Group object structure and state estimation with evolving networks and Monte Carlo methods

IEEE Transactions on Signal Processing

Volumn 59, Issue 4, 2011, Pages 1383-1396

  Gning, Amadou ^a   Mihaylova, Lyudmila ^a   Maskell, Simon ^b   Pang, Sze Kim ^c   Godsill, Simon ^c  

^a LANCASTER UNIVERSITY   (United Kingdom)

^b QINETIQ   (United Kingdom)

^c UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

Evolving graphs; group target tracking; MetropolisHastings step; Monte Carlo methods; nonlinear estimation; random graphs

Indexed keywords

EVOLVING GRAPHS; GROUP TARGET TRACKING; METROPOLIS-HASTINGS STEP; MONTE CARLO; NON-LINEAR ESTIMATION; RANDOM GRAPHS;

ESTIMATION; GRAPH THEORY; GRAPHIC METHODS; MOTION ESTIMATION; TARGET TRACKING; UNCERTAINTY ANALYSIS;

MONTE CARLO METHODS;

EID: 79952644978     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2010.2103062     Document Type: Article

References (32)

1. M. Ulmke and W. Koch, "Road-map assisted ground moving target tracking," IEEE Trans. Aesrosp. Electron. Syst., vol. 42, no. 4, pp. 1264-1274, 2006. (Pubitemid 46502256)
2. A. Jadbabaie, J. Lin, and A. Morse, "Coordination of groups of mobile autonomous agents using nearest neighbor rules," IEEE Trans. Autom. Control, vol. 48, no. 6, pp. 988-1001, Jun. 2003.
3. J. Marshall, M. Brouke, and B. Francis, "A pursuit strategy for wheeled-vehicle formations," in Proc. 42nd IEEE Conf. Decision Contr., 2003, vol. 3, pp. 2555-2560.
4. H. Axelsson, A. Muhammad, and M. Egerstedt, "Autonomous formation switching for multiple, mobile robots," in Proc. IFAC Conf. Anal. Des. Hybrid Syst., 2003.
5. D. Dimarogonas and K. Kyriakopoulos, "A connection between formation control and flocking behavior in nonholonomic multiagent systems," in Proc. IEEE Int. Conf. Robot. Autom., 2006.
6. R. Mahler, Statistical Multisource-Multitarget Information Fusion. Boston, MA: Artech House, 2007.
7. S. K. Pang, S. J. Godsill, F. Septier, J. Li, and S. Hill, "Sequential inference for dynamically evolving groups of objects," in Bayesian Time Series Models, D. Barber, A. T. Cemgil, and S. Chiappa, Eds. Cambridge, U.K.: Cambridge Univ. Press, 2010.
8. W. Konle, "Group tracking in an air surveillance system," in LNCS. New York: Springer, 2009, pp. 2434-2444.
9. S. K. Pang, J. Li, and S. J. Godsill, "Detection and tracking of coordinated groups," IEEE Trans. Aesrosp. Electron. Syst., no. 1, 2011.
10. T. Vicsek, A. Czirók, E. Ben-Jacob, I. Cohen, and O. Shochet, "Novel type of phase transition in a system of self-driven ppagess," Phys. Rev. Lett., vol. 75, no. 6, pp. 1226-1229, Aug. 1995.
11. D. Helbing, "Traffic and related self-driven many-ppages systems," Rev. Modern Phys., vol. 73, pp. 1067-1141, 2002.
12. M. J. Waxman and O. E. Drummond, O. E. Drummond, Ed., "A bibliography of cluster (group) tracking," in Proc. SPIE Signal Data Process. Small Targets, Aug. 2004, vol. 5428, pp. 551-560.
13. S. N. Dorogovtsev and J. F. F. Mendes, "Evolution of networks," Adv. Phys., vol. 51, no. 4, pp. 1079-1187, Jun 1, 2002. (Pubitemid 34759032)
14. R. Albert and A.-L. Barab́si, "Statistical mechanics of complex networks," Rev. Mod. Phys., vol. 74, no. 1, pp. 47-97, 2002.
15. Y. Bar-Shalom and W. Blair, Multitarget-Multisensor Tracking: Applications and Advances. Boston, MA: Artech House, 2000, vol. III.
16. S. Blackman and R. Popoli, Design and Analysis of Modern Tracking Systems. Boston, MA: Artech House Radar Library, 1999.
17. D. Clark and S. Godsill, "Group target tracking with the Gaussian mixture probability density filter," in Proc. 3rd Int. Conf. Intell. Sens., Sens. Netw. Inf. Process., 2007.
18. D. Clark, B. Vo, B.-N. Vo, and S. Godsill, "Nonlinear implementations of Gaussian mixture probability density filters," IEEE Trans. Signal Process., 2007, submitted for publication.
19. S. K. Pang, J. Li, and S. Godsill, "Models and algorithms for detection and tracking of coordinated groups," in Proc. IEEE Aerosp. Conf.,Mar. 2008.
20. W. Koch and R. Saul, "A Bayesian approach to extended object tracking and tracking of loosely structured target groups," in Proc. 8th Int. Conf. Inf. Fusion, 2005, ISIF.
21. D. Salmond and N. Gordon, "Group and extended object tracking," in Proc. IEE Colloquium. Target Tracking: Algorithms Applicat., London, U.K., 1999, pp. 16/1-16/4.
22. K. Gilholm, S. Godsill, S. Maskell, and D. Salmond, "Poisson models for extended target and group tracking," in Proc. SPIE 5913, 2005.
23. B. Ristic, S. Arulampalam, and N. Gordon, Beyond the Kalman Filter: Ppages Filters For Tracking Applications. Boston, MA: Artech House, 2004.
24. W. Koch and M. Feldmann, "Cluster tracking under kinematical constraints using random matrices," Robot. Autonomous Syst., vol. 57, no. 3, pp. 296-309, 2009.
25. W. Koch, "On exploiting 'negative' sensor evidence for target tracking and sensor data fusion," Inf. Fusion, vol. 8, no. 1, pp. 28-39, 2007. (Pubitemid 44781322)
26. P. Erdös and A. Renyi, "On the evolution of random graphs," Publ. Math. Inst. Hung. Acad. Sci., vol. 5, pp. 17-61.
27. X. R. Li and V. Jilkov, "A survey of maneuvering target tracking. Part I: Dynamic models," IEEE Trans. Aerosp. Electr. Syst., vol. 39, no. 4, pp. 1333-1364, 2003.
28. Y. Bar-Shalom and X. Li, Estimation and Tracking: Principles, Techniques and Software. Boston, MA: Artech House, 1993.
29. M. AlRashidi and M. El-Hawary, "A survey of ppages swarm optimization applications in electric power systems," IEEE Trans. Evol. Computat., vol. 13, no. 4, pp. 913-918, Aug. 2009.
30. A. Gning, L. Mihaylova, S. Maskell, S. K. Pang, and S. Godsill, "Evolving networks for group object motion estimation," in Proc. IET Seminar Target Tracking Data Fusion: Algorithms Applicat., Birmingham, U.K., 2008, pp. 99-106.
31. A. Gning, L. Mihaylova, S. Maskell, S. K. Pang, and S. Godsill, "Ground target group structure and state estimation with ppages filtering," in Proc. Int. Conf. Inf. Fusion, Cologne, Germany, 2008.
32. A. Doucet, N. Freitas, and E. N. Gordon, Sequential Monte Carlo Methods in Practice. New York: Springer-Verlag, 2001.