Wiener滤波,Kalman滤波和信息融合滤波理论研究进展  

Advances on Wiener filtering,Kalman filtering and information fusion filtering theories

作　　者：邓自立[1] 

机构地区：[1]黑龙江大学电子工程学院自动化系,哈尔滨150080

出　　处：《黑龙江大学工程学报》2011年第3期37-44,共8页Journal of Engineering of Heilongjiang University

基　　金：国家自然科学基金资助项目(60874063;60374026;69774019;69172007)

摘　　要：综述最优和自校正滤波的一种新的方法论——现代时间序列分析方法,其中给出了同Wiener滤波方法和Kalman滤波方法的比较,并且综述了近20年来由作者分别基于Kalman滤波方法和现代时间序列分析方法关于Wiener滤波、Kalman滤波和信息融合滤波理论的研究进展,其中包括一系列新方法、新理论和新的研究方向,并提出了存在的几个问题和今后研究方向,具有重要理论、工程应用和科学方法论意义。A new methodology for optimal and self-tuning filtering--modern time series analysis method is reviewed, where the comparisons with the Wiener filtering method and Kalman filtering method are given, and the advances on Wiener filtering, Kalman filtering, and information fusion filtering theories are reviewed, which are presented by the author based on the Kalman filtering method and modern time series analysis method, respectively, in the last twenty years, and which include several new methods, theories, and research directions, and the exsisting some problems and further research directions are also presented. They have important theoretical, engineering applications, and science methodology meanings.

关 键 词：KALMAN滤波 WIENER滤波 信息融合滤波 现代时间序列分析方法 科学方法论 

分 类 号：O211.64[理学—概率论与数理统计]