| Citation: | YANG Haifeng, WANG Jinna, WANG Yuxiang. Multiple-model self-calibration Kalman filter method[J]. Journal of Aerospace Power, 2024, 39（3）：20220244 doi: 10.13224/j.cnki.jasp.20220244
|
Based on the self-calibration Kalman filter (SKF) and the multiple-model estimation (MME), considering the influence of unknown inputs (such as gusts, faults, unknown system errors, etc.) on the system state equation in Engineering, the multiple-model self-calibration Kalman filter (MSKF) was proposed. According to the Bayes' theorem, this filtering method used the SKF and the standard Kalman filter (KF) whose weights were assigned automatically to obtain the final filtering result through weight-average way. Compared with the SKF, the MSKF can not only effectively compensate the effects of non-zero unknown inputs, but also improve the estimation accuracy when unknown inputs were zero. A large number of simulation results showed that accuracy can be improved by more than 10%, using the proposed method. In summary, the MSKF has stronger adaptability and robustness.
| [1] |
KALMAN R E. A new approach to linear filtering and prediction problems[J]. Journal of Basic Engineering,1960,82(1): 35-45. doi: 10.1115/1.3662552
|
| [2] |
SUNAHARA Y. An approximate method of state estimation for nonlinear dynamical systems[J]. Journal of Basic Engineering,1970,92(2): 385-393. doi: 10.1115/1.3425006
|
| [3] |
FUJIMOTO O,OKITA Y,OZAKI S. Nonlinearity compensation Extended Kalman filter and its application to target motion[J]. Oki Technical Review,1997,63(159): 1-12.
|
| [4] |
JULIER S J, UHLMANN J K. A new extension of Kalman filter to nonlinear systems[C]//Proceedings of 11th International Symposium Aerospace/Defense Sensing, Simulation and Controls. Orlando, US: Society of Photo-Optical Instrumentation Engineers (SPIE), 1997: 182-193.
|
| [5] |
JULIER S,UHLMANN J,DURRANT-WHYTE H F. A new method for the nonlinear transformation of means and covariances in filters and estimators[J]. IEEE Transactions on Automatic Control,2000,45(3): 477-482. doi: 10.1109/9.847726
|
| [6] |
JULIER S J,UHLMANN J K. Unscented filtering and nonlinear estimation[J]. Proceedings of the IEEE,2004,92(3): 401-422. doi: 10.1109/JPROC.2003.823141
|
| [7] |
DAN S. Optimal state estimation: Kalman H∞ and nonlinear approaches[M]. Hoboken, US: Wiley & Sons, 2006.
|
| [8] |
PITT M K,SHEPHARD N. Filtering via simulation: auxiliary particle filters[J]. Journal of the American Statistical Association,1999,94(446): 590-599. doi: 10.1080/01621459.1999.10474153
|
| [9] |
BLANKE M, SCHRÖDER J. Diagnosis and fault-tolerant control[M]. 2nd ed. Berlin, Germany: Springer, 2006.
|
| [10] |
CHEN J, PATTON R. Robust model-based fault diagnosis for dynamic systems[M]. Boston, US: Kluwer Academic Publishers, 1999
|
| [11] |
GILLIJNS S,DE MOOR B. Unbiased minimum-variance input and state estimation for linear discrete-time systems[J]. Automatica,2007,43(1): 111-116. doi: 10.1016/j.automatica.2006.08.002
|
| [12] |
傅惠民,吴云章,娄泰山,等. 自校准Kalman滤波方法[J]. 航空动力学报,2014,29(6): 1363-1368. doi: 10.13224/j.cnki.jasp.2014.06.015
FU Huimin,WU Yunzhang,LOU Taishan,et al. Self-calibration Kalman filter method[J]. Journal of Aerospace Power,2014,29(6): 1363-1368. (in Chinese) doi: 10.13224/j.cnki.jasp.2014.06.015
|
| [13] |
傅惠民,娄泰山,肖强,等. 自校准扩展Kalman滤波方法[J]. 航空动力学报,2014,29(11): 2710-2715. doi: 10.13224/j.cnki.jasp.2014.11.023
FU Huimin,LOU Taishan,XIAO Qiang,et al. Self-calibration extended Kalman filter method[J]. Journal of Aerospace Power,2014,29(11): 2710-2715. (in Chinese) doi: 10.13224/j.cnki.jasp.2014.11.023
|
| [14] |
MAGILL D. Optimal adaptive estimation of sampled stochastic processes[J]. IEEE Transactions on Automatic Control,1965,10(4): 434-439. doi: 10.1109/TAC.1965.1098191
|
| [15] |
RONG LI X. Hybrid estimation techniques[J]. Control and Dynamic Systems,1996,76: 213-287.
|
| [16] |
MAZOR E,AVERBUCH A,BAR-SHALOM Y,et al. Interacting multiple model methods in target tracking: a survey[J]. IEEE Transactions on Aerospace and Electronic Systems,1998,34(1): 103-123. doi: 10.1109/7.640267
|
| [17] |
LI X R,BAR-SHALOM Y. Performance prediction of the interacting multiple model algorithm[J]. IEEE Transactions on Aerospace and Electronic Systems,1993,29(3): 755-771. doi: 10.1109/7.220926
|
| [18] |
DAEIPOUR E,BAR-SHALOM Y. IMM tracking of maneuvering targets in the presence of glint[J]. IEEE Transactions on Aerospace and Electronic Systems,1998,34(3): 996-1003. doi: 10.1109/7.705913
|
DownLoad:
