摘要
为了解决常规卡尔曼滤波法存在的不足,给出了用模糊推理系统与卡尔曼法相结合的方法。该方法通过监视理论残差和实际残差的协方差一致程度,应用模糊系统不断调整滤波器的增益系数,对卡尔曼滤波器进行在线自适应控制,最终实现最优估计。通过对INS/GPS组合导航系统的计算机仿真,结果表明该方法是有效、实用的。
In order to resolve the shortcomings of the traditional Kalman filtering, a new method is presented in which the fuzzy reasoning system is combined with the traditional Kalman technology. By monitoring the covariance between abstract residual and actual residual, this algorithm modifies recursively the gain coefficient of the filter so as to adaptively control the Kalman filter. Finally the optimal estimate is achieved. The computer simulation results of the INS / GPS integrated navigation system indicate that the algorithm is effective and practical.
出处
《空军工程大学学报（自然科学版）》
CSCD
北大核心
2007年第2期36-39,共4页
Journal of Air Force Engineering University(Natural Science Edition)
基金
航空基金资助项目(619010803-1)
关键词
模糊推理系统
自适应卡尔曼滤波
组合导航
fuzzy reasoning system
adaptive Kalman filter
integrated navigation
