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2011-06-20
Fuzzy-Control-Based Particle Filter for Maneuvering Target Tracking
By
Progress In Electromagnetics Research, Vol. 118, 1-15, 2011
Abstract
In this paper, we propose a novel fuzzy-control-based particle filter (FCPF) for maneuvering target tracking, which combines the advantages of standard particle filter (SPF) and multiple model particle filter (MMPF). That is, the SPF is adopted during non-maneuvering movement while the MMPF is adopted during maneuvering movement. The key point of the FCPF is to use a fuzzy controller, which could imitate the thoughts of human beings in some degree, to detect the target's maneuver and use a backward correction sub-algorithm to alleviate the performance degradation of MMPF caused by detection delay. Simulation results indicate that the proposed algorithm has a much better tracking accuracy than the SPF while keeps approximately equal computational complexity. Compared with MMPF, both algorithms have no tracking lost, but the tracking accuracy of the proposed FCPF is a little better than the MMPF, and the FCPF consumes about 66% computation time of the MMPF. Thus, the proposed algorithm offers a more effective way for maneuvering target tracking.
Citation
Xianfeng Wang, Jun-Feng Chen, Zhi-Guo Shi, and Kang Chen, "Fuzzy-Control-Based Particle Filter for Maneuvering Target Tracking," Progress In Electromagnetics Research, Vol. 118, 1-15, 2011.
doi:10.2528/PIER11051907
References

1. Zang, W., Z. G. Shi, S. C. Du, and K. S. Chen, "Novel roughening method for reentry vehicle tracking using particle filter," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 14, 1969-1981, 2007.
doi:10.1163/156939307783152975

2. Liu, H. Q. and H. C. So, "Target tracking with line-of-sight identification in sensor networks under unknown measurement noises," Progress In Electromagnetics Research, Vol. 97, 373-389, 2009.
doi:10.2528/PIER09090701

3. Kural, F., F. Arikan, O. Arikan, and M. Efe, "Performance evaluation of track association and maintenance for a MFPAR With Doppler velocity measurements," Progress In Electromagnetics Research, Vol. 108, 249-275, 2010.
doi:10.2528/PIER10070801

4. Hussain, S. S. I., J. Bigham, C. Parini, and M. I. Shiekh, "Tracking performance of an adaptive transmit beamspace beamformer in dynamic miso wireless channels," Progress In Electromagnetics Research C, Vol. 20, 269-287, 2011.

5. Di, M., E. M. Joo, and L. H. Beng, "A comprehensive study of kalman filter and extended kalman filter for target tracking in wireless sensor networks," IEEE International Conference on Systems Man and Cybernetics, 2792-2797, Singapore, 2008.

6. Arulampalam, M. S., S. Maskell, N. Gordon, and T. Clapp, "A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking," IEEE Transactions on Signal Processing, 2002.

7. Li, Y., Y.-J. Gu, Z.-G. Shi, and K. S. Chen, "Robust adaptive beamforming based on particle filter with noise unknown," Progress In Electromagnetics Research, Vol. 90, 151-169, 2009.
doi:10.2528/PIER09010302

8. Liu, H.-Q., H.-C. So, F. K. W. Chan, and K. W. K. Lui, "Distributed particle filter for target tracking in sensor networks," Progress In Electromagnetics Research C, Vol. 11, 171-182, 2009.
doi:10.2528/PIERC09092905

9. Zheng, N., Y. Pan, and X. Yan, "Local weight mean comparison scheme and architecture for high-speed particle filters," Electronics Letters, Vol. 47, No. 2, 142-144, 2011.
doi:10.1049/el.2010.3375

10. Wang, Q., J. Li, M. Zhang, and C. Yang, "H-infinity filter based particle filter for maneuvering target tracking," Progress In Electromagnetics Research B, Vol. 30, 103-116, 2011.

11. Bi, S. Z. and X. Y. Ren, "Maneuvering target doppler-bearing tracking with signal time delay using interacting multiple model algorithms ," Progress In Electromagnetics Research, Vol. 87, 15-41, 2008.
doi:10.2528/PIER08091501

12. Shi, Z. G., S. H. Hong, and K. S. Chen, "Tracking airborne targets hidden in blind doppler using current statistical model particle filter," Progress In Electromagnetics Research, Vol. 82, 227-240, 2008.
doi:10.2528/PIER08012407

13. Chen, J. F., Z.-G. Shi, S.-H. Hong, and K. S. Chen, "Grey prediction based particle filter for maneuvering target tracking," Progress In Electromagnetics Research, Vol. 93, 237-254, 2009.
doi:10.2528/PIER09042204

14. Li, X. R. and V. P. Jilkov, "Survey of maneuvering target tracking --- Part V: Multiple-model methods," IEEE Transactions on Aerospace and Electronic Systems, Vol. 41, No. 4, 1255-1321, 2005.
doi:10.1109/TAES.2005.1561886

15. Ru, J. F., A. Bashi, and X. R. Li, "Performance comparison of target maneuver onset detection algorithms," Processing 2004 SPIE Conference on Signal and Data Processing of Small Targets, Vol. 5428, Orlando, USA, 2004.

16. Li, X. R. and V. P. Jilkov, "A survey of maneuvering target tracking --- Part IV: Decision-based methods," Proceedings of SPIE Conference on Signal and Data Processing of Small Targets, 4728-4760, Orlando, USA, 2002.

17. Li, X. R. and Y. Bar-Shalom, "Multiple-model estimation with variable structure," IEEE Transactions on Automatic Control, Vol. 41, No. 4, 478-493, 1996.
doi:10.1109/9.489270

18. Zadeh, L. A., "Fuzzy sets," Information and Control, Vol. 8, 338-353, 1965.
doi:10.1016/S0019-9958(65)90241-X

19. Zadeh, L. A., "A rationale for fuzzy control," Journal of Dynamic Systems, Measurement and Control, Vol. 94, No. 1, 3-4, 1972.
doi:10.1115/1.3426540

20. Mamdani, E. H., "Application of fuzzy algorithms for control of simple dynamic plant," Proceedings of The Institution of Electrical Engineers Control and Science, Vol. 121, No. 12, 1585-1588, 1974.
doi:10.1049/piee.1974.0328

21. Lee, C. C., "Fuzzy logic in control systems: Fuzzy logic controller --- Part I," IEEE Transactions on Systems, Man, and Cybernetics, Vol. 20, No. 2, 404-418, 1990.
doi:10.1109/21.52551

22. Chen, C. T., "A fuzzy approach to select the location of the distribution center," Fuzzy Sets and Systems, Vol. 118, No. 1, 65-73, 201.
doi:10.1016/S0165-0114(98)00459-X

23. Ristic, B., S. Arulampalam, and N. Gordon, Beyond the Kalman Filter: Particle Filter for Tracking Applications, Artech House, 2004.

24. Arulampalam, M. S., N. Gordon, M. Orton, and B. Ristic, "A variable structure multiple model particle filter for GMTI tracking ," Proceedings of the Fifth International Conference on Information Fusion, 2002.