的定位與追蹤，在本論文中討論\ GDOP 分布於不同基地台數量以及幾何佈建方式中，探討出的兩種佈建方式的比較後，藉由交錯式基地台佈建法可以得到相對於非交錯式佈建法更好的\ RMSE 值分佈。未來若再結合駕駛人行為判斷以及不同比例之基站分佈方式，可以達成更好的行車規劃甚至是自動駕駛輔助的輔助工具。

Along with the development of Next Generation Mobile Communication Network, the application of Small-Cell has become an important issue in mobile network system. Target positioning and locationing can be improved efficiently through
Small-Cell mobile network. In this Thesis, we investigate a Road Positioning eNodeB deployment method based on LTE communication network. We use OTDOA and Least-Square Closed-form SX Method (Spherical-Intersection,SX) to estimate the position of a moving
target (UE), calculate its GDOP value and transform into the measurement noise matrix of Adaptive Kalman Filter. We proposed two eNodeB deployment method, staggered and non-staggered deployment method and probe its effect on
positioning and tracking efficiency using GDOP values. Assume that Small-Cell deployed at road sides, covered a rectangular zone by different deployment method and simulate according to our road model.Getting the location by SX method using OTDOA. we calculated the GDOP value and substituted
into Adaptive Kalman Filter to estimate and track UE's position. We discuss how the GDOP distribution effected by different numbers and deployment method. The results show that the staggered deployment method get better RMSE distribution.

中文摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i
英文摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
誌謝. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
表目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi
圖目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
一、緒論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 研究背景. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 研究動機. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 論文架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
二、LTE 系統之無線定位法與幾何精度稀釋. . . . . . . . . . . . . . . . . . 4
2.1 LTE 通訊系統. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1.1 系統架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1.2 核心網路. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1.3 觀測性訊號抵達時間差法OTDOA . . . . . . . . . . . . . . . 6
2.2 OTDOA 使用之訊號抵達時間差法. . . . . . . . . . . . . . . . . . . 7
2.3 幾何精度稀釋. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3.1 eNodeB 佈建位置討論. . . . . . . . . . . . . . . . . . . . . . 9
2.3.2 eNodeB 佈建數量討論. . . . . . . . . . . . . . . . . . . . . . 13
2.4 群組式基地台網路. . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
三、基地台佈建與行動裝置定位追蹤. . . . . . . . . . . . . . . . . . . . . . . 26
3.1 基地台之佈建法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.1.1 交錯式eNodeB 系統架構. . . . . . . . . . . . . . . . . . . . 26
3.1.2 非交錯式eNodeB 系統架構. . . . . . . . . . . . . . . . . . . 28
3.2 以OTDOA進行之行動裝置定位法. . . . . . . . . . . . . . . . . . . 29
3.3 行動裝置之追蹤與誤差抑制. . . . . . . . . . . . . . . . . . . . . . . 32
3.3.1 卡爾曼濾波器. . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.3.2 適應性卡爾曼濾波器. . . . . . . . . . . . . . . . . . . . . . . 36
四、電腦模擬與分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
4.1 定位效能優劣判斷依據. . . . . . . . . . . . . . . . . . . . . . . . . . 38
4.2 模擬環境之參數設定與結果分析. . . . . . . . . . . . . . . . . . . . . 38
五、結論與未來方向. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.1 結論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.2 未來方向與建議. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
參考文獻. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

[1] E. D. Kaplan, Understanding GPS: Principles and Applications. Artech House,
March 1996.
[2] Motorola, \Long Term Evolution (lte): A technical overview," Motorola, Tech.
Rep., 2010.
[3] \Special issue on time delay estimation," IEEE Acoustics, Speech, and Signal
Processing Newsletter, vol. 49, no. 1, pp. 12{12, March 1980.
[4] B. Friedlander, \On the cramer- rao bound for time delay and doppler estima-
tion (corresp.)," IEEE Transactions on Information Theory, vol. 30, no. 3, pp.
575{580, May 1984.
[5] M. A. Spirito and A. G. Mattioli, \On the hyperbolic positioning of GSM
mobile stations," in Proceedings of 1998 URSI International Symposium on
Signals, Systems, and Electronics. Conference Proceedings (Cat. No.98EX167),
September 1998, pp. 173{177.
[6] S. Fischer, \Introduction to OTDOA on LTE Networks," Qualcomm Technolo-
gies,inc., Tech. Rep., 2014.
[7] J. Liu and S. Feng, \RSTD performance for small bandwidth of OTDOA posi-
tioning in 3GPP LTE," in Proceedings of 2013 IEEE 78th Vehicular Technology
Conference (VTC Fall), September 2013, pp. 1{5.
[8] J. Caffery and G. L. Stuber, \Subscriber location in CDMA cellular networks,"
IEEE Transactions on Vehicular Technology, vol. 47, no. 2, pp. 406{416, May
1998.
[9] N. Levanon, \Lowest GDOP in 2-d scenarios," in Proceedings of IEE on Radar,
Sonar and Navigation, vol. 147, no. 3, June 2000, pp. 149{155.
[10] H. B. Lee, \A novel procedure for assessing the accuracy of hyperbolic multi-
lateration systems," IEEE Transactions on Aerospace and Electronic Systems,
vol. AES-11, no. 1, pp. 2{15, January 1975.
[11] D. J. Torrieri, \Statistical theory of passive location systems," IEEE Transac-
tions on Aerospace and Electronic Systems, vol. AES-20, no. 2, pp. 183{198,
March 1984.
[12] Y. H. Huang, \Localization and target tracking with improved GDOP using
mobile sensor nodes," Master's thesis, National Sun Yat-Sen University, July
2010.
[13] D. Culler, D. Estrin, and M. Srivastava, \Guest editors' introduction: Overview
of sensor networks," Computer, vol. 37, no. 8, pp. 41{49, August 2004.
[14] H. Schau and A. Robinson, \Passive source localization employing intersect-
ing spherical surfaces from time-of-arrival differences," IEEE Transactions on
Acoustics, Speech, and Signal Processing, vol. 35, no. 8, pp. 1223{1225, August
1987.
[15] W. C. Ou, \Performance analysis of Closed-Form Least-Squares TDOA location
methods in multi-sensor environment," Master's thesis, National Sun Yat-Sen
University, July 2006.
[16] Y. T. Chan and K. C. Ho, \A simple and efficient estimator for hyperbolic
location," IEEE Transactions on Signal Processing, vol. 42, no. 8, pp. 1905{
1915, August 1994.
[17] R. Schmidt, \Least squares range difference location," IEEE Transactions on
Aerospace and Electronic Systems, vol. 32, no. 1, pp. 234{242, January 1996.
[18] R. O. Schmidt, \A new approach to geometry of range difference location,"
IEEE Transactions on Aerospace and Electronic Systems, vol. AES-8, no. 6,
pp. 821{835, November 1972.
[19] G. Mellen, M. Pachter, and J. Raquet, \Closed-form solution for determining
emitter location using time difference of arrival measurements," IEEE Transac-
tions on Aerospace and Electronic Systems, vol. 39, no. 3, pp. 1056{1058, July
2003.
[20] S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory.
New Jersey: Prentice Hall, 1993, vol. 1.
[21] G.Welch and G.Bishop, \An introduction to the Kalman lter," University of
North Carolina, Department of Computer Science at Chapel Hill, Tech. Rep.,
2006.
[22] R. Faragher, \Understanding the basis of the Kalman lter via a simple and in-
tuitive derivation," IEEE Signal Processing Magazine, pp. 128{132, September
2012.
[23] S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory:
Detection Theory. New Jersey: Prentice Hall, 1993, vol. 2.
[24] X. R. Li and V. P. Jilkov, \Survey of maneuvering target tracking. Part I.
dynamic models," IEEE Transactions on Aerospace and Electronic Systems,
vol. 39, no. 4, pp. 1333{1364, October 2003.
[25] P. O. Gutman and M. Velger, \Tracking targets using adaptive Kalman lter-
ing," IEEE Transactions on Aerospace and Electronic Systems, vol. 26, no. 5,
pp. 691{699, September 1990.