| 多传感器加权观测融合Wiener反卷积滤波器 |
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| 引用本文： | 崔崇信.多传感器加权观测融合Wiener反卷积滤波器[J].科学技术与工程,2010,10(30). |
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| 作者姓名： | 崔崇信 |
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| 作者单位： | 1. 黑龙江科技学院电气与信息工程学院,哈尔滨,150027
2. 黑龙江大学电子工程学院,哈尔滨,150080 |
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| 摘 要： | 基于Kalman滤波方法，应用加权观测融合方法，提出了全局最优观测融合Wiener反卷积滤波器。同集中式观测融合方法和分布式状态融合方法相比，不仅可获得全局最优Wiener反卷积滤波器，而且明显减小计算负担，便于实时应用。一个四传感器加权观测融合仿真例子说明了其有效性。
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| 关 键 词： | 多传感器 加权观测融合 Wiener反卷积滤波器 Kalman滤波方法 |
| 收稿时间： | 7/24/2010 6:24:09 PM |
| 修稿时间： | 8/7/2010 10:59:56 AM |
Multisensor Weighted Measurement Fusion Wiener Deconvolution Filter |
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| Cuichongxin.Multisensor Weighted Measurement Fusion Wiener Deconvolution Filter[J].Science Technology and Engineering,2010,10(30). |
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| Authors: | Cuichongxin |
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| Institution: | CUI Chong-xin,DENG Zi-li1(Department of Electrical and Information Engineering,College of Heilongjiang Science and Techniques,Harbin 150027,P.R.China,Department of Electronic Engineering1,Heilongjiang University,Harbin 150080,P.R.China) |
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| Abstract: | Based on the Kalman filtering method, applying the weighting measurement fusion method, a globally optimal multisensor measurement fusion Wiener deconvolution filter is presented. Compared with the centralized measurement fusion method and the decentralized state fusion method, not only the globally optimal Wiener signal filter can be obtained, but also the computational burden can obviously be reduced, so that it is suitable for real time application. A simulation example with four- sensor shows its effectiveness. |
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| Keywords: | multisensor weighting measurement fusion Wiener deconvolution filter Kalman filtering method |
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