| 一种组合式的Kalman滤波算法 |
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| 引用本文： | 余翔,冯璐,漆晶.一种组合式的Kalman滤波算法[J].电视技术,2013,37(9). |
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| 作者姓名： | 余翔 冯璐 漆晶 |
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| 作者单位： | 重庆邮电大学电信业务支撑系统研究所,重庆,400065 |
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| 摘 要： | 针对Kalman滤波算法在估计过程中存在噪声影响和过程信号无法直接观测等问题,提出一种组合式的Kalman滤波算法.首先对观测的数据进行自适应加权融合,然后将融合的结果作为第二级Kalman滤波的先验估计值,进行Kalman滤波.通过自适应算法与Kalman算法的组合算法进行数据融合,可以提高融合的准确度和精度.最后通过仿真证实算法的有效性.
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| 关 键 词： | Kalman 自适应加权 数据融合 |
| 收稿时间： | 9/9/2012 12:00:00 AM |
| 修稿时间： | 2012/10/16 0:00:00 |
A combination of Kalman filtering algorithm |
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| YU Xiang,feng lu and QI Jing.A combination of Kalman filtering algorithm[J].Tv Engineering,2013,37(9). |
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| Authors: | YU Xiang feng lu and QI Jing |
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| Affiliation: | Chongqing University of Posts and Telecommunications,Chongqing University of Posts and Telecommunications,Chongqing University of Posts and Telecommunications |
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| Abstract: | Based on the noise impact and process signals in Kalman filtering can not be directly observed, and proposes a kind of combination of Kalman filtering algorithm. Observation data first by fusion adaptive weighted fusion algorithm, the fusion results as a priori estimates of the second step Kalman filtering. The new algorithm combinated by adaptive algorithm and the Kalman algorithm improves the accuracy and precision. Finally, simulation confirmed the effectiveness of the algorithm. |
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| Keywords: | Kalman Adaptive Weighted Data fusion |
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