Vol. 118
Latest Volume
All Volumes
PIER 176 [2023] PIER 175 [2022] PIER 174 [2022] PIER 173 [2022] PIER 172 [2021] PIER 171 [2021] PIER 170 [2021] PIER 169 [2020] PIER 168 [2020] PIER 167 [2020] PIER 166 [2019] PIER 165 [2019] PIER 164 [2019] PIER 163 [2018] PIER 162 [2018] PIER 161 [2018] PIER 160 [2017] PIER 159 [2017] PIER 158 [2017] PIER 157 [2016] PIER 156 [2016] PIER 155 [2016] PIER 154 [2015] PIER 153 [2015] PIER 152 [2015] PIER 151 [2015] PIER 150 [2015] PIER 149 [2014] PIER 148 [2014] PIER 147 [2014] PIER 146 [2014] PIER 145 [2014] PIER 144 [2014] PIER 143 [2013] PIER 142 [2013] PIER 141 [2013] PIER 140 [2013] PIER 139 [2013] PIER 138 [2013] PIER 137 [2013] PIER 136 [2013] PIER 135 [2013] PIER 134 [2013] PIER 133 [2013] PIER 132 [2012] PIER 131 [2012] PIER 130 [2012] PIER 129 [2012] PIER 128 [2012] PIER 127 [2012] PIER 126 [2012] PIER 125 [2012] PIER 124 [2012] PIER 123 [2012] PIER 122 [2012] PIER 121 [2011] PIER 120 [2011] PIER 119 [2011] PIER 118 [2011] PIER 117 [2011] PIER 116 [2011] PIER 115 [2011] PIER 114 [2011] PIER 113 [2011] PIER 112 [2011] PIER 111 [2011] PIER 110 [2010] PIER 109 [2010] PIER 108 [2010] PIER 107 [2010] PIER 106 [2010] PIER 105 [2010] PIER 104 [2010] PIER 103 [2010] PIER 102 [2010] PIER 101 [2010] PIER 100 [2010] PIER 99 [2009] PIER 98 [2009] PIER 97 [2009] PIER 96 [2009] PIER 95 [2009] PIER 94 [2009] PIER 93 [2009] PIER 92 [2009] PIER 91 [2009] PIER 90 [2009] PIER 89 [2009] PIER 88 [2008] PIER 87 [2008] PIER 86 [2008] PIER 85 [2008] PIER 84 [2008] PIER 83 [2008] PIER 82 [2008] PIER 81 [2008] PIER 80 [2008] PIER 79 [2008] PIER 78 [2008] PIER 77 [2007] PIER 76 [2007] PIER 75 [2007] PIER 74 [2007] PIER 73 [2007] PIER 72 [2007] PIER 71 [2007] PIER 70 [2007] PIER 69 [2007] PIER 68 [2007] PIER 67 [2007] PIER 66 [2006] PIER 65 [2006] PIER 64 [2006] PIER 63 [2006] PIER 62 [2006] PIER 61 [2006] PIER 60 [2006] PIER 59 [2006] PIER 58 [2006] PIER 57 [2006] PIER 56 [2006] PIER 55 [2005] PIER 54 [2005] PIER 53 [2005] PIER 52 [2005] PIER 51 [2005] PIER 50 [2005] PIER 49 [2004] PIER 48 [2004] PIER 47 [2004] PIER 46 [2004] PIER 45 [2004] PIER 44 [2004] PIER 43 [2003] PIER 42 [2003] PIER 41 [2003] PIER 40 [2003] PIER 39 [2003] PIER 38 [2002] PIER 37 [2002] PIER 36 [2002] PIER 35 [2002] PIER 34 [2001] PIER 33 [2001] PIER 32 [2001] PIER 31 [2001] PIER 30 [2001] PIER 29 [2000] PIER 28 [2000] PIER 27 [2000] PIER 26 [2000] PIER 25 [2000] PIER 24 [1999] PIER 23 [1999] PIER 22 [1999] PIER 21 [1999] PIER 20 [1998] PIER 19 [1998] PIER 18 [1998] PIER 17 [1997] PIER 16 [1997] PIER 15 [1997] PIER 14 [1996] PIER 13 [1996] PIER 12 [1996] PIER 11 [1995] PIER 10 [1995] PIER 09 [1994] PIER 08 [1994] PIER 07 [1993] PIER 06 [1992] PIER 05 [1991] PIER 04 [1991] PIER 03 [1990] PIER 02 [1990] PIER 01 [1989]
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 Kang Chen , "Fuzzy-Control-Based Particle Filter for Maneuvering Target Tracking," Progress In Electromagnetics Research, Vol. 118, 1-15, 2011.
doi:10.2528/PIER11051907
http://www.jpier.org/PIER/pier.php?paper=11051907
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.