Joint state and parameter estimation in particle filtering and stochastic optimization

Journal of Control Theory and Applications

Volumn 6, Issue 2, 2008, Pages 215-220

  Yang, Xiaojun ^a,b   Xing, Keyi ^a   Shi, Kunlin ^b   Pan, Quan ^c  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b Xi'an Institute of Electromechanical Information Technology   (China)

^c NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

Author keywords

Adaptive estimation; Parameter estimation; Particle filtering; Sequential Monte Carlo; Simultaneous perturbation stochastic approximation

Indexed keywords

ACOUSTIC SIGNAL PROCESSING; ADAPTIVE ALGORITHMS; ADAPTIVE SYSTEMS; APPROXIMATION ALGORITHMS; AUTOMATION; BOOLEAN FUNCTIONS; CONTROL THEORY; DYNAMIC PROGRAMMING; ESTIMATION; LINEAR CONTROL SYSTEMS; MAXIMUM LIKELIHOOD ESTIMATION; MILITARY DATA PROCESSING; MODEL STRUCTURES; NONLINEAR FILTERING; NONLINEAR SYSTEMS; OPTIMIZATION; SIGNAL FILTERING AND PREDICTION; STOCHASTIC PROGRAMMING;

ADAPTIVE ESTIMATIONS; DYNAMIC STATES; EDITORIAL BOARD; MAXIMUM LIKELIHOOD ESTIMATION (MLSE); NON-LINEAR DYNAMIC SYSTEMS; PARTICLE FILTER (PF); SIMULATION RESULTS; SIMULTANEOUS PERTURBATION STOCHASTIC APPROXIMATION (SPSA); SOUTH CHINA UNIVERSITY OF TECHNOLOGY; STATIC PARAMETERS; STOCHASTIC OPTIMIZATIONS;

PARAMETER ESTIMATION;

EID: 47049128971     PISSN: 16726340     EISSN: 10008152     Source Type: Journal    
DOI: 10.1007/s11768-008-6078-2     Document Type: Article

References (16)

1. A. Doucet, J. F. G. de FReitas, N. J. Gordon. Sequential Monte Carlo Methods in Practice[M]. New York: Springer-Verlag, 2001.
2. X. Yang, Q. Pan, R. Wang, et al. Development and prospect of particle filtering[J]. Control Theory & Applications, 2006, 23(2): 261-267 (in Chinese).
3. D. Gamerman. Markov chain Monte Carlo for dynamic generalized models[J]. Biometrika, 1998, 85(1): 215-227.
4. C. Berzuini, N. G. Best, W. R. Gilks, et al. Dynamic conditional independence models and Markov chain Monte Carlo methods[J]. Journal of the American Statistical Association, 1997, 92: 1403-1411.
5. L. Jane, W. Mike. Combined parameter and state estimation in simulation-based filtering[M]//Sequential Monte Carlo Methods in Practice. A. Doucet, J.F.G. de Freitas, N. J. Gordon, Eds. New York: Springer-Verlag, 2001.
6. D. Lee, N. K. K. Chia. A particle algorithm for sequential Bayesian parameter estimation and model selection[J]. IEEE Transactions on Signal Processing, 2002, 50(2): 326-336.
7. G. Storvic. Particle filters in state space models with the presence of unknown static parameters[J]. IEEE Transactions on Signal Processing, 2002, 50(2): 281-289.
8. P. M. Djuric, J. Miguez. Sequential particle filtering in the presence of additive Gaussian noise with unknown parameters[C]// Proceedings of International Conference on Acoustic Speech and Signal Processing(ICASSP). Orlando, Florida: IEEE Press, 2002: 1621-1624.
9. C. Andrieu, A. Doucet, S. S. Singh, et al. Particle methds for change detection, system identification, and control[J]. Proceedings of the IEEE, 2004, 92(3): 423-438.
10. N. J. Gordon, D. J. Salmond, A. F. M. Smith. Novel approach to nonlinear/non-Gaussian Bayesian state estimation[J]. IEE Proceedings-F, 1993, 140(2): 107-113.
11. A. Kong, J. Liu, W. Wong. Sequential imputations and Bayesian missing data problems[J]. Journal of the American Statistical Association, 1994, 89(5): 278-288.
12. D. Crisan, A. Doucet. A survey of convergence results on particle filtering methods for practitioners[J]. IEEE Transaction on Signal Processing, 2002, 50(3): 736-746.
13. J. C. Spall. A stochastic approximation technique for generating maximum likelihood parameter estimates[C]//Proceedings of the American Control Conference. Minneapolis, Minnesota: IEEE Press, 1987: 1161-1167.
14. B. L. Chan, A. Doucet, V. B. Tadic. Optimization of particle filters using simultaneous perturbation stochastic approximation[C]// Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing. Hong Kong: IEEE Press, 2003, 681-684.
15. J. C. Spall. Implementation of the simultaneous perturbation algorithm for stochastic optimization[J]. IEEE Transactions on Aerospace and Electronic Systems, 1998, 34(3): 817-823.
16. C. Andrieu, A. doucet, V. B. Tadic. Online sampling for parameter estimation in general state space models[C]//Proceedings of IFAC Symposium on System Identification (SYSID 2003). Rotterdam, Netherlands: IFAC, 2003: 221-225.