Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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A MAP Estimate of Optimal Data Association in Multi-Target Tracking

다중표적추적의 최적 데이터결합을 위한 MAP 추정기 개발

  • 이양원 (호남대학교 정보통신공학과)
  • Published : 2003.03.01
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Abstract

We introduced a scheme for finding an optimal data association matrix that represents the relationships between the measurements and tracks in multi-target tracking (MIT). We considered the relationships between targets and measurements as Markov Random Field and assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space that may incorporate most of the important natural constraints. To find the minimizer of the energy function, we derived a new equation in closed form. By introducing Lagrange multiplier, we derived a compact equation for parameters updating. In this manner, a pair of equations that consist of tracking and parameters updating can track the targets adaptively in a very variable environments. For measurements and targets, this algorithm needs only multiplications for each radar scan. Through the experiments, we analyzed and compared this algorithm with other representative algorithm. The result shows that the proposed method is stable, robust, fast enough for real time computation, as well as more accurate than other method.

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References

  1. D. L. Alspach, 'A Gaussian sum approach to multi-target identification tracking problem,' Automatica, vol. 11, pp. 285-296, May 1975 https://doi.org/10.1016/0005-1098(75)90044-8
  2. D. B. Reid, 'An algorithm for tracking multiple targets,' IEEE Trans. on Automat. Contr., vol. 24, pp. 843-854, Dec. 1979 https://doi.org/10.1109/TAC.1979.1102177
  3. Y. Bar-Shalom, 'Extension of probabilistic data associatiation filter in multitarget tracking,' in Proc. 5th Symp. Nonlinear Estimation Theory and its Application, pp. 16-21, Sept. 1974
  4. D. Sengupta and R. A. Iltis, 'Neural solution to the multitarget tracking data association problem,' IEEE Trans. on AES-25, pp. 96-108, Jan. 1989 https://doi.org/10.1109/7.18666
  5. R. Kuczewski, 'Neural network approaches to multitarget tracking,' in proceedings of the IEEE ICNN conference, 1987
  6. T. E. Fortmann, Y. Bar-Shalom and M. Scheffe, 'Sonar Tracking of Multiple Targets Using Joint Probabilistic Data Association,' IEEE J. Oceanic Engineering, vol. OE-8, pp.173-184, July 1983 https://doi.org/10.1109/JOE.1983.1145560
  7. T. E. Fortmann, Y. Bar-Shalom, Tracking and Data Association. Orland Acdemic Press, Inc. p. 224, 1988
  8. J. B. Hiriart-Urruty and C. Lemarrecchal, Convex Analysis and Minimization Algorithms I, Springer-Verlag, 1993
  9. D. G. Luenberger, Linear and Nonlinear Programming, Addition-wesley Publishing Co., 1984
  10. Y. W. Lee and H. Jeong, 'A Neural Network Approach to the Optimal Data Association in Multi-Target Tracking,' Proc. of WCNN'95, INNS Press
  11. R. E. Kalman, 'A new approach to linear filtering and prediction problems,' Trans. ASME, (J. Basic Eng.), vol.82, pp. 34-45, Mar. 1960
  12. R. A. Singer, 'Estimating optimal tracking filter performance for manned maneuvering targets,' IEEE Transactions on Aerospace and Electronic Systems, vol. 6, pp. 473-483, July 1970 https://doi.org/10.1109/TAES.1970.310128
  13. C. S. Won and H. Derin, 'Unsupervised segmentation of noisy and textured images using Markov random fields,' CVGIP: Graphical Models and Image Processing, vol. 54, No. 4, pp. 308-328, July, 1992 https://doi.org/10.1016/1049-9652(92)90078-C
  14. J. Moussouris, 'Gibbs and Markov systems with con straints,' Journal of statistical physics, vol. 10, pp. 11-33, 1974 https://doi.org/10.1007/BF01011714
  15. D. Griffeath, Introduction to random fields, In J. G. Kemeny, J. L. Snell and A. W. Knapp, editors, Denumerable Markov Chains, chapter 12, ppl. 425-458, Springer-Verlag, New York, 2nd edition, 1976