儘管全球定位系統具有非常高的準確性，但它在室內並不能很好地運用，必須用其他與衛星無關的定位系統來彌補。相較於室外，室內環境普遍較小，導致定位結果之誤差更加明顯。另外，一般是以越容易完成定位或能夠快速定位成功為目標。基於上述考量，本論文將提出幾種不同的定位方法，每種定位方法都有一定的優勢。有限制的兩步法利用兩步法中加強感測器以交換時間來減少固定點需求的功能，增加條件限制以獲得更高的準確性。三步法則是藉由兩步法之特性，將演算法運用到三維場景，不過由於建築物樓層高度特性，對演算法會造成影響。另外，本論文亦應用側方觀測法於定位中，演算法可減少對固定點的需求，使用者本身也不需要移動，但感測器部分需要更多的功能，以適合未來的發展。結合之前多種演算法的特色，可利用側方觀測法減少固定點的能力，透過兩步法特性可進一步減少固定點，因此，可從固定點不足的環境中獲益最多，使用效果好，但對感測器需求是前述幾種方法的總和，而此方法被稱為單步法。經過模擬驗證可知側方觀測法具有以上所有方法的最高精度，而且總體使用率也是方法中較高的，將是定位系統的理想選擇。

Although the global positioning system (GPS) has a great degree of accuracy, it does not work well for the indoor environment, which has to be filled up with the other positioning system without involving with satellites. Unlike the outdoor environment, the indoor environment is usually tightly spaced, making even the slightest error in positioning become relatively more significant. Besides, one usually expects finishing locating easier or faster. Base on the aforementioned considerations, this paper will propose a few positioning methods. Each of them excels in a certain aspect. For the 2-step method with restriction, it is designed based on the 2-step method with more sensors and locating time to trade off the number of fixed points required. With the added restriction, higher accuracy can be achieved. The 3-step method with or without restriction make the two aforementioned algorithms be feasible for a three dimension scenario. However, the fixed floor height might influence the effectiveness. As for the flank observation method (FOM), it does not need to move and requires fewer fixed points than the trilateration method. Taking the advantages of the previous methods, the 1-step method may benefit most. Via simulations, we demonstrate that FOM has the best accuracy among all the aforementioned methods with an acceptable level of usage. Therefore, FOM is highly recommended for use in the indoor positioning system.

[1] X. Hu, M. Stalnacke, T. B. Minde, R. Carlsson, and S. Larsson, “A mobile game to
collect and improve position of images,” in Proc. International Conference on Next
Generation Mobile Applications, Services and Technologies, Sept. 2009, pp. 70–73.
[2] S. Lee, N. Lee, J. Ahn, J. Kim, B. Moon, S. H. Jung, and D. Han, “Construction of
an indoor positioning system for home iot applications,” in Proc. IEEE International
Conference on Communications (ICC), May 2017, pp. 1–7.
[3] T. A. Mounir, P. S. Mohamed, B. Cherif, and B. Amar, “Positioning system for
emergency situation based on RSSI measurements for WSN,” in Proc. International
Conference on Performance Evaluation and Modeling in Wired and Wireless Networks
(PEMWN), Nov. 2017, pp. 1–6.
[4] T. Wigren, M. Anderson, and A. Kangas, “Emergency call delivery standards impair
cellular positioning accuracy,” in Proc. IEEE International Conference on Communications,
May 2010, pp. 1–6.
[5] E. Kaplan and C. Hegarty, Understanding GPS: Principles and Applications, ser.
Artech House Mobile Communications Series. Artech House, 2006. [Online].
Available: https://books.google.com.tw/books?id=V_5OAAAAMAAJ
[6] T. P. Yunck, W. G. Melbourne, and C. L. Thoenton, “GPS-based satellite tracking
system for precise positioning,” IEEE Transactions on Geoscience and Remote Sensing,
vol. GE-23, no. 4, pp. 450–457, July 1985.
[7] H. Liu, H. Darabi, P. Banerjee, and J. Liu, “Survey of wireless indoor positioning
techniques and systems,” IEEE Transactions on Systems, Man, and Cybernetics,
Part C (Applications and Reviews), vol. 37, no. 6, pp. 1067–1080, Nov. 2007.
[8] Y. Gu, A. Lo, and I. Niemegeers, “A survey of indoor positioning systems for wireless
personal networks,” IEEE Communications Surveys Tutorials, vol. 11, no. 1, pp.
13–32, Mar. 2009.
[9] J. Hightower and G. Borriello, “Location systems for ubiquitous computing,” Computer,
vol. 34, no. 8, pp. 57–66, Aug. 2001.
[10] V. Honkavirta, T. Perala, S. Ali-Loytty, and R. Piche, “A comparative survey of
WLAN location fingerprinting methods,” in Proc. Workshop on Positioning, Navigation
and Communication, Mar. 2009, pp. 243–251.
[11] Z. Zheng, L. Liu, C. Zhao, and W. Hu, “High accuracy indoor positioning scheme
using single LED and camera,” Electronics Letters, vol. 54, no. 4, pp. 227–229, 2018.
[12] Y. Zhang, L. Deng, and Z. Yang, “Indoor positioning based on FM radio signals
strength,” in Proc. International Conference on Electronics Instrumentation Information
Systems (EIIS), June 2017, pp. 1–5.
[13] E. Cay, Y. Mert, A. Bahcetepe, B. K. Akyazi, and A. S. Ogrenci, “Beacons for indoor
positioning,” in Proc. International Conference on Engineering and Technology
(ICET), Aug. 2017, pp. 1–5.
[14] D. E. Manolakis, “Efficient solution and performance analysis of 3-D position estimation
by trilateration,” IEEE Transactions on Aerospace and Electronic Systems,
vol. 32, no. 4, pp. 1239–1248, Oct. 1996.
[15] M. E. Rusli, M. Ali, N. Jamil, and M. M. Din, “An improved indoor positioning algorithm
based on RSSI-trilateration technique for Internet of Things (IOT),” in Proc.
International Conference on Computer and Communication Engineering (ICCCE),
July 2016, pp. 72–77.
[16] T. D. Huynh, C. S. Chen, and S.-W. Ho, “Exploiting user movement for position
detection,” in Proc. IEEE Consumer Communications and Networking Conference
(CCNC), Jan. 2015, pp. 513–518.
[17] T. D. Huynh, C. S. Chen, and S. W. Ho, “Localization method for device-to-device
through user movement,” in Proc. IEEE International Conference on Communication
Workshop (ICCW), June 2015, pp. 821–826.
[18] R. Harle, “A survey of indoor inertial positioning systems for pedestrians,” IEEE
Communications Surveys Tutorials, vol. 15, no. 3, pp. 1281–1293, Jan. 2013.
[19] E. Foxlin, “Pedestrian tracking with shoe-mounted inertial sensors,” IEEE Computer
Graphics and Applications, vol. 25, no. 6, pp. 38–46, Nov. 2005.
[20] 史天元, “「側方觀測」探由(On the origin of flank observation),” 地籍測量,
vol. 34, no. 2, pp. 17–24, 2015。