為因應無線通訊應用服務之需求，行動定位技術，廣受政府、學術界、與業界所矚目。在無線通訊系統中，訊號非視線傳播為影響行動定位準確性的主要問題之一。本研究針對此問題，利用叢簇方法設計新的定位演算法，分析抵達時間之量測距離和基地台所形成的幾何圖形，計算行動台所有可能的位置，選取定位候選點密度較高的叢簇產生目的函式，並計算其最佳解，以預測行動台之位置。模擬並實驗在不同因素，如接收非視線傳播訊號的基地台個數和非視線傳播誤差值大小對行動定位準確性的影響，實驗結果顯示本研究提出的演算法比 Range scaling 定位演算法，Linear line of position 定位演算法和Taylor series algorithm 定位演算法均有較佳的定位準確性，且可滿足 E-911 之定位準確度需求。

For the mass demands of wireless communication services, the mobile location technologies have drawn much attention of the governments, academia, and industries around the world. In wireless communication, one of the main problems with accurate location is nonline of sight (NLoS) propagation. To solve the problem, we present a new location algorithm with clustering technology by utilizing the geometrical feature of cell layout, time of arrival (ToA) range measurements, and three base stations. The mobile location is estimated by solving the optimal solution of the objective function based on the high density cluster. Simulations study was conducted to evaluate the performance of the algorithm for different NLoS error distributions and various upper bound of NLoS error. The results of our experiments demonstrate that the proposed algorithm is significantly more effective in location accuracy than range scaling algorithm, linear lines of position algorithm, and Taylor series algorithm, and also satisfies the location accuracy demand of E-911.

CHAPTER 1 INTRODUC1
CHAPTER 2 RELATED RESEARCHES.............................................................................................................5
2.1 LOCATION TECHNIQUES5
2.1.1 Cell-ID Method ......5
2.1.2 Time of Arrival (ToA) Method ..............................................................................................................6
2.1.3 Signal Strength Method.........................................................................................................................8
2.1.4 Angle of Arrival (AoA) Method.............................................................................................................9
2.1.5 Global Positioning System (GPS)..........................................................................................................9
2.2 SIGNAL NLOS PROPAGATION .....................................................................................................................10
2.2.1 Taylor Series Algorithm (TSA) and Linear Lines of Position (LLoP) Algorithm.............................11
2.2.2 Range Scaling algorithm (RSA) ..........................................................................................................12
CHAPTER 3 DENSITY-BASED CLUSTERING ALGORITHM (DCA) .......................................................14
3.1 CALCULATION OF THE CANDIDATE POINTS ...............................................................................................15
3.2 BOUNDARIES OF α, β, AND γ.........................................................................................................................17
3.3 MODIFICATION OF THEOBJECTIVE FUNCTION..........................................................................................21
3.4 ESTIMATION OF THEMOBILE LOCATION...................................................................................................24
CHAPTER 4 SIMULATION DESIGN ...............................................................................................................25
SIMULATION PROCEDURE .......27
Step 1....................................27
Step 2....................................28
Step 3....................................29
Step 4....................................30
CHAPTER 5 PERFORMANCE AND SIMULATION RESULTS...................................................................31
5.1 EFFECT OF THE NLOS DISTRIBUTION ........................................................................................................31
5.2 EFFECT OF THE UPPER BOUND OF NLOS ERROR.......................................................................................34
5.3 EFFECT OF THE NUMBER OF NLOS BSS .....................................................................................................35
5.4 EFFECT OF THE PERCENTAGE OF CANDIDATE POINTS ..............................................................................36
CHAPTER 6 CONCLUSIO38
REFERENCES ...........................39
APPENDIX .................................40

[1] J. Caffery and G. Stuber, “Overview of radiolocation in CDMA cellular systems,” IEEE
Commun. Mag., vol. 36, pp. 38–45, Apr. 1998.
[2] J. Caffery, Wireless Location in CDMA Cellular Radio Systems. Norwell, MA: Kluwer,
1999.
[3] J. Caffery, “A new approach to the geometry of TOA location,” in Proc. IEEE Vehicular
Technology Conf. (VTC’00), pp. 1943–1949, 2000.
[4] P.-C. Chen, “A nonline-of-sight error mitigation algorithm in location estimation,” in
Proc. IEEE Wireless Communication and Networking Conf. (WCNC’99), pp. 316–320,
1999.
[5] Revision of the Commissions Rules to Insure Compatibility with Enhanced 911
Emergency Calling Systems, Fed. Commun. Commission (FCC), Washington, DC, Tech.
Rep. RM-8143, 1996.
[6] W. Foy, “Position-location solutions by Taylor series estimation,” IEEE Trans. Aerosp.
Electron. Syst., vol. AES-12, pp. 187–193, Mar. 1976.
[7] M. Hata and T. Nagatsu, “Mobile Location Using Signal Strength Measurementsin a
Cellular System,” IEEE Trans. Vehic. Tech., vol. VT-29, May 1980, pp. 245–51.
[8] P. van Rooyen, M. Lotter, and D. van Wyk, Space-Time Processing for CDMA Mobile
Communications. New York: Kluwer, 2000.
[9] N. Shepherd, and W. Trammell, “Vehicle Location by a SignalAttenuation Method,”
IEEE Trans. Vehic. Tech., vol. VT-18, Nov. 1969, pp. 105–10.
[10] M.I. Silventoinen and T. Rantalainen, “Mobile station emergency locating in GSM,” in
Proc. IEEE Int. Conf. Personal Wireless Communications, pp. 232–238, 1996.
[11] S. Venkatraman, J. Caffery, and H.-R. You “A novel ToA location algorithm using LoS
range estimation for NLoS environments,” IEEE Transactions on Vehicular Technology,
vol. 53, pp.1515-1524, Sep. 2004.
[12] S.-S. Woo, H. You, and J.-S. Koh, “The NLOS mitigation technique for position location
using IS-95 CDMA networks,” in Proc. IEEE Vehicular Technology Conf. (VTC’00), vol.
6, pp. 2556–2560, 2000.
[13] M.P. Wylie and J. Holtzman, “The nonline of sight problem in mobile location
estimation,” in Proc. IEEE Int. Conf. Universal Personal Communications (ICUPC’96),
vol. 2, pp. 827–831, 1996.