5. 電腦模擬
5.5 最大概似函數（Maximum Likelihood）
3.7 節以說明如何利用檢測法調整事後機率，圖 5.27 觀察不同檢測法調整事後機率 與原始 ML 方法做比較，其中另外模擬如果可以完美檢測出哪些 BS 為 LOS 調整PNLOS 1， 在做 ML 比較，
圖 5.27 檢測法調整 ML
結果顯示在 NLOS 發生機率高時，檢測法調整事後機率可降低 RMSE，而當 NLOS 發生機率 低時，仍可維持與 ML 接近的 RMSE。
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0 10 20 30 40 50 60 70
PNLOS
RMSE
NLOSrate=0.1,i=0.015di ML
完 美 檢 測 直 接 上 限 餘 差
第六章
結論與未來展望
由第五章電腦模擬結果顯示，其他降低 NLOS 效應的方式如果搭配檢測法，先移除 部分量測資訊，可以使 RMSE 下降，且移除部分量測資訊也可降低運算複雜度，除了少 數特殊情況無法改善以外例如當所有 BS 皆為 NLOS，加入限制式搭配檢測法無明顯改善，
原因在於移除部分量測資訊會使的交集區 S 變大，雖然無明顯改善，但仍可達到降低運 算複雜度的效果。
即使所有量測值皆為 NLOS，利用檢測法也可將 NLOS 偏差量大的量測資訊做移除動 作，保留 NLOS 偏差量小的量測資訊，也可以改善 RMSE，如 5.3.2 節所描述。
移除個數 d 小的情況下，只能移除 NLOS 偏差量大的量測資訊，無法將 NLOS 全部 移除，而仍然可以降低 RMSE，但移除個數 d 過大，會將 LOS 誤判為 NLOS，使的最後結 果不理想。另一方面移除個數 d 的大小也會影響到運算複雜度，移除個數 d 小運算複雜 度高、移除個數 d 大運算複雜度低。
最後本論文所提出的檢測法，是在沒有任何 NLOS 統計資訊的情況下，所做的檢測 法，如果已知 NLOS 統計性質情況下，可考量 NLOS 統計性質搭配檢測法，發展更完善的 檢測法，例如事先知道 NLOS 發生機率，則可選擇移除個數 d 的大小。
參考書目
〔1〕P.C. Chen “ A Non-Line-of-Sight Error Mitigation Algorithm in Location Estimation”
Wireless Communications and Networking Conference,pp.316-320, 1999. WCNC.
〔2〕J. Xing,J.Zhang,L. Jiao,X. Zhang “A Robust Wireless Sensor Network Localization Algorithm in NLOS Environment” 2007 IEEE International Conference on Control and Automation Guangzhou,pp.3244-3249 CHINA – May 30 to June 1, 2007
〔3〕K. Yu, Y. J. Guo “ Improved Positioning Algorithms for Non-line-of-Sight Environments”
IEEE Transactions on Vehicular Technology, VOL.57,NO.4, July 2008
〔4〕K.Wei ,W. Lenan “Constrained Least Squares Algorithm for TOA-Based Mobile Location under NLOS Environments” Wireless Communications, Networking and Mobile Computing, pp.1-4,2009
〔5〕S. Venkatesh , R. M.Buehrer “NLOS Mitigation Using Linear Programming in
Ultrawideband Location-Aware Networks” IEEE Transactions on Vehicular Technology, VOL.
56, NO.5, September 2007
〔6〕X.Wang, Z.Wang, and B. O’Dea “ A TOA-Based Location Algorithm Reducing the Errors Due to Non-Line-of-Sight (NLOS) Propagation” IEEE Transactions on Vehicular
Technology, VOL.52,NO.1,January 2003
〔7〕K.T. Lay, and W.K. Chao “ Mobile Positioning Based on TOA/TSOA/TDOA
Measurements with NLOS Error Reduction” Proceedings of 2005 International Symposium on Intelligent Signal Processing and Communication Systems ,pp.545-548, December 13-16,2005 Hong Kong
〔8〕L. Cong, W. Zhuang “ Nonline-of-Sight Error Mitigation in Mobile Location” IEEE Transactions on Vehicular Technology, VOL. 4, NO.2, March 2005
〔9〕C.K. Seow, S. Y. Tan “ Non-Line-of-Sight Localization in Multipath Environments”
IEEE Transactions on Mobile Computing, VOL. 7, NO. 5, May 2008
〔10〕H. Miao, K.Yu, M. J. Juntti “ Positioning for NLOS Propagation: Algorithm
Derivations and Cramer-Rao Bounds” IEEE Transactions on Vehicular Technology, VOL. 56, NO.5, September 2007
〔11〕S. Venkatraman , J. Caffery “ Hybrid TOA/AOA Techniques for Mobile Location in Non-Line-of-Sight Environments” Wireless Communications and Networking Conference, VOL.1,pp.274-278, 2004.
〔12〕R.W. Ouyang,A. K. Wong,C.T. Lea and V. Y. Zhang“Received Signal Strength-Based Wireless Localization via Semidefinite Programming” IEEE Transactions on Vehicular Technology, VOL. 59,pp. 1307 - 1318, 2010
〔13〕X. Li“RSS-Based Location Estimation with Unknown Pathloss Model”IEEE Transactions on Wireless Communications,VOL.5,pp.3626 – 3633,2006
〔14〕J. Khodjaev, Y.Park, A. S. Malik “ Survey of NLOS identification and error mitigation problems in UWB-based positioning algorithms for dense environments” Annals of
Telecommunications-Annales Des Telecommunications VOL. 65 pp. 301-311,2009
〔15〕J. Riba and A. Urruela “ A Non-Line-of-Sight Mitigation Technique Based on ML-Detection” 2004 IEEE International Conference on Acoustics, Speech and Signal Processing VOL.2 pp. ii 153-156 ,2004
〔16〕W.K. Lui, H.C.So,and W.-K. Ma “ Maximum A Posteriori Approach to
Time-of-Arrival-Based Localization in Non-Line-of-sight Environment”IEEE Transactions on Vehicular Technology,VOL.59,NO.3,March 2010
〔17〕K.Yu and Y.Jay Guo“ Statistical NLOS Identification Based on AOA,TOA,snd Signal Strength”IEEE Transactions on Vehicular Technology,VOL.58,NO.3,January 2009
〔18〕W. H .Foy “ Position-Location Solutions by Taylor-Series Estimation”IEEE Transactions on Aerospace and Electronic Systems VOL.12,NO.2 March 1976
〔19〕S.A.Jazzar, J. Caffery, H.R. You “ Scattering-Model-Based Methods for TOA Location in NLOS Environments” IEEE Transactions on Vehicular Technology, VOL. 56, NO.2, March 2007
〔20〕S. A. Jazzar, J. Caffery, H.R. YOU “ A Scattering Model Based Approach to NLOS Mitigation in TOA Location Systems” Vehicular Technology Conference, 2002. VTC Spring 2002.VOL. 2
〔21〕Y.A. Chan,Y. C. Hang,and P.C. Ching“Exact and Approximate Maximum Lilelihood Localization Algorithms” IEEE Transactions on Vehicular Technology, VOL. 55, NO.1, January 2006
〔22〕Caffery “ A New Approach to the Geometry of TOA Location” Vehicular Technology Conference IEEE VTS-Fall VTC 2000 pp.1943-1949 , 52nd, 2000.
〔23〕G.Shen, R. Zetik, O.Hirsch, and R. S. Thoma “ Range-Based Localization for UWB Sensor Networks in Realistic Environments” Hindawi Publishing Corporation EURASIP Journal on Wireless Communicationsm and Networking Volume 2010
〔24〕L. Lin, D.Ping, F. Pingzhi “ A Simple and Efficient Positioning Algorithm Based on Geometry” 2010 International Conference on Communications and Mobile
Computing,pp.374-377