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地球科学进展  2008, Vol. 23 Issue (8): 813-820    DOI: 10.11867/j.issn.1001-8166.2008.08.0813
综述与评述     
非线性滤波方法与陆面数据同化
韩旭军1,2,李 新1
1.中国科学院寒区旱区环境与工程研究所遥感与地理信息科学研究室,甘肃 兰州 730000;2.中国科学院深圳先进技术研究院,广东 深圳 518054
Review of the Nonlinear Filters in the Land Data Assimilation
Han Xujun1,2,Li Xin1
1.Laboratory of Remote Sensing and Geospatial Science, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China;2.Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518054,China
 全文: PDF(977 KB)  
摘要:

陆面数据同化研究近几年成为地球科学研究的新兴领域,其中以非线性滤波为代表的数据同化方法发展迅速并得到了广泛应用。在贝叶斯理论框架内,从递推贝叶斯估计理论的角度系统地分析了扩展卡尔曼滤波、无迹卡尔曼滤波、集合卡尔曼滤波、SIR粒子滤波等非线性滤波方法的异同;针对应用比较广泛的集合卡尔曼滤波和SIR粒子滤波应用中存在的问题,论述了几种提高滤波性能的实用方法,如协方差矩阵的Localization方法、协方差矩阵的Inflation方法、双集合卡尔曼滤波方法、扰动集合、扰动大气驱动和模型参数、平方根集合卡尔曼滤波以及粒子滤波算法的改进等。最后总结讨论了各种非线性滤波方法应用中的特点、难点以及各种算法在陆面数据同化中的应用前景和发展方向。

关键词: 陆面数据同化贝叶斯滤波卡尔曼滤波粒子滤波    
Abstract:

The land data assimilation research has become the emerging domain in the geoscience, the data assimilation algorithm obtained rapid development and widespread application taking the nonlinear filter as representative's. The extended Kalman filter, unscented Kalman filter, the ensemble Kalman filter and the SIR particle filter are discussed in the Bayesian theory framework from the viewpoint of the recursive Bayesian estimation. Towards the problems in the application of the ensemble Kalman filter and the SIR particle filter, some techniques that can improve the filter performances are also reviewed, such as the covariance localization, the covariance inflation, the double ensemble Kalman filter, the perturbations in the ensembles, the model forcing and parameters, the ensemble square root Kalman filter and the improved variants of the particle filters. The advantages and disadvantages of each filter as well as the applied perspective and the future research directions are discussed.

Key words: Land data assimilation    Bayesian filtering    Kalman filter    Particle filter
收稿日期: 2007-10-31 出版日期: 2008-08-10
:  TP79  
基金资助:

国家自然科学基金项目“陆面数据同化中的贝叶斯滤波方法研究”(编号:40771036);国家自然科学基金重点项目“中国西部地区陆面数据同化系统研究”(编号:90202014)资助.

通讯作者: 韩旭军     E-mail: xj.han@sub.siat.ac.cn
作者简介: 韩旭军(1980-),男,山东博兴人,助理研究员,主要从事陆面数据同化研究.E-mail:xj.han@sub.siat.ac.cn
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引用本文:

韩旭军,李新. 非线性滤波方法与陆面数据同化[J]. 地球科学进展, 2008, 23(8): 813-820.

Han Xujun,Li Xin. Review of the Nonlinear Filters in the Land Data Assimilation. Advances in Earth Science, 2008, 23(8): 813-820.

链接本文:

http://www.adearth.ac.cn/CN/10.11867/j.issn.1001-8166.2008.08.0813        http://www.adearth.ac.cn/CN/Y2008/V23/I8/813

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