| 多传感器AR信号自校正加权融合Wiener滤波器 |
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| 引用本文： | 王伟,邓自立.多传感器AR信号自校正加权融合Wiener滤波器[J].科学技术与工程,2010,10(3). |
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| 作者姓名： | 王伟 邓自立 |
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| 作者单位： | 黑龙江大学自动化系,哈尔滨,150080 |
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| 基金项目： | 国家自然科学基金(60874063)资助 |
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| 摘 要： | 对带多传感器和带未知模型参数及未知噪声方差的自回归(AR)信号,应用递推辅助变量(RIV)算法得到局部模型参数估值器,用相关方法得到局部噪声方差估值器。用取局部估值器的平均得到信息融合估值器。将它们代入最优加权融合AR信号Wiener滤波器,提出一种自校正加权融合Wiener滤波器。它们以概率1收敛于最优融合Wiener滤波器,因而具有渐近最优性。它的精度比每个局部自校正Wiener滤波器精度都高。仿真例子说明了其有效性。
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| 关 键 词： | 多传感器信息融合加权融合 AR信号 参数估计 噪声方差估计 自校正Wiener滤波器 收敛性 |
| 收稿时间： | 2009/10/19 0:00:00 |
| 修稿时间： | 2009/10/23 0:00:00 |
Self-tuning Weighted Fusion Wiener Filter for with AR signals |
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| Wang Wei and Deng Zili.Self-tuning Weighted Fusion Wiener Filter for with AR signals[J].Science Technology and Engineering,2010,10(3). |
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| Authors: | Wang Wei and Deng Zili |
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| Institution: | Department of Automation/a>;Heilongjiang University/a>;Harbin 150080.P.R.China |
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| Abstract: | For the autoregressive(AR) signals with multisensor,and with unknown model parameters and noise variance,applying the recursive instrumental variable(RIV) yields the local estimators of the model parameters,and applying the correlation method yields the local noise variance estimators,their information fusion estimators are obtained by taking the average of the local estimators.Substituting them into the optimal weighted fusion Wiener filter of the AR signals,a self-turning weighted fusion Wiener filter is ... |
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| Keywords: | multisensor information fusion weighted fusion AR signal parameter estimation noise variance estimation self-tuning Wiener filter convergence |
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