引用本文: | 崔培玲,王桂增,潘泉.一类动态多尺度系统融合估计算法的分析[J].控制理论与应用,2007,24(1):84~89.[点击复制] |
CUI Pei-ling ,WANG Gui-zeng ,PAN Quan .Analyzing of the fusion estimationalgorithm of a class of dynamic multiscale system[J].Control Theory and Technology,2007,24(1):84~89.[点击复制] |
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一类动态多尺度系统融合估计算法的分析 |
Analyzing of the fusion estimationalgorithm of a class of dynamic multiscale system |
摘要点击 1433 全文点击 1024 投稿时间:2005-09-23 修订日期:2006-02-23 |
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DOI编号 10.7641/j.issn.1000-8152.2007.1.015 |
2007,24(1):84-89 |
中文关键词 动态多尺度系统 状态空间投影 卡尔曼滤波 |
英文关键词 dynamic multiscale system state
space projection Kalman filter |
基金项目 国家自然科学基金重点资助项目 60234010 ;
中国博士后基金资助项目 2005037353;国家“863”计划资助项目 2006AA042168 |
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中文摘要 |
为了进一步认识基于状态空间投影的一类动态多尺度系统的融合估计算法本质,
本文对该算法进行了分析. 首先,
将该融合估计算法和在最细尺度上直接进行卡尔曼滤波的算法性能进行了比较,
并用仿真进行了验证. 结果表明, 在最细尺度上,
融合估计效果比直接进行卡尔曼滤波的效果好. 其次,
从计算过程和计算量方面, 与一般的时间配准方法进行了对比分析.
结果表明, 该融合估计算法用比较严谨的数学模型代替了时间配准,
可以在每个尺度上获得基于全部观测信息的最优估计,
但计算量比时间配准方法大. 本文的研究为基于状态空间投影的一类动态多尺度系统的融合估计算法的实际应用奠定了基础. |
英文摘要 |
The fusion
estimation algorithm of a class of dynamic multiscale system based
on state space projection is explained for clearly understanding of
its essence in this paper. Firstly, the fusion estimation algorithm
is compared with that directly performing Kalman filter at the
finest scale. Simulation results show that performance of the fusion
estimation algorithm outperforms that of directly performing Kalman
filter at the finest scale. Secondly, the fusion estimation
algorithm is compared with general time registration method in terms
of algorithm process and computational cost. It is shown that, time
registration is replaced with rigorous mathematical model in the
fusion estimation algorithm, and optimal estimation based on
measurement information at all scales can be obtained, and at the
same time, the computational cost is larger than that of time
registration method. It thus lays a foundation for practical
application of the fusion estimation algorithm
for a class of dynamic multiscale system. |
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