Manifold-based canonical correlation analysis for wireless sensor network localization

Wireless Communications and Mobile Computing

Volumn 12, Issue 15, 2012, Pages 1389-1404

  Gu, Jingjing ^a   Chen, Songcan ^a  

^a NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

Author keywords

Locality Correlation Analysis (LCA); Locality Preserving Canonical Correlation Analysis (LPCCA); Manifold Learning; Sensor Localization; Wireless sensor network

Indexed keywords

CANONICAL CORRELATION ANALYSIS; CORRELATION ANALYSIS; LOCALIZATION ACCURACY; LOCALIZATION ALGORITHM; LOCALIZATION MODELS; LOCATION ALGORITHMS; LOCATION ESTIMATION; MANIFOLD LEARNING; MANIFOLD STRUCTURES; RECEIVED SIGNAL STRENGTH; SENSOR LOCALIZATION; SIGNAL SPACES; TOPOLOGY STRUCTURE; WIRELESS SENSOR;

ALGORITHMS; CORRELATION METHODS; ESTIMATION; SENSORS; WIRELESS SENSOR NETWORKS;

LIFE CYCLE;

EID: 80052929619     PISSN: 15308669     EISSN: 15308677     Source Type: Journal    
DOI: 10.1002/wcm.1071     Document Type: Article

References (35)

1. Doherty L, Pister KSJ, Ghaoui LE,. Convex position estimation in wireless sensor networks. In: Proceedings of the IEEE Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies 2001; 1655-1663. (Pubitemid 32485812)
2. Shang Y, Ruml W, Zhang Y, Fromherz MPJ,. Localization from mere connectivity. Proceedings of the 4th ACM International Symposium on Mobile Ad Hoc Networking & Computing 2003; 201-212.
3. Ou CH,. Range-free node localization for mobile wireless sensor networks. 3rd International Symposium on Wireless Pervasive Computing 2008; 535-539.
4. Harter A, Hopper A, Steggles P, Ward A, Webster P,. The anatomy of a context-aware application. Wireless Networks 1999; 8: 187-197. (Pubitemid 34168126)
5. Girod L, Estrin D,. Robust range estimation using acoustic and multimodal sensing. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems 2001; 1312-1320. (Pubitemid 34683831)
6. Priyantha NB, Miu KL, Balakrishnan H, Teller S,. The cricket compass for context-aware mobile applications. International Conference on Mobile Computing and Networking 2001; 1-14. (Pubitemid 33006699)
7. Wann CD, Lin HY,. Hybrid TOA/AOA estimation error test and non-line of sight identification in wireless location. Wireless Communications and Mobile Computing 2009; 9: 859-873.
8. John K, Gerry C, Eric H,. RightSPOT: A novel sense of location for a smart personal object. Proceedings of Ubicomp 2003; 36-43.
9. Niculescu D, Nath B,. DV based positioning in ad hoc networks. Kluwer Journal of Telecommunication Systems 2003; 22: 267-280.
10. Awad A, Frunzke T, Dressier F,. Adaptive Distance Estimation and Localization in WSN using RSSI Measures. HDigital System Design Architectures, Methods and Tools 2007; 471-478.
11. Fan RF, Jiang H, Wu Sh, Zhang NT,. Ranging error-tolerable localization in wireless sensor networks with inaccurately positioned anchor nodes. Wireless Communications and Mobile Computing 2009; 9: 705-717.
12. Picard JSP, Weiss AJ,. Localization of networks using various ranging bias models. Wireless Communications and Mobile Computing 2008; 8: 553-562.
13. Rahman MZ, Kleeman L,. Paired measurement localization: a robust approach for wireless localization. IEEE Transactions on Mobile Computing 2009; 8: 1087-1102.
14. Biswas P, Lian TC, Wang TC, Ye YY,. Semidefinite programming based algorithms for sensor network localization. ACM Transactions on Sensor Network 2006; 2: 188-220. (Pubitemid 44188494)
15. Wang CQ, Chen JM, Sun YX,. Sensor network localization using kernel spectral regression. Wireless Communications and Mobile Computing 2010; 10: 1045-1054.
16. Patwari N, Hero AO,. Manifold Learning Algorithms for Localization in Wireless Sensor Networks. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing 2004; iii 857-60.
17. Nguyen XL, Jordan MI, Sinopoli B,. A kernel-based learning approach to ad hoc sensor network localization. ACM Transactions on Sensor Networks 2005; 1: 134-152.
18. Duc AT, XuanLong N, Thinh N,. Localization Problem in Sensor Networks: The Machine Learning Approach. Book "Localization Algorithms and Strategies for Wireless Sensor Networks: Monitoring and Surveillance Techniques for Target Tracking" IGI Global, 2009; Chapter XII.
19. Jin YY, Sho WS, Wang WC,. Indoor localization with channel impulse response based fingerprint and nonparametric regression. IEEE Transactions on Wireless Communications 2010; 9: 1120-1127.
20. Pan JJF, Kwok JT, Yang Q,. Multidimensional vector regression for accurate and low-cost location estimation in pervasive computing. IEEE Transactions on Knowledge and Data Engineering, 2006; 9: 1181-1193. (Pubitemid 44192186)
21. Pan JJF, Yang Q, Chang H, Yeung DY,. A Manifold Regularization Approach to Calibration Reduction for Sensor-Network Based Tracking. JT American Association for Artificial Intelligence 2006; 988-993. (Pubitemid 44705405)
22. Sun TK, Chen SC,. Locality preserving CCA with applications to data visualization and pose estimation. Image and Vision Computing 2006; T25: 531-543.
23. Goldsmith A,. Wireless Communications. Cambridge University: New York, USA, 2005; 25-46.
24. Kaemarungsi K, Krishnamurthy P,. Modeling of Indoor Positioning Systems Based on Location Fingerprinting. 23th AnnualJoint Conference of the IEEE Computer and Communications Societies 2004; 1012-1022.
25. Joseph FHJ, Rolph EA, Ronald L, Black WC,. Canonical Correlation Analysis. Multivariate Data Analysis 5thP 1998; Chapter 8.
26. Melzer T, Reiter M, Bischof H,. Appearance models based on kernel canonical correlation analysis. Pattern Recognition 2003; 36: 1961-1971. (Pubitemid 36726816)
27. Hotelling H,. Relations between two sets of variants. Biometrika 1936; 321-377.
28. Hearst MA, Dumais ST, Osman E, Platt J,. Support vector machines. IEEE Intelligent Systems and their Applications 1998; 13: 18-28.
29. Taylor JS, Cristianini N,. Kernel Methods for Pattern Analysis. Cambridge University: New York, USA, 2004; 25-82.
30. Cai D, He X, Han J,. Efficient kernel discriminate analysis via spectral regression. 7th IEEE International Conference on Data Mining, 2007; 427-432.
31. Belkin M, Niyogi P, Sindhwani V,. Manifold regularization: a geometric framework for learning from labeled and unlabeled examples. The Journal of Machine Learning Research 2006; 7: 2399-2434. (Pubitemid 44708005)
32. Tenenbaum JB, Silva VD, Langford JC,. A global geometric framework for nonlinear dimensionality reduction. Science 2000; 290: 2319-2323. (Pubitemid 32041577)
33. He XF, Niyogi P,. Locality preserving projections. Advances in Neural Information Processing Systems 2004; 96-103.
34. Pan JJF, Yang Q,. Co-Localization from Labeled and Unlabeled Data Using Graph Laplacian. Proceedings of the 20th International Joint Conference on Artificial Intelligence 2007; 2166-2171.
35. Barsocchi P, Lenzi S, Chessa S, Giunta G,. A Novel pproach to Indoor RSSI Localization by Automatic Calibration of the Wireless Propagation Model. IEEE 69th Vehicular Technology Conference, 2009; 1-5.