固定指数加权模糊自适应EKF研究及其应用  

The Research and Application of Fixed Exponential Weighting Fuzzy-logic Based Extended Klaman Filter

作　　者：刘山林[1] 蔡宗平[1] 

机构地区：[1]第二炮兵工程学院,西安710025

出　　处：《弹箭与制导学报》2009年第2期238-241,共4页Journal of Projectiles,Rockets,Missiles and Guidance

摘　　要：为了改善扩展卡尔曼滤波(EKF)算法在机动目标跟踪中的跟踪性能,文中研究了一种固定指数加权模糊自适应扩展卡尔曼滤波技术,通过监视理论残差和实际残差的协方差一致程度,应用模糊推理系统不断调整滤波协方差,对扩展卡尔曼滤波器(EKF)进行在线自适应控制,最终实现最优估计。仿真结果表明,改进的算法稳定性高,精度得到明显改善,用于弱机动目标跟踪效果较好。For improving the tracking performance of extended Kalman filter（EKF） in maneuvering target tracking,the fixed exponential weighting fuzzy-logic based extended Kalman filter is studied. Through monitoring the degree of compatibility between the covariance of theoretical residual and the eovarianee of actual residual, adaptive control is proceeded for the extended Kalman filter to realize optimal estimation by continuously adjusting the covariance of filter using the fuzzy-logic System. Simulation results demonstrate that the algorithm improves the filter precision, especially in the cases of low maneuvring target tracking.

关 键 词：扩展卡尔曼滤波 固定指数加权 自适应模糊推理系统 机动目标跟踪 

分 类 号：TN713[电子电信—电路与系统]