| 引用本文: | 吴黎明,马静,孙书利.具有不同观测丢失率多传感器随机不确定系统的加权观测融合估计[J].控制理论与应用,2014,31(2):244~249.[点击复制] |
| WU Li-ming,MA Jing,SUN Shu-li.Weighted measurement fusion estimation for stochastic uncertain systems with multiple sensors of different missing measurement rates[J].Control Theory and Technology,2014,31(2):244~249.[点击复制] |
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| 具有不同观测丢失率多传感器随机不确定系统的加权观测融合估计 |
| Weighted measurement fusion estimation for stochastic uncertain systems with multiple sensors of different missing measurement rates |
| 摘要点击 2683 全文点击 2017 投稿时间：2013-02-24 修订日期：2013-09-04 |
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| DOI编号 10.7641/CTA.2014.30136 |
| 2014,31(2):244-249 |
| 中文关键词 多传感器 丢失观测 乘性噪声 加权观测融合 满秩分解 |
| 英文关键词 multisensor missing measurement multiplicative noise weighted measurement fusion full-rank decomposition |
| 基金项目 国家自然科学基金资助项目(NSFC-61174139); 黑龙江省高校长江学者后备支持计划资助项目(2013CJHB005); 黑龙江省高校科技创新团队资助项目(2012TD007); 黑龙江大学高层次人才资助项目(Hdtd2010-03); 省重点实验室基金资助项目. |
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| 中文摘要 |
| 本文研究了具有丢失观测的多传感器线性离散随机不确定系统的最优线性估计问题, 其中不同的传感器
具有不同的丢失率. 首先将乘性噪声转化为加性噪声, 然后基于矩阵满秩分解和加权最小二乘理论, 提出了具有较
小计算负担的加权观测融合估计算法. 分析了加权观测融合估计算法的稳态特性, 给出了稳态存在的一个充分条
件. 所提出的加权观测融合估值器与集中式融合估值器具有相同的精度, 即具有全局最优性. 仿真研究验证了算法
的有效性. |
| 英文摘要 |
| This paper is concerned with the optimal linear estimation problem for a multisensor linear discrete-time
stochastic uncertain system with missing measurements. Different sensors have different missing measurement rates.
Firstly, multiplicative noises are transferred to additive noises. Then, based on full-rank decomposition of a matrix and
weighted least-squares theory, the weighted measurement fusion estimation algorithms with small computational burden
are developed. The steady-state property of the weighted measurement fusion estimation algorithms is analyzed. A sufficient
condition for the existence of the steady state is given. The weighted measurement fusion estimators proposed here
have the same accuracy as the centralized fusion estimators, i.e., they have the global optimality. A simulation example
shows the effectiveness of the algorithms. |