Self-tuning weighted measurement fusion Kalman filter and its convergence

Journal of Control Theory and Applications

Volumn 8, Issue 4, 2010, Pages 435-440

  Ran, Chenjian ^a   Deng, Zili ^a  

^a HEILONGJIANG UNIVERSITY   (China)

Author keywords

Asymptotic global optimality; Convergence; Fused noise variance estimator; Fused parameter estimator; Multisensor weighted measurement fusion; Self tuning fusion Kalman filter

Indexed keywords

ASYMPTOTIC GLOBAL OPTIMALITY; CONVERGENCE; MULTI SENSOR; NOISE VARIANCE; PARAMETER ESTIMATORS; SELFTUNING;

ALGORITHMS; ASYMPTOTIC ANALYSIS; KALMAN FILTERS; MEASUREMENTS; OPTIMIZATION; SPURIOUS SIGNAL NOISE; SYSTEMS ANALYSIS; TARGET TRACKING;

PARAMETER ESTIMATION;

EID: 78650135995     PISSN: 16726340     EISSN: 10008152     Source Type: Journal    
DOI: 10.1007/s11768-010-8243-7     Document Type: Article

References (18)

1. Q. Gan, C. H. Harris. Comparison of two measurement fusion methods for Kalman-filter-based multisensor data fusion[J]. IEEE Transactions on Aerospace and Electronic systems, 2001, 37(1): 273-279.
2. Y. Gao, C. Ran, Z. Deng. Weighted measurement fusion Kalman filter with correlated measurement noise and its global optimality[C]//Proceedings of the International Colloquiumen Information Fusion. Xi'an, 2007: 228-234.
3. Z. Deng, G. Hao, X. Wu. Global optimality and completely functional equivalence of two weighted measurement fusion algorithms[J]. Science Technology and Engineering, 2003, 5(13): 860-865.
4. B. Wittenmark. A self-tuning predictor[J]. IEEE Transactions on Automatic Control, 1974, 19(5): 848-851.
5. P. Hagander, B. Wittenmark. A self-tuning filter for fixed-lag smoothing[J]. IEEE Transactions on Information Theory, 1977, 23(3): 377-384.
6. T. Moir, M. J. Grimble. Optimal self-tuning filtering, prediction, and smoothing for discrete multivariable processes[J]. IEEE Transactions on Automatic control, 1984, 29(2): 128-135.
7. P. T. K. Fung, M. J. Grimble. Dynamic ship positioning using a selftuning Kalman filter[J]. IEEE Transactions on Automatic Control, 1983, 28(3): 339-356.
8. Z. Deng, C. Li. Self-tuning information fusion Kalman predictor weighted by diagonal matrices and its convergence analysis[J]. Acta Automatic Sinica, 2007, 33(2): 156-163.
9. Z. Deng, Y. Gao, C. Li, et al. Self-tuning decoupled information fusion Wiener state component filters and their convergence[J]. Automatica, 2008, 44(3): 685-695.
10. X. Sun, P. Zhang, Z. Deng. Self-tuning decoupled fusion Kalman filter based on Riccati equation[J]. Frontiers of Electronic and Electronic Engineering in Chinese, 2008, 3(4): 459-464.
11. Y. Gao, W. Jia, X. Sun, et al. Self-tuning multisensor weighted measurement fusion Kalman filter[J]. IEEE Transactions on Aerospace and Electrnoic Systems, 2009, 45(1): 179-191.
12. L. Ljung. System Identification: Theory for the User[M]. Englewood Cliffs: Prentice-Hall, 1999.
13. C. Ran, G. Tao, J. Liu, et al. Self-tuning decoupled fusion kalman predictor and its convergence analysis[J]. IEEE Sensors Journal, 2009, 9(12): 2024-2032.
14. Y. Gao, W. Wang, Z. Deng. Information fusion estimation of noise statistics for multisensor systems[C]//Chinese Control and Decision Conference. New York: IEEE, 2009: 1116-1120.
15. L. Gu, X. Sun, Z. Deng. The convergence analysis of the self-tuning Riccati equation[C]//Chinese Control and Decision Conference. New York: IEEE, 2009: 1154-1159.
16. T. Kailath, A. H. Sayed, B. Hassibi. Linear Estimation[M]. Upper Saddle River: Prentice-Hall, 2000.
17. Y. Gao, H. Xu, Z. Deng. Multi-stage information fusion identification method for multisensor ARMA signals with white measurement noises[C]//Proceedings of the 8th IEEE International Conference on Control and Automation. Xiamen, 2010: 1115-1119.
18. E. W. Kamen, J. Su. Introduction to Optimal Estimation[M]. London: Springer-Verlag, 1999.