volume | PIER Journals

Abstract

For maneuvering target tracking, we propose a novel grey prediction based particle filter (GP-PF), which incorporates the grey prediction algorithm into the standard particle filter (SPF). The basic idea of the GP-PF is that new particles are sampled by both the state transition prior and the grey prediction algorithm. Since the grey prediction algorithm is a kind of model-free method and is able to predict the system state based on historical measurements other than establishing a priori dynamic model, the GP-PF can significantly alleviate the sample degeneracy problem which is common in SPF, especially when it is used for maneuvering target tracking. Simulations are conducted in the context of two typical maneuvering motion scenarios and the results indicate that the overall performance of the proposed GP-PF is better than the SPF and the multiple model particle filter (MMPF) when the tracking accuracy, computational complexity and tracking lost probability are considered. The performance improvements can be attributed to that the GP-PF has both model-based and model-free features.

1. Blackman, S. S., Multiple Target Tracking with Radar Applications, Artech House, 1986.

2. Bar-Shalom, Y. and T. E. Fortmann, Tracking and Data Association, Academic Press, 1988.

3. Singh, A. K., P. Kumar, T. Chakravarty, G. Singh, and S. Bhooshan, "A novel digital beamformer with low angle resolution for vehicle tracking radar," Progress In Electromagnetics Research, Vol. 66, 229-237, 2006.
doi:10.2528/PIER06112102 Google Scholar

4. Shi, Z. G., S. Qiao, K. S. Chen, W. Z. Cui, W. Ma, T. Jiang, and L. X. Ran, "Ambiguity functions of direct chaotic radar employing microwave chaotic Colpitts oscillator," Progress In Electromagnetics Research, Vol. 77, 1-14, 2007.
doi:10.2528/PIER07072001 Google Scholar

5. Turkmen, I. and K. Guney, "Tabu search tracker with adaptive neuro-fuzzy inference system for multiple target tracking," Progress In Electromagnetics Research, Vol. 65, 169-185, 2006.
doi:10.2528/PIER06090601 Google Scholar

6. 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 Google Scholar

7. 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 Google Scholar

8. Tanizaki, H., Nonlinear Filters: Estimation and Application, Springer, 1996.

9. Bar-Shalom, Y. and X. R. Li, Multitarget Multisensor Tracking: Principles and Techniques, YBS Publishing, 1995.

10. Chen, J. M., X. Cao, Y. Xiao, and Y. Sun, "Simulated annealing for optimisation with wireless sensor and actuator networks," Electronics Letters, Vol. 44, No. 20, 1208-1209, 2008.
doi:10.1049/el:20081574 Google Scholar

11. Gordon, N. J., D. J. Salmond, and A. F. M. Smith, "Novel approach to nonlinear/non-Gaussian Bayesian state estimation," IEE Proceeding---F, Vol. 140, No. 2, 107-113, 1993. Google Scholar

12. Doucet, A., N. D. Freitas, and N. Gordon, Sequential Monte Carlo Methods in Practice, Springer, 2001.

13. Du, S. C., Z. G. Shi, W. Zang, and K. S. Chen, "Using interacting multiple model particle filter to track airborne targets hidden in blind Doppler," Journal of Zhejiang University-Science A, Vol. 8, No. 8, 1277-1282, 2007.
doi:10.1631/jzus.2007.A1277 Google Scholar

14. Shi, Z. G., S. H. Hong, and K. S. Chen, "Experimental study on tracking the state of analog Chua's circuit with particle filter for chaos synchronization," Physics Letters A, Vol. 372, 5575-5580, 2008.
doi:10.1016/j.physleta.2008.06.082 Google Scholar

15. Hong, S. H., Z. G. Shi, and K. S. Chen, "Novel roughening algorithm and hardware architecture for bearings-only tracking using particle filter," Journal of Electromagnetic Waves and Applications, Vol. 22, 411-422, 2008.
doi:10.1163/156939308784160857 Google Scholar

16. 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 Google Scholar

17. 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 Google Scholar

18. Wang, X., X. Guan, X. Ma, D. Wang, and Y. Su, "Calculating the poles of complex radar targets," Journal of Electromagnetic Waves and Applications, Vol. 20, No. 14, 2065-2076, 2006.
doi:10.1163/156939306779322657 Google Scholar

19. Stratakos, Y., G. Geroulis, and N. Uzunoglu, "Analysis of glint phenomenon in a monopulse radar in the presence of skin echo and non-ideal interferometer echo signals," Journal of Electromagnetic Waves and Applications, Vol. 19, No. 5, 697-711, 2005.
doi:10.1163/1569393053305008 Google Scholar

20. Abdelaziz, A. A., "Improving the performance of an antenna array by using radar absorbing cover," Progress In Electromagnetics Research Letters, Vol. 1, 129-138, 2008.
doi:10.2528/PIERL07112503 Google Scholar

21. Chan, Y. K. and S. Y. Lim, "Synthetic aperture radar (SAR) signal generation," Progress In Electromagnetics Research B, Vol. 1, 269-290, 2008.
doi:10.2528/PIERB07102301 Google Scholar

22. Li, X. R. and V. P. Jilkov, "Survey of maneuvering target tracking --- Part I: Dynamic models," IEEE Aerospace and Electronic Systems Magazine, Vol. 39, No. 4, 1333-1364, 2003. Google Scholar

23. Blom, H. A. P. and Y. Bar-Shalom, "The interacting multiple model algorithm for systems with Markovian switching coefficients," IEEE Transactions on Automatic Control, Vol. 33, No. 8, 780-783, 1988.
doi:10.1109/9.1299 Google Scholar

24. McGinnity, S. and G. W. Irwin, "Multiple model bootstrap filter for maneuvering target tracking," IEEE Aerospace and Electronic Systems Magazine, Vol. 36, No. 3, 1006-1012, 2000. Google Scholar

25. Boers, Y. and J. N. Driessen, "Interacting multiple model particle filter," IEE Proceedings on Radar, Sonar and Navigation, Vol. 150, No. 5, 344-349, October October 2003.

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

27. Li, X. R. and V. P. Jilkov, "A survey of maneuvering target tracking---Part V: Multiple-model methods," IEEE Aerospace and Electronic Systems Magazine, Vol. 41, No. 4, 1255-1321, 2003. Google Scholar

28. Arulampalam, S., N. Gordon, M. Orton, and B. Ristic, "A variable structure multiple model particle filter for GMTI tracking," Proceedings of 5th International Conference on Information Fusion, 927-934, Annapolis, USA, July 2002.

29. Jilkov, V. P., D. S. Angelova, and T. A. Semerdijev, "Design and comparison of mode-set adaptive IMM for maneuvering target tracking," IEEE Trans. on Aerosp. Electron. Syst., Vol. 35, No. 1, 343-350, 1999.
doi:10.1109/7.745704 Google Scholar

30. Luo, R. C., T. M. Chen, and K. L. Su, "Target tracking using hierarchical grey-fuzzy motion decision-making method," IEEE Transactions on Systems, Man, and Cybernetics---Part A, Vol. 31, No. 3, 179-186, 2001.
doi:10.1109/3468.925657 Google Scholar

31. Luo, R. C. and T. M. Chen, "Target tracking by grey prediction theory and look-ahead fuzzy logic control," IEEE International Conference on Robotics and Automation, 1176-1181, Detroit, America, May 1999.

32. Deng, J. L., "Control problems of grey system," Systems and Control Letters, Vol. 5, 288-294, 1982. Google Scholar

33. Wong, C. C., B. C. Lin, and C. T. Cheng, "Fuzzy tracking method with a switching grey prediction for mobile robot," IEEE International Conference on Fuzzy Systems, 103-106, Melbourne, Australia, December 2001.

34. Arulampalam, M. S., S. Maskell, N. Gordon, and T. Clapp, "A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking," IEEE Transaction on Signal Processing, Vol. 50, No. 2, 174-188, 2002.
doi:10.1109/78.978374 Google Scholar

35. 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 Google Scholar

Mr. Jun-Feng Chen

Professor Zhi-Guo Shi

Dr. Shao-Hua Hong

Dr. Kang Chen