Some assignment problems arising from multiple target tracking

Mathematical and Computer Modelling

Volumn 43, Issue 9-10, 2006, Pages 1074-1091

  Poore, Aubrey B ^a   Gadaleta, Sabino ^a  

^a NUMERICA CORPORATION   (United States)

Author keywords

Group assignment; Multi dimensional assignment; Multiple hypothesis correlation; Multiple hypothesis tracking; Target tracking

Indexed keywords

ALARM SYSTEMS; ALGORITHMS; DATA ACQUISITION; DECISION MAKING; OPTIMIZATION; REAL TIME SYSTEMS; SENSORS; VELOCITY;

GROUP ASSIGNMENT; MULTI-DIMENSIONAL ASSIGNMENT; MULTIPLE HYPOTHESIS CORRELATION; MULTIPLE HYPOTHESIS TRACKING (MHT); TARGET TRACKING;

PROBLEM SOLVING;

EID: 33646061635     PISSN: 08957177     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.mcm.2005.05.026     Document Type: Article

References (49)

1. Bar-Shalom Y., Li X.R., and Kirubarajan T. Estimation with Applications to Tracking and Navigation (2001), John Wiley & Sons, Inc., New York
2. Bar-Shalom Y., and Li X.-R. Multitarget-Multisensor Tracking: Principles and Techniques (1995), YBS
3. Blackman S., and Popoli R. Design and Analysis of Modern Tracking Systems (1999), Artech House, Norwood, MA
4. Poore A.B., and Robertson III A.J. A new class of Lagrangian relaxation based algorithm for a class of multidimensional assignment problems. Computational Optimization and Applications 8 (1997) 129-150
5. Poore A.B., Lu S., and Suchomel B.J. Data association using multiple frame assignments. Handbook of Multisensor Data Fusion (2001), CRC Press LLC
6. Poore A.B. Multidimensional assignment formulation of data association problems arising from multitarget tracking and multisensor data fusion. Computational Optimization and Applications 3 (1994) 27-57
7. A.B. Poore, S. Lu, B. Suchomel, Network MFA tracking architectures, in: O.E. Drummond (Ed.), Proceedings of SPIE Conference on Small Targets 2001, 2001
8. Blackman S. Multiple Target Tracking with Radar Applications (1986), Artech House, Dedham, MA
9. In: Bar-Shalom Y. (Ed). Multitarget-Multisensor Tracking: Advanced Applications (1990), Artech House, Dedham, MA
10. In: Bar-Shalom Y. (Ed). Multitarget-Multisensor Tracking: Applications and Advances (1992), Artech House, Dedham, MA
11. In: Bar-Shalom Y., and Blair W.D. (Eds). Multitarget-Multisensor Tracking: Applications and Advances III (2000), Artech House, Dedham, MA
12. Moore J.R., and Blair W.D. Multitarget/Multisensor Tracking: Applications and Advances III (2000)
13. Joint Composite Tracking Network, http://seal.gatech.edu/jctn/
14. Jonker R., and Volgenant A. A shortest augmenting path algorithm for dense and sparse linear assignment problems. Computing 38 (1987) 325-340
15. Drummond O.E., Castañon D.A., and Bellovin M.S. Comparison of 2-d assignment algorithms for sparse, rectangular, floating point, cost matrices. Journal of the SDI Panels on Tracking, Institute for Defense Analyses (1990) 4-81-4-97
16. Levedahl M. Performance comparison of 2-D assignment algorithms for assigning truth objects to measured tracks. Proceedings of the SPIE, Conference on Signal and Data Processing of Small Targets vol. 4048 (2000) 380-389
17. Bertsekas D.P. Network optimization: Continuous and Discrete Models (1998), Athena Scientific, Belmont, MA
18. A.B. Poore, N. Rijavec, T. Barker, M. Munger, Data association problems posed as multidimensional assignment problems: Numerical simulations, in: O.E. Drummond (Ed.), Signal and Data Processing of Small Targets 1954 (Proceedings of the SPIE) 1993, pp. 564-573
19. Cormen T., Leiserson C., Rivest R., and Stein C. Introduction to Algorithms (2001), MIT Press
20. Bertsekas D.P. Nonlinear Programming (1999), Athena Scientific, Belmont, MA
21. Garvey M., and Johnson D. Computers and Intractability: A guide to the theory of NP-Completeness (1979), W.H. Freeman & Co., CA
22. Glover F., and Laguna M. Tabu Search (1997), Kluwer Academic Publishers
23. Murphey R.A., Pardalos P.M., and Pitsoulis L.S. A greedy randomized adaptive search procedure for the multitarget multisensor tracking problem. In: Pardalos P.M., and Du D.-Z. (Eds). Network design: Connectivity and facilities location. DIMACS Series on Discrete Mathematics and Theoretical Computer Science vol. 40 (1998), American Mathematical Society 277-301
24. Robertson A.J. A set of greedy randomized adaptive local search procedure (GRASP) implementations for the multidimensional assignment problem. Computational Optimization and Applications 19 (2001) 145-164
25. Pattipati K.R., Popp R.L., and Kirubarajan T. Survey of assignment techniques for multitarget tracking. In: Bar-Shalom Y., and Blair W.D. (Eds). Multitarget-Multisensor Tracking: Advanced Applications vol. III (2000), Artech House, Boston 77-159 (Chapter 2)
26. Hiriart-Urruty J.-B., and Lemarechal C. Convex Analysis and Minimization Algorithms I. A Series of Comprehensive Studies in Mathematics vol. I (1993), Springer-Verlag, Berlin
27. Hiriart-Urruty J.-B., and Lemarechal C. Convex Analysis and Minimization Algorithms II. A Series of Comprehensive Studies in Mathematics vol. II (1993), Springer-Verlag, Berlin
28. Goldberg D.E. Genetic Algorithms in Search, Optimization, and Machine Learning (1989), Addison-Wesley Professional
29. Frieze A.M., and Yadegar J. An algorithm for solving 3-dimensional assignment problems with application to scheduling a teaching practice. Journal of the Operational Research Society 32 (1981) 989-995
30. Poore A.B., and Yan X. Partial branch and bound for improved data association in multiframe processing. In: Kadar I. (Ed). Signal Processing, Sensor Fusion, and Target Recognition VIII vol. 3720 (April 1999), SPIE
31. Poore A.B., and Yan X. Some algorithmic improvements in multiple-frame most probable hypothesis tracking. In: Drummond O.E. (Ed). Proceedings of SPIE no. 3809 (1999), SPIE 435-443
32. Gadaleta S., Klusman M., Poore A.B., and Slocumb B.J. Multiple frame cluster tracking. Signal and Data Processing of Small Targets, in: SPIE vol. 4728 (2002) 275-289
33. Theodoridis S., and Koutroumbas K. Pattern Recognition (1999), Academic Press
34. MacQueen J. Some methods for classification and analysis of multivariate observations. Proceedings of the Fifth Berkeley Symposium on Mathematical statistics and probability (1967), University of California Press 281-297
35. Dempster A., Laird N., and Rubin D. Maximum-likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society B 39 (1977) 39
36. Briers M., Maskell S., and Philpott M. Two-dimensional assignment with merged measurements using Lagrangian relaxation. In: Drummond O. (Ed). Proceedings of SPIE vol. 5204 (2004), SPIE
37. S. Gadaleta, A.B. Poore, B.J. Slocumb, Some assignment problems arising from cluster tracking, in: ORNL Workshop on Signal Processing, Communications and Chaotic Systems: A Tribute to Rabinder N. Madan, Harbor Island Conference Center, June 20, 2002
38. Poore A.B., and Gadaleta S. The group assignment problem arising in multiple target tracking. Theory and Algorithms for Cooperative Systems (2004), World Scientific
39. S. DeVries, R. Vohra, Combinatorial auctions: A survey, 2000
40. C. Li, K. Sycara, Algorithms for combinatorial coalition forming and payoff division in an electronic marketplace, Technical Report, Carnegie Mellon University, 2001
41. Blair W.D., Slocumb B.J., Brown G.C., and Register A.H. 2-d measurement-to-track association for tracking closely spaced, possibly unresolved, Rayleigh targets: Idealized resolution. Aerospace Conference Proceedings 4 (2002) 4.1543-4.1550
42. H. Chen, T. Kirubarajan, Y. Bar-Shalom, Tracking of spawning targets with multiple finite resolution sensors, in: Proceedings International Conference on Information Fusion, FUSION 2002, Annapolis, MD, July 2002, 2002, pp. 1511-1518
43. Gadaleta S., Poore A., and Slocumb B. Pixel-cluster decomposition tracking for multiple IR-sensor surveillance. Signal and Data Processing of Small Targets. SPIE vol. 5204 (2003) 270-282
44. Chong C.-Y., Mori S., Barker W., and Chang K.-C. Architectures and algorithms for track association and fusion. IEEE AES Systems Magazine 15 (2000) 5-13
45. Murty K. An algorithm for ranking all the assignments in order of increasing cost. Operations Research 16 (1968) 682-687
46. Blackman S., and Popoli R. Design and Analysis of Modern Tracking Systems (1999), Artech House, Boston, London
47. A.B. Poore, S. Gadaleta, B.J. Slocumb, Multiple hypothesis correlation in track-to-track fusion management, in: Handbook of Modelling for Discrete Optimization, Kluwer International Series in Operations Research and Management Science, Kluwer (in press)
48. Slocumb B.J., and Blair W.D. Maximum likelihood narrowband radar data segmentation and centroid processing. Proceedings of the SPIE, Conference on Signal and Data Processing of Small Targets vol. 5204 (2003) 648-661
49. B.J. Slocumb, Data segmentation/centroid processing with tracker feedback for tracking closely spaced objects, Technical Report, Numerica Corporation, 2003