大失准角下SINS的KF/EKF2混合滤波对准

针对捷联惯导系统(SINS)大失准角下滤波对准过程中非线性滤波器状态维数过大的问题,提出了一种基于模型分解的卡尔曼滤波/二阶扩展卡尔曼滤波(KF/EKF2)混合滤波方法,将基于欧拉平台误差角的非线性滤波模型分解为线性部分和非线性部分,分别采用线性KF滤波和非线性EKF2滤波处理,并且设计了混合滤波的滤波步骤。实验结果表明,KF/EKF2混合滤波算法在计算量、实时性及精度等方面优于最常用的无迹卡尔曼滤波(UKF)和EKF2滤波。

KF/EKF2 Hybrid Filter for SINS Alignment Under Large Misalignment Angles

Aiming at the problem of excessive state dimension of nonlinear filter in SINS filtering alignment process under large misalignment angles, the Kalman filtering/extended Kalman filtering (KF/EKF2) hybrid filtering method based on the model decomposition is proposed. The initial alignment model based on Euler platform error angle (EPEA) is decomposed into the linear part and nonlinear part, and is processed by the linear KF filter and nonlinear EKF2 filter respectively. The filtering process is designed to ensure the overall optimization of state variables. The experiment results show that the KF/EKF2 hybrid filtering algorithm is superior to the most commonly used unscented Kalman filtering (UKF) and EKF2 filtering in terms of computational complexity, real time performance and accuracy.