摘要
针对扩展卡尔曼滤波器(EKF)在组合导航系统模型不确定时存在滤波精度下降甚至发散的问题,提出一种具有强跟踪性能的中心差分卡尔曼滤波器(CDKF).强跟踪CDKF基于强跟踪滤波器(STF)的理论框架,采用中心差分变换代替STF中的雅可比矩阵计算,兼具STF鲁棒性强,CDKF滤波精度高和实现简单的优点,有效克服了EKF在系统模型不确定时滤波失效的缺点.仿真结果验证了强跟踪CDKF的有效性.
A central difference Kalman filter（CDKF） with strong tracking behavior is proposed to overcome the problem that extended Kalman filter（EKF） decreases in accuracy,even divergences when integrated navigation system has model uncertainty.Strong tracking CDKF views strong tracking filter（STF） as the basic theory framework and makes central difference transformation take place of calculating nonlinear function Jacobian matrix,so it combines strong robustness of STF with high accuracy and easy implementation of central difference transformation.The proposed strong tracking CDKF can avoid filtering failure of EKF while system model is uncertain.Simulation results show the effectiveness of the strong tracking CDKF.
出处
《控制与决策》
EI
CSCD
北大核心
2010年第12期1837-1842,共6页
Control and Decision
基金
国家自然科学基金项目(60974104)
