强跟踪CDKF 及其在组合导航中的应用

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.

Strong tracking CDKF and application for integrated navigation

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.