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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 938242, 11 pages
http://dx.doi.org/10.1155/2014/938242
Research Article

Unknown Clutter Estimation by FMM Approach in Multitarget Tracking Algorithm

1The Institute of Integrated Automation, MOE KLINNS Lab, School of Electronics and Information, Xi’an Jiaotong University, Xi’an 710049, China
2Xi’an Research Institute of Hi-Tech, Hongqing Town, Xi’an 710025, China

Received 28 August 2013; Accepted 19 December 2013; Published 16 March 2014

Academic Editor: Shuli Sun

Copyright © 2014 Ning Lv et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Y. Bar-Shalom and T. E. Fortmann, Tracking and Data Association, vol. 179, Academic Press, San Diego, Calif, USA, 1988. View at MathSciNet
  2. Y. Bar-Shalom and L. Xiao-Rong, Multitarget-Multisensor Tracking: Principles and Techniques, YBS Publishing, Storrs, Conn, USA, 1995.
  3. S. Blackman and R. Popoli, Design and Analysis of Modern Tracking Systems, Artech House, Boston, Mass, USA, 1999.
  4. H. Samet, “K-nearest neighbor finding using MaxNearestDist,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 2, pp. 243–252, 2008. View at Publisher · View at Google Scholar · View at Scopus
  5. S. P. Puranik and J. K. Tugnait, “Tracking of multiple maneuvering targets using multiscan JPDA and IMM filtering,” IEEE Transactions on Aerospace and Electronic Systems, vol. 43, no. 1, pp. 23–35, 2007. View at Publisher · View at Google Scholar · View at Scopus
  6. H. Zhang, X.-P. Fan, and Z.-H. Qu, “Mobile robot adaptive monte carlo localization based on multiple hypothesis tracking,” Acta Automatica Sinica, vol. 33, no. 9, pp. 941–946, 2007. View at Publisher · View at Google Scholar · View at Scopus
  7. R. P. S. Mahler, “Multitarget bayes filtering via first-order multitarget moments,” IEEE Transactions on Aerospace and Electronic Systems, vol. 39, no. 4, pp. 1152–1178, 2003. View at Publisher · View at Google Scholar · View at Scopus
  8. R. Mahler, “PHD filters of higher order in target number,” IEEE Transactions on Aerospace and Electronic Systems, vol. 43, no. 4, pp. 1523–1543, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. W. Liu and C. Han, “Multitarget tracking algorithm based on finite mixture models and equivalent measurement,” in Proceedings of the 11th International Conference on Information Fusion (FUSION '08), pp. 1544–1551, July 2008. View at Publisher · View at Google Scholar · View at Scopus
  10. G. McLachlan and D. Peel, Finite Mixture Models, Wiley-Interscience, New York, NY, USA, 2000. View at Publisher · View at Google Scholar · View at MathSciNet
  11. B.-N. Vo, S. Singh, and A. Doucet, “Sequential Monte Carlo methods for multi-target filtering with random finite sets,” IEEE Transactions on Aerospace and Electronic Systems, vol. 41, no. 4, pp. 1224–1245, 2005. View at Publisher · View at Google Scholar · View at Scopus
  12. B.-N. Vo and W.-K. Ma, “The Gaussian mixture probability hypothesis density filter,” IEEE Transactions on Signal Processing, vol. 54, no. 11, pp. 4091–4104, 2006. View at Publisher · View at Google Scholar · View at Scopus
  13. K. Panta, B.-N. Vo, and S. Singh, “Novel data association schemes for the probability hypothesis density filter,” IEEE Transactions on Aerospace and Electronic Systems, vol. 43, no. 2, pp. 556–570, 2007. View at Publisher · View at Google Scholar · View at Scopus
  14. M. A. T. Figueiredo and A. K. Jain, “Unsupervised learning of finite mixture models,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 3, pp. 381–396, 2002. View at Publisher · View at Google Scholar · View at Scopus
  15. P. J. Green, “Reversible jump Markov chain monte carlo computation and Bayesian model determination,” Biometrika, vol. 82, no. 4, pp. 711–732, 1995. View at Publisher · View at Google Scholar · View at Scopus
  16. I. R. Goodman, R. P. S. Mahler, and H. T. Nguyen, Mathematics of Data Fusion, vol. 37, Kluwer Academic, Norwell, Mass, USA, 1997. View at MathSciNet
  17. X. R. Li and V. P. Jilkov, “Survey of maneuvering target tracking: dynamic models,” in Proceedings of the International Conference on Signal and Data Processing of Small Targets, Proceedings of SPIE, pp. 212–235, April 2000. View at Scopus
  18. J. R. Hoffman and R. P. S. Mahler, “Multitarget miss distance via optimal assignment,” IEEE Transactions on Systems, Man, and Cybernetics A, vol. 34, no. 3, pp. 327–336, 2004. View at Publisher · View at Google Scholar · View at Scopus