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协方差交叉融合Kalman预报器
引用本文:张鹏. 协方差交叉融合Kalman预报器[J]. 现代电子技术, 2012, 35(17): 107-109
作者姓名:张鹏
作者单位:哈尔滨德强商务学院,黑龙江哈尔滨,150025
基金项目:2011年度黑龙江省普通高等学校青年学术骨干支持计划项目(1251G012)
摘    要:对于带未知局部预报误差互协方差的两传感器跟踪系统,通过协方差交叉融合方法,得到了协方差交叉融合稳态Kalman预报器,并用协方差椭圆的方法给出了其精度关系的几何解释。用相关方法证明了协方差交叉融合稳态Kalman预报器的精度高于每个局部稳态最优Kalman预报器,低于按矩阵加权融合稳态最优Kalman预报器。用一个Monte-Carlo仿真例子说明了协方差交叉融合稳态Kalman预报器的精度接近于稳态最优融合Kalman预报器。

关 键 词:信息融合Kalman预报器  协方差交叉融合  未知互协方差  协方差椭圆  融合精度

Kalman predictor based on covariance intersection fusion
ZHANG Peng. Kalman predictor based on covariance intersection fusion[J]. Modern Electronic Technique, 2012, 35(17): 107-109
Authors:ZHANG Peng
Affiliation:ZHANG Peng(Harbin Deqiang College of Commerce,Harbin 150025,China)
Abstract:By using the covariance intersection(CI) fusion method,the covariance intersection fusion steady-state Kalman predictor is presented for the two-sensor tracking system with unknown cross-covariances between the local predicting errors.The geometric interpretation of accuracy relations is given by means of the covariance ellipses.The relevant methods demonstrate that the accuracy of convariance intersection fusion Kalman predictor is higher than that of each local steady-state optimal Kalman predictor,and is lower than that of the matrix weighted fusion steady-state optimal predictor.A Monte-Carlo simulation example shows that its accuracy is close to that of the steady-state optimal fusion Kalman predictor.
Keywords:information fusion Kalman predictor  covariance intersection fusion  unknown cross-covariance  covariance ellipse  fusion accuracy
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