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遥感技术与应用  2014, Vol. 29 Issue (5): 701-710    DOI: 10.11873/j.issn.1004-0323.2014.5.0701
综述     
粒子滤波算法在数据同化中的应用研究进展
毕海芸1,2,马建文1
(1.中国科学院遥感与数字地球研究所,北京 100094;
2.中国科学院大学,北京 100049)
Advances in the Study of Particle Filter in Data Assimilation
Bi Haiyun1,2,Ma Jianwen1
(1.Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China;
2.University of the Chinese Academy of Sciences,Beijing 100049,China)
 全文: PDF(1275 KB)  
摘要:

数据同化能将观测数据和模型模拟有机结合,优势互补,成为全球环境变化研究的重要方法之一。在数据同化算法的发展过程中,粒子滤波算法不受模型线性和误差高斯分布假设的约束,成为当前数据同化算法研究的重点。通过对粒子滤波算法在数据同化中应用研究进展的相关文献进行收集、整理和归纳,总结了粒子滤波算法的优势及在数据同化中的应用,并分析了粒子滤波算法应用于数据同化时所存在的主要问题和相应的解决方法,最后展望了未来的研究重点及发展趋势,为深入开展粒子滤波算法研究、使之更好地应用于数据同化领域提供理论依据。

关键词: 全球环境变化数据同化粒子滤波    
Abstract:

Since data assimilation can combine observational data and model simulation data to integrate their benefits,it has become an important global environment change research method.During the development process of data assimilation algorithms,the particle filter is free from the constraints of linear models and Gaussian error distributions,thus becoming the focus in the study of data assimilation algorithms.In this study,literature on the application and study of particle filter in the field of data assimilation is collected,arranged and concluded.Then the advantages of particle filter and its application in data assimilation are summarized.The main problems and corresponding solutions when applying particle filter in data assimilation are also analyzed,and the future research priorities and trends are discussed at the end of this paper.All of these can provide a theoretical basis for the further study of particle filter,so as to make a better use of it in data assimilation.

Key words: Global environment change    Data assimilation    Particle filter
收稿日期: 2013-07-25 出版日期: 2014-11-10
:  TP 79  
基金资助:

中国科学院遥感与数字地球研究所课题“高分辨率光学图像目标自动识别”(Y2YY02101B)资助。

作者简介: 毕海芸(1988-),女,湖北宜昌人,博士研究生,主要从事陆面数据同化研究。Email:bihaiyun1988@126.com。
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引用本文:

毕海芸,马建文. 粒子滤波算法在数据同化中的应用研究进展[J]. 遥感技术与应用, 2014, 29(5): 701-710.

Bi Haiyun,Ma Jianwen. Advances in the Study of Particle Filter in Data Assimilation. Remote Sensing Technology and Application, 2014, 29(5): 701-710.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2014.5.0701        http://www.rsta.ac.cn/CN/Y2014/V29/I5/701

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