| 基于Kalman滤波的自回归滑动平均信号信息融合Wiener滤波器 |
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| 引用本文： | 邓自立,高 媛. 基于Kalman滤波的自回归滑动平均信号信息融合Wiener滤波器[J]. 控制理论与应用, 2005, 22(4): 641-644 |
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| 作者姓名： | 邓自立 高 媛 |
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| 作者单位： | 黑龙江大学,自动化系,黑龙江,哈尔滨,150080;黑龙江大学,自动化系,黑龙江,哈尔滨,150080 |
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| 基金项目： | 国家自然科学基金资助项目(60374026)，黑龙江大学自动控制重点实验室资助项目(04-01). |
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| 摘 要： | 应用Kalman滤波方法,在按矩阵加权线性最小方差最优信息融合规则下,提出了带白色观测噪声的多通道ARMA信号的多传感器信息融合Wiener滤波器.它可统一处理信息融合滤波、平滑和预报问题.为了计算最优加权阵,提出了计算局部滤波误差互协方差阵的公式.同单传感器情形相比,可提高估计精度.一个带三传感器的目标跟踪系统的仿真例子说明了其有效性.
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| 关 键 词： | 多通道ARMA信号 多传感器信息融合 按矩阵加权最优融合规则 Wiener滤波器 Kalman滤波方法 |
| 文章编号： | 1000-8152（2005）04-0641-04 |
| 收稿时间： | 2003-12-23 |
| 修稿时间： | 2003-12-232004-12-31 |
Kalman filtering-based information fusion Wiener filter of autoregressive moving average signals |
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| DENG Zi-li,GAO Yuan. Kalman filtering-based information fusion Wiener filter of autoregressive moving average signals[J]. Control Theory & Applications, 2005, 22(4): 641-644 |
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| Authors: | DENG Zi-li GAO Yuan |
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| Affiliation: | Department of Automation,Heilongjiang University,Harbin Heilongjiang 150080,China |
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| Abstract: | By using the Kalman filtering method and the linear minimum variance optimal fusion rule weighted by matrices,a multisensor information fusion Wiener filter is presented for the multichannel autoregressive moving average(ARMA) signals with white observation noise.It can handle the information fusion filtering,smoothing and prediction problems in a unified framework.In order to compute the optimal weighting matrices,the formula of computing the cross-covariance matrices among local filtering errors,is presented.Compared with the single sensor case,the estimation accuracy is improved.A simulation example for a target tracking system with three-sensor shows its effectiveness. |
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| Keywords: | multichannel AMAR signal multisensor information fusion optimal fusion rule weighted by matrices Wiener filter Kalman filtering method |
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