微信服务号

微信订阅号

2025-4-6- 7
Home > Archive>Volume 21, Issue 11, 2010 >2883-2891
PDF HTML XML Export Cite reminder
Localization in Wireless Sensor Network Using Locality Preserving Canonical Correlation Analysis
Author:
Affiliation:

  • Article
    • | |
  • Metrics
    • |
  • Reference [25]
    • |
  • Related [20]
    • |
  • Cited by [5]
    • | |
  • Comments
    Abstract:

    In this paper, the deployment of wireless network is analyzed in accordance with the manifold distribution. Next, the previous Locality Preserving Canonical Correlation Analysis (LPCCA) algorithm is used to build a mapping from the signal-vector space to the physical location space and develop a location algorithm, Location Estimation-Locality Preserving Canonical Correlation Analysis (LE-LPCCA, for short), which sufficiently takes the local structure of the network topology into account. Finally, experimental results on benchmark show that this method achieves a higher accuracy and stability than other location algorithms.

    Reference
    [1] Bahl P, Padmanabhan VN. RADAR: An in-building RF-based user location and tracking system. In: Proc. of the IEEE INFOCOM 2000, Vol.2. Tel Aviv: IEEE Computer and Communications Societies, 2000. 775?784.
    [2] Nauyen XL, Jordan MI, Sinopoli B. A kernel-based learning approach to ad hoc sensor network localization. ACM Trans. on Sensor Networks, 2005,1(1):134?152. [doi: 10.1145/1077391.1077397]
    [3] Chen YQ, Yang Q, Yin J, Chai XY. Power-Efficient access-point selection for indoor location estimation. IEEE Trans. on Knowledge And Data Engineering, 2006,18(7):877?888. [doi: 10.1109/TKDE.2006.112]
    [4] Biswas P, Lian TC, Wang TC, Ye YY. Semidefinite programming based algorithms for sensor network localization. ACM Trans. on Sensor Networks, 2006,2(2):188?220. [doi: 10.1145/1149283.1149286]
    [5] Madigan D, Ju WH, Krishnan P, Krishnakumar AS, Zorych I. Location estimation in wireless networks: A Bayesian approach. Statistica Sinica, 2006,16(2):495?522.
    [6] Harter A, Hopper A, Steggles P, Wark A, Webster P. The anatomy of a context-aware application. Wireless Networks, 2002,8(2/3): 187?197.
    [7] Girod L, Estrin D. Robust range estimation using acoustic and multimodal sensing. In: Proc. of the IEEE/RSJ Int’l Conf. on Intelligent Robots and Systems (IROS 2001), Vol.3. Maui: IEEE Robotics and Automation Society, 2001. 1312?1320.
    [8] Niculescu D, Nath B. Ad hoc positioning system (APS) using AoA. In: Proc. of the IEEE INFOCOM, IEEE Computer and Communications Societies. San Francisco: IEEE Press, 2003. 1734?1743.
    [9] Wang FB, Shi L, Ren FY. Self-Localization systems and algorithms for wireless sensor networks. Journal of Software, 2005,16(5): 857?868 (in Chinese with English abstract). http://www.jos.org.cn/1000-9825/16/857.htm [doi: 10.1360/jos160857]
    [10] Doherty L, Pister KSJ, Ghaoui LE. Convex position estimation in wireless sensor networks. In: Proc. of the IEEE INFOCOM, IEEE Computer and Communications Societies. Anchorage: IEEE Computer and Communications Societies, 2001. 1655?1663.
    [11] Sun LM, Li JZ, Chen Y, Zhu HS. Wireless Sensor Network. Beijing: Tsinghua University Press, 2005. 141?146 (in Chinese).
    [12] Pan JJF, Kwok JT, Yang Q, Chen YQ. Multidimensional vector regression for accurate and low-cost location estimation in pervasive computing. IEEE Trans. on Knowledge and Data Engineering, 2006,18(9):1181?1193. [doi: 10.1109/TKDE.2006.145]
    [13] Melzer T, Reiter M, Bischof H. Appearance models based on kernel canonical correlation analysis. Pattern Recognition, 2003, 36(9):1961?1971. [doi: 10.1016/S0031-3203(03)00058-X]
    [14] Sun TK, Chen SC. Locality preserving CCA with applications to data visualization and pose estimation. Image and Vision Computing, 2007,25(5):531?543. [doi I: 10.1016/j.imavis.2006.04.014]
    [15] Hardoon DR, Szedmak S, Shawe-Taylor J. Canonical correlation analysis: An overview with application to learning methods. Neural Computation, 2004,16(12):2639?2664. [doi: 10.1162/0899766042321814]
    [16] Bishop E. Differentiable manifolds in complex Euclidean space. Duke Mathematical Journal, 1965,32(1):1?21. [doi: 10.1215/ S0012-7094-65-03201-1]
    [17] Roweis ST, Saul LK. Nonlinear dimensionality reduction by locally linear embedding. Science, 2000,290(5500):2323?2326. [doi: 10.1126/science.290.5500.2323]
    [18] Tenenbaum JB, de Silva V, Langford JC. A global geometric framework for nonlinear dimensionality reduction. Science, 2000, 290(5500):2319?2323. [doi: 10.1126/science.290.5500.2319]
    [19] He XF, Niyogi P. Locality preserving projections (LPP). In: Proc. of the NIPS, Advances in Neural Information Processing Systems. Vancouver: MIT Press, 2004. 96?103.
    [20] He XF, Yan SC, Hu YX, Niyogi P, Zhang HJ. Face recognition using Laplacianfaces. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2005,27(3):328?340. [doi: 10.1109/TPAMI.2005.55]
    [21] Min W, Lu K, He XF. Locality pursuit embedding. Pattern Recognition, 2004,37(4):781?788. [doi: 10.1016/j.patcog.2003.09.005]
    [22] Patwari N, Hero III AO. Manifold learning algorithms for localization in wireless sensor networks. In: Proc. of the IEEE Int’l Conf. on Acoustic Speech and Signal Processing. Montreal: IEEE Press, 2004. 857?860.
    [23] Pan JJF, Yang Q, Chang H, Yeung DY. A manifold regularization approach to calibration reduction for sensor-network based tracking. In: Proc. of the American Association for Artificial Intelligence (AAAI 2006). Boston: AAAI Press, 2006. 988?993.
    附中文参考文献: [9] 王福豹,史龙,任丰原.无线传感器网络中的自身定位系统和算法.软件学报,2005,16(5):857?868. http://www.jos.org.cn/1000- 9825/16/857.htm [doi: 10.1360/jos160857]
    [11] 孙利民,李建中,陈渝,朱红松.无线传感器网络.北京:清华大学出版社,2005.141?146.
    Comments
    Comments
    分享到微博
    Submit
Get Citation

顾晶晶,陈松灿,庄毅.用局部保持典型相关分析定位无线传感器网络节点.软件学报,2010,21(11):2883-2891

Copy
Share
Article Metrics
  • Abstract:5333
  • PDF: 6637
  • HTML: 0
  • Cited by: 0
History
  • Received:September 01,2008
  • Revised:July 08,2009
Links:Institute of Software, CASChina Computer FederationCASNSFC
You are the first2033305Visitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address：4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code：100190
Phone：010-62562563 Fax：010-62562533 Email：jos@iscas.ac.cn
Technical Support：Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063