Decentralized sigma-point information filters for target tracking in collaborative sensor networks

IEEE Transactions on Signal Processing

Volumn 53, Issue 8, 2005, Pages 2997-3009

  Vercauteren, Tom ^a,b   Wang, Xiaodong ^a  

^a Fu Foundation School of Engineering and Applied Science   (United States)

^b INRIA   (France)

Author keywords

Decentralized filtering; Information filter; Sensor networks; Sigma point Kalman filter; Target tracking

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; KALMAN FILTERING; MATHEMATICAL MODELS; PROBABILITY; REGRESSION ANALYSIS; SENSOR DATA FUSION; TRACKING (POSITION);

COLLABORATIVE SENSOR NETWORKS; COLLABORATIVE SIGNAL PROCESSING ALGORITHMS; DECENTRALIZED FILTERING; DECENTRALIZED SIGMA POINT INFORMATION FILTERS; DECENTRALIZED TRACKING SCHEME; NONLINEAR DYNAMIC INFERENCE; TARGET TRACKING;

SIGNAL FILTERING AND PREDICTION;

EID: 25444498350     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2005.851106     Document Type: Article

References (27)

1. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "Wireless sensor networks: A survey," Comput. Networks, vol. 38, no. 4, pp. 393-422, 2002.
2. J. Liu, J. Reich, and F. Zhao, "Collaborative in-network processing for target tracking" in EURASIP J. Appl. Signal Processing, Mar. 2003, pp. 378-391.
3. M. Chu, H. Haussecker, and F. Zhao, "Scalable information-driven sensor querying and routing for ad hoc heterogeneous sensor network," Int. J. High Perf. Comput. Appl., vol. 16, no. 3, pp. 293-314, Mar. 2002.
4. A.G.O. Mutambara, Decentralized Estimation and Control for Multisensor Systems. Boca Raton, FL: CRC, 1998.
5. B.D.O. Anderson and J. B. Moore, Optimal Filtering: Prentice-Hall, 1979.
6. S. Haykin, Adaptive Filter Theory, 3rd ed. Englewood Cliffs, NJ: Prentice-Hall, 1996.
7. J. Manyika and H. Durrant-Whyte, Data Fusion and Sensor Management: A Decentralized Information-Theoretic Approach. Englewood Cliffs, NJ: Prentice-Hall, 1994.
8. S.J. Julier, J. K. Uhlmann, and H. F. Durrant-Whyte, "A new method for the nonlinear transformations of means and covariances in filters and estimators," IEEE Trans. Autom. Control, vol. 45, no. 3, pp. 477-482, Mar. 2000.
9. S. J. Julier and J. K. Uhlmann, "The scaled unscented transformation," in Proc. IEEE Amer. Control Conf., May 2002, pp. 4555-4559.
10. K. Ito and K. Xiong, "Gaussian filters for nonlinear filtering problems," IEEE Trans. Autom. Control, vol. 45, no. 5, pp. 910-927, May 2000.
11. T. Lefebvre, H. Bruyninckx, and J. De Schutter, "Comment on "a new method for the nonlinear transformation of means and covariances in filters and estimators"," IEEE Trans. Autom. Control, vol. 47, no. 8, pp. 1406-1408, Aug. 2002.
12. R. van der Merwe and E. Wan, "Sigma-point Kalman filters for probabilistic inference in dynamic state-space models," in Proc. Workshop Adv. in Machine Learning, Montreal, QC, Canada, Jun. 2003.
13. M.J. Coates, Distributed particle filtering for sensor networks, in Proc. Int. Symp. Inf. Process. Sensor Networks, Berkeley, CA, Apr. 2004.
14. M. Rosencrantz, G. Gordon, and S. Thrun, "Decentralized sensor fusion with distributed particle filters," in Proc. Conf. Uncertainty Artificial Intell., Acapulco, Mexico, 2003.
15. A. Doucet, S. J. Godsill, and C. Andrieu, "On sequential Monte Carlo sampling methods for bayesian filtering," Statist. Comput., vol. 10, no. 3, pp. 197-208, 2000.
16. A. Doucet, N. de Freitas, and N. Gordon, Eds., Sequential Monte Carlo Methods in Practice. New York: Springer-Verlag, 2001.
17. H. W. Sorenson and D. L. Alspach, "Recursive Bayesian estimation using Gaussian sums," Automatica, vol. 7, no. 4, pp. 465-479, July 1971.
18. D. L. Alspach and H. W. Sorenson, "Nonlinear Bayesian estimation using Gaussian sum approximations," IEEE Trans. Autom. Control, vol. AC-17, no. 4, pp. 439-448, Aug. 1972.
19. J. Kotecha and P. M. Djuric, "Gaussian sum particle filtering," IEEE Trans. Signal Process., vol. 51, no. 10, pp. 2602-2612, Oct. 2003.
20. Y. Bar-Shalom and T. E. Fortmann, Tracking and Data Association. New York: Academic, 1988.
21. K.C. Chang, C. Y. Chong, and Y. Bar-Shalom, "Joint probabilistic data association in distributed sensor networks," IEEE Trans. Autom. Control, vol. AC-31, no. 10, pp. 889-897, Oct. 1986.
22. H.V. Poor, An Introduction to Signal Detection and Estimation, Second ed. New York: Springer-Verlag, 1994.
23. C. Y. Chong, "Hierarchical estimation," in Proc. 2nd MIT/ONR Workshop C3, Jun. 1979.
24. A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. R. Statist. Soc. (B), vol. 39, no. 1, pp. 1-38, 1977.
25. X. R. Li and V. P. Jilkov, "A survey of maneuvering target tracking: Dynamic models," in Proc. SPIE Signal Data Process. Small Targets, vol. 4048-22, Apr. 2000.
26. T. Rappaport, Wireless Communications: Principles and Practice, Second ed. Englewood Cliffs, NJ: Prentice-Hall, 2002.
27. A. Houles and Y. Bar-Shalom, "Multisensor tracking of a maneuvering target in clutter," IEEE Trans. Aerosp. Electron. Syst., vol. 25, no. 2, pp. 176-189, Mar. 1989.