地震动瞬时谱估计的UnscentedKalman滤波方法

李英民; 董银峰; 赖明

地震动瞬时谱估计的UnscentedKalman滤波方法

1.
重庆大学土木工程学院,重庆 400045;2.重庆大学山地城镇建设与新技术教育部重点实验室,重庆 400045,3.建设部科技司,北京100835

基金项目: 国家自然科学基金资助项目(50008017);教育部新世纪优秀人才支持计划资助项目(NCET-06-0765)

详细信息

作者简介:
李英民(1968- ),男,山东人,教授,博士生导师(联系人.Tel:+86-23-65121991;E-mail:liyingmin@cqu.edu.cn).

中图分类号: O211.64；P315.3
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出版历程
- 收稿日期: 2006-09-20
- 修回日期: 2007-09-04
- 刊出日期: 2007-11-15

Instantaneous Spectrum Estimation of Earthquake Ground Motions Based on Unscented Kalman Filter Method

1.
College of Civil Engineering, Chongqing University, Chongqing 400045, P. R. China;

摘要

摘要: 用时变ARMA模型描述地震动时程，提出了采用Unscented Kalman滤波技术实现地震动瞬时谱估计的思路．算例分析表明，Unscented Kalman滤波方法较Kalman滤波方法适用范围广，具有较高的时间和频率分辨率，能够更好地跟踪地震动的局部特性，适合处理非线性模型或有突变特性的模型的辨识问题．不同阶数ARMA模型的估计结果还表明，以往被忽略的ARMA模型的理论频率分辨力对地震动瞬时谱估计精度有重要影响，应作为一个参考指标在ARMA模型的判阶中加以考虑．
- Unscented Kalman滤波 /
- 地震动 /
- 瞬时谱 /
- 时变ARMA模型
Abstract: Representing earthquake ground motion as time varying ARMA model, the instantaneous spectrum can be determined only by the time varying coefficients of the corresponding ARMA model. Then, unscented Kalman filter was introduced to estimate the time varying coefficients. The comparison between the estimation results of unscented Kalman filter and Kalman filter method shows that unscented Kalman filter can more precisely represent the distribution of the spectral peaks in time-frequency plane than Kalman filter and its time and frequency resolution is finer which ensures its better ability to track the local properties of earthquake ground motions and to identify the systems with nonlinearity or abruptness. Moreover, the estimation results of ARMA models with different orders indicate that the theoretical frequency resolving power of ARMA model which was usually ignored in former relevant studies has great effect on the estimation precision of instantaneous spectrum and it should be taken as one of the key factors in order selection of ARMA model.
- unscented Kalman filter /
- earthquake ground motion /
- instantaneous spectrum /
- time varying ARMA model

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参考文献(18)

[1]	李英民.工程地震动的模型化研究[D].博士学位论文.重庆:重庆建筑大学,1999.
[2]	Conte J P, Pister K S, Mahin S A. Influence of the earthquake ground motion process and structural properties on response characteristics of simple structures[R]. Report No. UCB/EERC-90/09, Earthquake Engineering Research Center, University of California, Berkeley, CA, 1990.
[3]	Cohen L. Time-frequency distributions—a review[J].Proceedings of the IEEE,1989,77(7):941-981. doi: 10.1109/5.30749
[4]	Huang N E, Shen Z, Long S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis[J].Proc of the Royal Society of London, Ser A,1998,454(1971): 903-995. doi: 10.1098/rspa.1998.0193
[5]	谢衷洁. 时间序列分析[M].北京: 北京大学出版社, 1990.
[6]	Kalman R E. A new approach to linear filtering and prediction problems[J]. Journal of Basic Engineering, Transactions of the ASME, Ser D,1960,82(1):35-45. doi: 10.1115/1.3662552
[7]	Sorenson H W. Least-square estimation: from Gauss to Kalman[J].IEEE Spectrum,1970,7(7):63-68.
[8]	Ljung L.System Identification—Theory for the User[M].2nd Ed.New Jersey:PTR Prentice Hall, 1999.
[9]	Haykin S.Kalman Filtering and Neural Networks[M].New York: John Wiley and Sons Inc,2001.
[10]	Sanjeev A, Simon M, Neil G,et al.A tutorial on particle filters for on-line no-linear/non-Gaussian Bayesian tracking[J].IEEE Trans on Signal Processing,2002,50(2):174-188. doi: 10.1109/78.978374
[11]	Julier S, Uhlmann J K. A new extension of the Kalman filter to nonlinear system[A].In: Proc of AeroSence:The 11th International Symposium on Aerospace/Defence Sensing, Simulation and Controls[C].Orlando,Florida:SPIE，1997,182-193.
[12]	Parzen E. Some recent advances in time series modeling[J].IEEE Trans on Automatic Control,1974,19(6):723-730. doi: 10.1109/TAC.1974.1100733
[13]	Jong P, Penzer J. The ARMA model in state space form[J].Journal of Statistics & Probability Letters,2004,70(1):119-125.
[14]	Akaike H. A new look at the statistical model identification[J].IEEE Trans on Automatic Control,1974,19(6):716-723. doi: 10.1109/TAC.1974.1100705
[15]	Broersen P M T. Finite sample criteria for autoregressive order selection[J].IEEE Trans on Signal Processing,2000,48(12):3550-3558. doi: 10.1109/78.887047
[16]	康宜华, 何岭松, 杨叔子. ARMA谱的理论频率分辨力[J]. 华中理工大学学报,1995,23(6):101-104.
[17]	Gustaffasson F, Gunnarsson S, Ljung L. Shaping frequency-dependent time resolution when estimation spectral properties with parametric methods[J].IEEE Trans on Signal Processing,1997,45(4):160-163.
[18]	Dong Y F, Zhen N N, Lai M,et al.Estimation of instantaneous spectrum of earthquake ground motions using neural networks[A].In:Andcrson E DL Ed.Proc the 13th World Conference on Earthquake Engineering[C].Vancouver,Canada:Mira Digital Publishing,2004, PN1446.

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地震动瞬时谱估计的UnscentedKalman滤波方法

作者简介:
李英民(1968- ),男,山东人,教授,博士生导师(联系人.Tel:+86-23-65121991;E-mail:liyingmin@cqu.edu.cn).

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Instantaneous Spectrum Estimation of Earthquake Ground Motions Based on Unscented Kalman Filter Method

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地震动瞬时谱估计的UnscentedKalman滤波方法

作者简介: 李英民(1968- ),男,山东人,教授,博士生导师(联系人.Tel:+86-23-65121991;E-mail:liyingmin@cqu.edu.cn).

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出版历程

Instantaneous Spectrum Estimation of Earthquake Ground Motions Based on Unscented Kalman Filter Method

计量

出版历程

目录

作者简介:
李英民(1968- ),男,山东人,教授,博士生导师(联系人.Tel:+86-23-65121991;E-mail:liyingmin@cqu.edu.cn).