| 基于强跟踪滤波器的多传感器信息融合应用研究 |
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| 引用本文： | 李淑玉,楼树美,孔李军. 基于强跟踪滤波器的多传感器信息融合应用研究[J]. 计算机与数字工程, 2009, 37(8): 54-57,117 |
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| 作者姓名： | 李淑玉 楼树美 孔李军 |
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| 作者单位： | 信阳职业技术学院,信阳,464000;河南工业大学,郑州,450001 |
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| 基金项目： | "十一五"国家科技支撑计划重点项目 |
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| 摘 要： | 在对经典Kalman滤波器和强跟踪Kalman滤波器分析的基础上,给出了改进的强跟踪Kalman滤波器方法,并进一步给出了改进的强跟踪Kalman滤波器分布式信息融合方法。该方法底层采用改进的强跟踪器滤波,上层采用估计误差方差最小方法进行分布式信息融合,信息融合结果精度高,同时对突变信号有很强的实时跟踪能力。仿真结果表明该方法的有效性和可靠性。
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| 关 键 词： | Kalman滤波器 信息融合 多传感器 |
Distributed Information Fusion Applied Research Based on the Strong Tracking Filter |
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| Li Shuyu,Lou Shumei,Kong Lijun. Distributed Information Fusion Applied Research Based on the Strong Tracking Filter[J]. Computer and Digital Engineering, 2009, 37(8): 54-57,117 |
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| Authors: | Li Shuyu Lou Shumei Kong Lijun |
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| Affiliation: | Xinyang Vocational and Technical College1;Henan University of Technology2 |
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| Abstract: | On the basis of the analysis of basic Kalman filter and strong-tracking Kalman filter,we propose a modified strong-tracking Kalman filter and a modified strong-tracking Kalman filter distributed information fusion algorithm.In this method,we adopted modified strong-tracking Kalman filter on the bottom information processing,and the smallest variance estimation error method used on the top.Fusion results have high precision and a very strong real-time tracking capability for urgent change signal.Simulation s... |
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| Keywords: | Kalman filter information fusion multi-sensor |
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