Detection and tracking of coordinated groups

IEEE Transactions on Aerospace and Electronic Systems

Volumn 47, Issue 1, 2011, Pages 472-502

  Pang, Sze Kim ^a   Li, Jack ^a   Godsill, Simon J ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CLOSELY-SPACED TARGETS; CONTINUOUS TIME; CORRECT GROUP; DETECTION AND TRACKING; DYNAMICAL MODEL; GROUND MOVING TARGET INDICATOR; GROUP MODELS; GROUP STRUCTURE; GROUP TARGETS; GROUP TRACKING; MARKOV CHAIN MONTE CARLO; MODELING INTERACTIONS; RADAR DATA; REPULSIVE FORCES; STOCHASTIC DIFFERENTIAL EQUATIONS; TRACKING ACCURACY;

ALGORITHMS; COMPUTER SIMULATION; DIFFERENTIAL EQUATIONS; INFERENCE ENGINES; MARKOV PROCESSES; STOCHASTIC MODELS; TRACKING (POSITION);

TARGET TRACKING;

EID: 79551631256     PISSN: 00189251     EISSN: None     Source Type: Journal    
DOI: 10.1109/TAES.2011.5705687     Document Type: Article

References (45)

1. Blackman, S. S. and Popoli, R. Design and Analysis of Modern Tracking Systems. Norwood, MA: Artech House, 1999.
2. Bar-Shalom, Y. and Blair, W. D. (Eds.) Multitarget-Multisensor Tracking: Applications and Advances, Vol. III. Norwood, MA: Artech House, 2000.
3. Ristic, B., Arulampalam, S., and Gordon, N. Beyond the Kalman Filter-Particle Filters for Tracking Applications. Norwood, MA: Artech, 2004.
4. Gordon, N. J., Salmond, D. J., and Smith, A. F. M. Novel approach to nonlinear/non-Gaussian Bayesian state estimation. In IEE Proceedings F-Radar and Signal Processing, 140 (Apr. 1993), 107-113.
5. Doucet, A., Godsill, S. J., and Andrieu, C. On sequential Monte Carlo sampling methods for Bayesian filtering. Statistics and Computing, 10 (2000), 197-208.
6. Robert, C. P. and Casella, G. Monte Carlo Statistical Methods (2nd ed.). New York: Springer, 2004.
7. Gilks, W. R., Richardson, S., and Spiegelhalter, D. J. Markov Chain Monte Carlo in Practice. Lynnfield, MA: Chapman and Hall/CRC, 1996.
8. Johnson, S. C. Hierarchical clustering schemes. Psychometrika, 2 (1967), 241-254.
9. MacQueen, J. B. Some methods for classification and analysis of multivariate observations. In Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, 1967, 281-297.
10. Meester, S. G. and MacKay, J. A parametric model for cluster correlated categorical data. Biometrics, 50 (Dec. 1994), 954-963.
11. Blei, D. M., Ng, A. Y., and Jordan, M. I. Latent Dirichlet allocation. Journal of Machine Learning Research, 3 (Mar. 2003), 993-1022.
12. Teh, Y. W., Jordan, M. I., Beal, M. J., and Blei, D. M. Hierarchical Dirichlet processes. Department of Statistics, UC Berkeley, Technical Report 653, 2003. Available online: citeseer.ist.psu.edu/teh03hierarchical.html.
13. Gordon, N. J., Salmond, D. J., and Fisher, D. Bayesian target tracking after group pattern distortion. Signal and Data Processing of Small Targets, SPIE, O. E. Drummond (Ed.), 3163, 1997, 238-248.
14. Gilholm, K. and Salmond, D. Spatial distribution model for tracking extended objects. IEE Proceedings on Radar, Sonar and Navigation, 152 (Oct. 2005), 364-371.
15. Gilholm, K., Godsill, S. J., Maskell, S., and Salmond, D. Poisson models for extended target and group tracking. SPIE Conference: Signal and Data Processing of Small Targets, Aug. 2005.
16. Koch, W. and Feldmann, M. Cluster tracking under kinematical constraints using random matrices. IET Seminar on Target Tracking and Data Fusion: Algorithms and Applications, Apr. 2008, 89-96.
17. Mahler, R. P. S. Statistical Multisource-Multitarget Information Fusions. Norwood, MA: Artech House, 2007.
18. Mahler, R. P. S. An extended first-order Bayes filter for force aggregation. In Proceedings of SPIE, vol. 4728, 2002, 196-207.
19. Mahler, R. P. S. Bayesian cluster detection and tracking using a generalized Cheeseman approach. In Proceedings of SPIE, vol. 5096, 2003, 334-345.
20. Clark, D. and Godsill, S. J. Group target tracking with the Gaussian mixture probability hypothesis density filter. In Proceedings of the Third International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Dec. 2007, 149-154.
21. Mahler, R. P. S. and Zajic, T. Bulk multitarget tracking using a first-order multitarget moment filter. In Proceedings of SPIE, vol. 4729, 2002, 175-186.
22. Reynolds, C. Flocks, herds and schools: A distributed behavioral model. In Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH), 1987, 25-34.
23. Vicsek, T., Czirok, A., Ben-Jacob, E., and Shochet, O. Novel type of phase transition in a system of self-driven particles. Physical Review Letters, 75 (1995), 1226-1229.
24. Cucker, F. and Smale, S. Emergent behavior in flocks. IEEE Transactions on Automatic Control, 52 (2007), 852-862.
25. Oksendal, B. Stochastic Differential Equations: An Introduction with Applications (6th ed.). New York: Springer-Verlag, 2003.
26. Sarkka, S. Recursive Bayesian inference on stochastic differential equations. Ph.D. dissertation, Helsinki University of Technology, Department of Electrical and Communications Engineering, Laboratory of Computational Engineering, 2006.
27. Godsill, S. J. and Vermaak, J. Models and algorithms for tracking using trans-dimensional sequential Monte Carlo. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 3, May 2004, 976-979.
28. Godsill, S. J., Vermaak, J., Ng, W., and Li, J. Models and algorithms for tracking of manoeuvring objects using variable rate particle filters. Proceedings of IEEE, 95, 5 (May 2007), 925-952.
29. Khan, Z., Balch, T., and Dellaert, F. MCMC-based particle filtering for tracking a variable number of interacting targets. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27 (Nov. 2005), 1805-1819.
30. Pang, S. K., Li, J., and Godsill, S. J. Models and algorithms for detection and tracking of coordinated groups. In 5th International Symposium on Image and Signal Processing and Analysis, Sept. 2007, 504-509.
31. Fallon, M. and Godsill, S. J. Multi target acoustic source tracking using track before detect. In IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, Oct. 2007, 102-105.
32. Ulmke, M., Erdinc, O., and Willett, P. Gaussian mixture cardinalized PHD filter for ground moving target tracking. In Proceedings of the 10th International Conference on Information Fusion, July 2007, 1-8.
33. Cameron, P. J. Combinatorics: Topics, Techniques, Algorithms. London: Cambridge University Press, 1994.
34. Godsill, S. J. On the relationship between Markov chain Monte Carlo methods for model uncertainty. Journal of Computational and Graphical Statistics, 10, 2 (2001), 230-248.
35. Vermaak, J., Maskell, S., Briers, M., and Perez, P. A unifying framework for multi-target tracking and existence. In Proceedings of the 8th International Conference on Information Fusion, vol. 1, July 2005, 25-28.
36. Jahangir, M., Coe, D., Blake, A., Kealey, P., and Moate, C. Podsar: A versatile real-time SAR GMTI surveillance and targeting system. In Proceedings of Radar Conference 2008, May 2008, 1-6.
37. Kreucher, C., Morelande, M., Kastella, K., and Hero, A. O. Particle filtering for multitarget detection and tracking. IEEE Transactions on Aerospace and Electronic Systems, 41 (Oct. 2005), 1396-1414.
38. Boers, Y. and Driessen, H. Particle filter based track before detect algorithms. In Proceedings of SPIE Conference on Signal and Data Processing of Small Targets, vol. 5204, Aug. 2003, 20-30.
39. Rutten, M., Gordon, N. J., and Maskell, S. Efficient particle-based track-before-detect in Rayleigh noise. In Proceedings of 7th International Conference on Information Fusion, 2004.
40. Ng, W., Li, J., Godsill, S. J., and Pang, S. K. Multitarget initiation, tracking and termination using Bayesian Monte Carlo methods. The Computer Journal, 50 (Nov. 2007), 674-693.
41. Golightly, A. and Wilkinson, D. J. Bayesian sequential inference for nonlinear multivariate diffusions. Statistics and Computing, (Aug. 2006), 323-338.
42. Gilks, W. R. and Berzuini, C. Following a moving target-Monte Carlo inference for dynamic Bayesian models. Journal of the Royal Statistical Society, Series B (Statistical Methodology), 63 (2001), 127-146.
43. Tierney, L. Markov chains for exploring posterior distributions. Annals of Statistics, 22 (1994), 1701-1786.
44. Ng, W., Li, J., Godsill, S. J., and Vermaak, J. A hybrid approach for online joint detection and tracking for multiple targets. In Proceedings of the IEEE Aerospace Conference, Mar. 2005, 2126-2141.
45. Stengel, R. F. Optimal Control and Estimation. Mineola, NY: Dover, 1994.