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標題: 應用模糊粒子濾波演算法於行動感測網路之定位技術研究
Fuzzy Particle Filter for Distributed Positioning in Mobile Wireless Sensor Networks
作者: 詹富凱
Chan, Fu-Kai
關鍵字: Wireless Sensor Networks;無線感測網路;fuzzy control;Particle Filtering;模糊控制;粒子濾波器
出版社: 電機工程學系所
引用: [1] Y. T. Chan, H. Y. C. Hang, and P. C. Ching, “Exact and approximate maximum likelihood localization algorithms,” IEEE Trans. Veh. Technol., vol. 55, no. 1, pp. 10-16, Jan. 2006. [2] C. Cheng and A. Sahai, “Estimation bounds for localization,” in Proc. IEEE Int. Conf. Sensor and Ad-Hoc Communications and Networks (SECON), Santa Clara, CA, Oct. 2004, pp. 415-424 [3] I. Guvenc and C. C. Chong, “A Survey on TOA Based Wireless Localization and NLOS Mitigation Techniques,” in IEEE Communications Surveys and Tutorials, no. 3, July 2009. [4] P. Zou, Z. Huang, J.Lu, “Passive Stationary Target Positioning Using Adaptive Particle Filter with TDOA and FDOA Measurements,” in IEEE Communication and 5th International Symposium. pp. 435-465. 2004. [5] P.N. Pathirana, N. Bulusu, A.V. Savkin, and S. Jha, “Node Localization Using Mobile Robots in Delay-Tolerant Sensor Networks,” IEEE Trans. on Mobile Computing, vol. 4, no. 3, pp. 285-296, 2005. [6] M. Sichitiu and V. Ramadurai, “Localization of Wireless Sensor Networks with a Mobile Beacon,” in Proc. of the 1st IEEE MASS, 2004. [7] L. Hu and D. Evans, “Localization for Mobile Sensor Networks,” in Proc. of the 10th ACM MobiCom, 2004. [8] R. Cesbron and R. Arnott, “Locating GSM mobiles using antenna array,” Electron. Lett., vol. 34, pp. 1539-1540, Aug. 1998. [9] H. C. So and E. M. K. Shiu, “Performance of TOA-AOA hybrid mobile location,” IEICE Trans. Fundamentals, vol. E86-A, no. 8, pp. 2136-2138, Aug. 2003. [10] P. Deng and P.-Z. Fan, “An AOA assisted TOA positioning system,” Proc. International Conference on Communication Technology, vol. 2, pp. 1501-1504, 2000. [11] S. Venkatraman, J. Caffery, Jr., and H.-R. You, “A novel ToA location algorithm using LoS range estimation for NLoS environments,” IEEE Transactions on Vehicular Technology, vol. 53, no. 5, pp. 1515-1524,2004. [12] N. Deligiannis, S. Louvros, and S. Kotsopoulos, “Optimizing Location Positioning Using Hybrid TOA-AOA Techniques in Mobile Cellular Networks,” Proc. of Mobimedia'07, Aug. 2007. [13] Y.-T. Chan, W.-Y. Tsui, H.-C. So, and P.-C. Ching, “Time-of-arrival based localization under NLOS conditions,” IEEE Transactions on Vehicular Technology, vol. 55, no. 1, pp. 17-24, 2006. [14] F. Gustafsson and F. Gunnarsson, “Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements,” IEEE Signal Processing Magazine, vol. 22, no. 4, pp. 41-53, 2005. [15] A. H. Sayed, A. Tarighat, and N. Khajehnouri, “Network-based wireless location: challenges faced in developing techniques for accurate wireless location information,” IEEE Signal Processing Magazine, vol. 22, no. 4, pp. 24-40, 2005. [16] J. Luo, H. V. Shukla, J.-P. Hubaux, “Non-Interactive Location Surveying for Sensor Networks with Mobility-Differentiated TOA,” in Proc. of the 25th IEEE INFOCOM, April 2006. [17] H. Tang, Y.-W. Park, and T.-S. Qiu, “A TOA-AOA-Based NLOS Error Mitigation Method for Location Estimation,” EURASIP Journal on Advances in Signal Processing, vol. 8, Article ID 682528, 14 pages, 2008. [18] C.-Y. Wen, R. D. Morris, and W. A. Sethares, “Distance Estimation Using Bidirectional Communications Without Synchronous Clocking,” IEEE Transactions on Signal Processing, vol. 55, no. 5, pp. 1927-1939, May 2007. [19] N. J. Gordon, D. J. Salmond, A. F. M. Smith, “Novel approach to nonlinear/non-Gaussian Bayesian state estimation,” IEEE Proceedings For Radar and Signal Processing, Vol. 12, No. 2, pp. 107-113, Apr. 1993. [20] J. Hightower and G. Borriello, “Particle Filters for Location Estimation in Ubiquitous Computing: A Case Study,” in Proc. of the Sixth International Conference on Ubiquitous Computing, pp. 88-106, Sep. 2004. [21] R. Ware and F. Lad, “Approximating the Distribution for Sum of Product of Normal Variables,” the research report of the Mathematics and Statistics department at Canterbury University, 2003. [22] R. Parthiban and A. Menon, “A Fuzzy Logic Algorithm for Minimizing Error (FLAME) in Wireless Sensor Networks,” Proc. IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Singapore, paper FA3.5, July, 2009 [23] Y. Shi, M. Mizumoto, N. Yubazaki, M. Otani A, “learning algorithm for tuning fuzzy rules based on the gradient descent method, ” Proceedings of the Fifth IEEE International Conference on Fuzzy Systems (FUZZ-IEEE''96), New Orleans, USA, Vol.1, pp.55-61, 1996 (with, and). [24] S. Chib and E. Greenberg, “Understanding the Metropolis-Hastings algorithm,” The American Statistician 49: 327-335, 1995.

Location-awareness is crucial and becoming increasingly important to many applications in wireless sensor networks. This paper presents a network-based positioning system and outlines recent work in which we have developed an efficient principled approach to localize a mobile sensor using an TOA/AOA hybrid positioning scheme employing multiple seeds in the line-of-sight scenario. Based on the initial position estimate, a fuzzy algorithm is used to reduce positioning error. The proposed algorithm exploits the information flow while coping with distributed signal processing and the requirements of network scalability. The feasibility of the proposed scheme is shown to be effective under certain assumptions and the analysis is supported by simulation and numerical studies.
其他識別: U0005-1008201016492100
Appears in Collections:電機工程學系所

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