Process noise identification based particle filter: An efficient method to track highly manoeuvring targets

IET Signal Processing

Volumn 5, Issue 6, 2011, Pages 538-546

  Jing, L ^a   ChongZhao, H ^a   Vadakkepat, P ^b  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

COMMON PROBLEMS; MANOEUVRING TARGET; MANOEUVRING TARGET TRACKING; MULTIPLE MODELS; NONSTATIONARY PROCESS; PARTICLE FILTER; PROCESS NOISE; SAMPLE IMPOVERISHMENT; TRACKING PROCESS; TRANSITION PROBABILITY MATRIX; UNCERTAIN DYNAMICS;

NONLINEAR FILTERING; STATE ESTIMATION;

TARGET TRACKING;

EID: 80052795872     PISSN: 17519675     EISSN: 17519683     Source Type: Journal    
DOI: 10.1049/iet-spr.2010.0025     Document Type: Article

References (17)

1. Karlsson, R., and Gustafsson, F.: 'Range estimation using angle-only target tracking with particle filters', Proc. American Control Conf., 2001, 5, p. 3743-3748
2. Ikoma, N., Ichimura, N., Higuchi, T., and Maeda, H.: 'Maneuvering target tracking by using particle filter', IFSA World Congress and 20th NAFIPS Int. Conf., 2001, 4, p. 2223-2228
3. Karlsson, R., and Bergman, N.: 'Auxiliary particle filters for tracking a maneuvering target', Proc. 39th IEEE Conf. on Decision and Control, 2000, 4, p. 3891-3895
4. Ikoma, N., Higuchi, T., and Maeda, H.: 'Tracking of maneuvering target by using switching structure and heavy-tailed distribution with particle filter method', Proc. Int. Conf. on Control Applications, 2002, 2, p. 1282-1287
5. Malcolm, W., Doucet, A., and Zollo, S.: 'Sequential Monte Carlo tracking schemes for maneuvering targets with passive ranging', Proc. Fifth Int. Conf. on Information Fusion, 2002, 1, p. 482-488
6. Doucet, A., de Freitas, J.F.G., and Gordon, N.J.: 'Sequential Monte Carlo methods in practice', (Springer-Verlag, New York 2001)
7. Morelande, M., and Challa, S.: 'Manoeuvring target tracking in clutter using particle filters', IEEE Trans. Aerosp. Electron. Syst., 2005, 41, (1), p. 252-27010.1109/TAES.2005.1413760 0018-9251
8. Godsill, S.J., Vermaak, J., Ng, W., and Li, J.F.: 'Models and algorithms for tracking of maneuvering objects using variable rate particle filters', Proc. IEEE, 2007, 95, (5), p. 925-95210.1109/JPROC.2007.894708 0018-9219
9. Arulampalam, M., Maskell, S., Gordon, N., and Clapp, T.: 'A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking', IEEE Trans. Signal Process., 2002, 50, p. 174-18810.1109/78.978374 1053-587X
10. Musso, C., Oudjane, N., and LeGland, F.: 'Improving regularised particle filters in sequential Monte Carlo methods in practice', (Springer-Verlag, New York 2001)
11. Gilks, W.R., and Berzuini, C.: 'Following a moving target - Monte Carlo inference for dynamic Bayesian models', J. R. Stat. Soc., 2001, 63, p. 127-14610.1111/1467-9868.00280
12. Jazwinski, A.H.: 'Stochastic processes and filtering theory', (Academic Press, New York 1970)
13. Li, X.R., and Bar-Shalom, Y.: 'A recursive multiple model approach to noise identification', IEEE Trans. Aerosp. Electron. Syst., 1994, 30, (3), p. 671-68410.1109/7.303738 0018-9251
14. Li, X.R., and Bar-Shalom, Y.: 'A recursive hybrid system approach to noise identification', Proc. First IEEE Conf. on Control Applications, 1992, p. 847-852
15. Chen, B., and Tugnait, J.K.: 'Tracking of multiple maneuvering targets in clutter using IMM/JPDA filtering and fixed-lag smoothing', Automatica, 2001, 37, p. 239-24910.1016/S0005-1098(00)00158-8 0005-1098
16. Koch, W., and Keuk, G.: 'Multiple hypothesis track maintenance with possibly unresolved measurements', IEEE Trans. Aerosp. Electron. Syst., 1997, AES-33, p. 883-89210.1109/7.599263 0018-9251
17. Musso, C., Oudjane, N., and LeGland, F.: 'Improving regularized particle filters', Doucet, A., DeFreitas, N., Gordon, N., Sequential Monte Carlo methods in practice, (Springer, New York 2001), p. 247-271