| 引用本文: | 邓自立,王伟玲,王强.自校正信息融合Wiener预报器及其收敛性[J].控制理论与应用,2009,26(11):1261~1266.[点击复制] |
| DENG Zi-li,WANG Wei-ling,WANG Qiang.Self-tuning information fusion Wiener predictor and its convergence[J].Control Theory and Technology,2009,26(11):1261~1266.[点击复制] |
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| 自校正信息融合Wiener预报器及其收敛性 |
| Self-tuning information fusion Wiener predictor and its convergence |
| 摘要点击 1932 全文点击 1081 投稿时间：2008-10-21 修订日期：2009-01-07 |
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| DOI编号 |
| 2009,26(11):1261-1266 |
| 中文关键词 多传感器信息融合 相关观测噪声 噪声统计估计 Lyapunov方程 自校正Wiener预报器 收敛性 现代时间序列分析方法 |
| 英文关键词 multisensor information fusion correlated measurement noises noise statistics estimation Lyapunov equation self-tuning Wiener predictor convergence modern time series analysis method |
| 基金项目 国家自然科学基金资助项目(60874063); 黑龙江大学自动控制重点实验室资助项目(F04–01). |
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| 中文摘要 |
| 对带相关观测噪声和未知噪声统计的多传感器系统, 用相关方法得到噪声统计在线估值器．在按分量标量加权线性最小方差最优信息融合准则下, 用现代时间序列分析方法, 基于滑动平均(moving average)新息模型的辨识, 提出了自校正解耦融合Wiener预报器．用动态误差系统分析(dynamic error system analysis)方法证明了自校正融合Wiener预报器收敛于最优融合Wiener预报器, 因而它具有渐近最优性．它的精度比每个局部自校正Wiener预报器精度都高．它的算法简单, 便于实时应用．一个目标跟踪系统的仿真例子说明了其有效性. |
| 英文摘要 |
| For the multisensor systems with correlated measurement noises and unknown noise statistics,the on-line noise statistics estimators are obtained by the correlation method．Under the linear minimum variance optimal information
fusion criterion weighted by scalars for components,by the modern time series analysis method,a self-tuning decoupled fusion Wiener predictor is presented based on the identification of the moving average(MA) innovation models．By using the dynamic error system analysis(DESA) method,it is proved that the self-tuning fusion Wiener predictor converges to the optimal fusion Wiener predictor,so that it has the asymptotic optimality．Its accuracy is higher than that of each local self-tuning Wiener predictor．Its algorithm is simple,and is suitable for real time applications．A simulation example for
a target tracking system shows its effectiveness. |
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