Nonparametric belief propagation for self-localization of sensor networks

IEEE Journal on Selected Areas in Communications

Volumn 23, Issue 4, 2005, Pages 809-819

  Ihler, Alexander T ^a   Fisher III, John W ^b   Moses, Randolph L ^c   Willsky, Alan S ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c Ohio State University   (United States)

Author keywords

Algorithms; Calibration; Distributed estimation; Localization; Message passing; Sensor network

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; CALIBRATION; COMPUTATIONAL METHODS; COMPUTER SIMULATION; PROBLEM SOLVING; SENSORS; SIGNAL FILTERING AND PREDICTION; WIRELESS TELECOMMUNICATION SYSTEMS;

DISTRIBUTION ESTIMATION; LOCALIZATION; MESSAGE PASSING; SENSOR NETWORKS;

TELECOMMUNICATION NETWORKS;

EID: 17144417306     PISSN: 07338716     EISSN: None     Source Type: Journal    
DOI: 10.1109/JSAC.2005.843548     Document Type: Article

References (32)

1. IEEE Signal Process. Mag. (Special Issue on Collaborative Information Processing), vol. 19, no. 2, Mar. 2002.
2. Proc. IEEE (Special Issue on Sensor Networks and Applications), vol. 91, Aug. 2003.
3. R. Moses and R. Patterson, "Self-calibration of sensor networks," in Proc. SPIE, vol. 4743, Unattended Ground Sensor Technologies and Applications IV, 2002, pp. 108-119.
4. E. B. Sudderth, A. T. Ihler, W. T. Freeman, and A. S. Willsky, "Nonparametric belief propagation," in Proc. CVPR, 2003, pp. I-605-I-612.
5. J. Pearl, Probabilistic Reasoning in Intelligent Systems. San Mateo, CA: Morgan Kaufman, 1988.
6. R. Moses, D. Krishnamurthy, and R. Patterson, "Self-localization for wireless networks," Eurasip J. Appl. Signal Process., pp. 348-358, 2003.
7. K. Whitehouse, "The design of calamari: An ad hoc localization system for sensor networks," M.S. thesis, Univ. California, Berkeley, CA, 2002.
8. M. W. Trosset, "The formulation and solution of multidimensional scaling problems," Rice Univ., Houston, TX, Tech. Rep. TR93-55, 1993.
9. K. Langendoen and N. Reijers, "Distributed localization in wireless sensor networks: A quantitative comparison," Comput. Netw., vol. 43, no. 4, pp. 499-518, Nov. 2003.
10. N. Patwari and A. Hero, "Relative location estimation in wireless sensor networks," IEEE Trans. Signal Process., vol. 51, pp. 2137-2148, Aug. 2003.
11. L. Doherty, L. E. Ghaoui, and K. S. J. Pister, "Convex position estimation in wireless sensor networks," in Proc. INFOCOM, Apr. 2001, pp. 1655-1663.
12. A. Savvides, H. Park, and M. B. Srivastava, "The bits and flops of the ra-hop multilateration primitive for node localization problems," in Proc. ACM Workshop Wireless Sensor Netw. Appl., 2003, pp. 112-121.
13. N. Priyantha, H. Balakrishnan, E. Demaine, and S. Teller, "Anchor-free distributed localization in sensor networks," Lab. Comput. Sci., Mass. Inst. Technol., Cambridge, MA, Tech. Rep. 892, 2003.
14. M. Fazel, H. Hindi, and S. P. Boyd, "Log-det heuristic for matrix rank minimization with applications to Hankel and Euclidean distance matrices," in Proc. Amer. Control Conf., 2003, pp. 2156-2162.
15. S. Geman and D. Geman, "Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images," IEEE Trans. Pattern Anal. Machine Intell., vol. 6, no. 6, pp. 721-741, Nov. 1984.
16. J. S. Yedidia, W. T. Freeman, and Y. Weiss, "Constructing free energy approximations and generalized belief propagation algorithms," MERL, Tech. Rep. 2004-040, 2004.
17. M. J. Wainwright and M. I. Jordan, "Graphical models, exponential families, and variational inference," Dept. of Statistics, Univ. California, Berkeley, CA, Tech. Rep. 629, 2003.
18. A. T. Ihler, J. W. Fisher, III, R. L. Moses, and A. S. Willsky, "Non-parametric belief propagation for self-calibration in sensor networks," in Proc. IPSN, 2004, pp. 225-233.
19. K. Murphy, Y. Weiss, and M. Jordan, "Loopy-belief propagation for approximate inference: An empirical study," in Proc. UAI, vol. 15, Jul. 1999, pp. 467-475.
20. D. Koller, U. Lerner, and D. Angelov, "A general algorithm for approximate inference and its application to hybrid Bayes nets," in Proc. UAI, vol. 15, 1999, pp. 324-333.
21. J. M. Coughlan and S. J. Ferreira, "Finding deformable shapes using loopy belief propagation," in Proc. ECCV, vol. 7, May 2002, pp. 463-368.
22. P. Felzenszwalb and D. Huttenlocher, "Belief propagation for early vision," in Proc. CVPR, 2004, pp. I-261-I-268.
23. B. Silverman, Density Estimation for Statistics and Data Analysis. London, U.K.: Chapman & Hall, 1986.
24. M. Isard, "PAMPAS: Real-valued graphical models for computer vision," in Proc. CVPR, 2003, pp. I-613-I-620.
25. A. T. Ihler, E. B. Sudderth, W. T. Freeman, and A. S. Willsky, "Efficient multiscale sampling from products of Gaussian mixtures," in Proc. NIPS, vol. 17, 2003.
26. Sequential Monte Carlo Methods in Practice, A. Doucet, N. de Freitas, and N. Gordon, Eds., Springer-Verlag, New York, 2001.
27. M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, "A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking," IEEE Trans. Signal Process., vol. 50, no. 2, pp. 174-188, Feb. 2002.
28. L. Chen, M. Wainwright, M. Cetin, and A. Willsky, "Data association based on optimization in graphical models with application to sensor networks," Math. Comput. Modeling, 2004, submitted for publication.
29. A. T. Ihler, J. W. Fisher, III, and A. S. Willsky, "Message errors in belief propagation," Lab. Inf. Decision Syst., Mass. Inst. Technol., Cambridge, MA, Tech. Rep. TR-2602, 2004.
30. Y. Mao and A. Banihashemi, "Decoding low-density parity check codes with probabilistic scheduling," IEEE Commun. Lett., vol. 5, no. 10, pp. 414-416, Oct. 2001.
31. M. J. Wainwright, T. S. Jaakkola, and A. S. Willsky, "Tree-based reparameterization analysis of sum-product and its generalizations," IEEE Trans. Inf. Theory, vol. 49, pp. 1120-1146, May 2003.
32. A. T. Ihler, J. W. Fisher, III, and A. S. Willsky, "Communication-Constrained Inference," Lab. Inf. Decision Syst., Mass. Inst. Technol., Cambridge, MA, Tech. Rep. TR-2601, 2004.