CDKF在车载捷联惯导自对准中的应用

研究了车载捷联惯导在大方位失准角下的静基座自对准。采用Sigma点卡尔曼滤波,根据均值与协方差信息按非线性映射传播的特点,直接利用非线性模型,可以消除EKF存在的需要解析Jacobi矩阵以及将非线性系统线性化后的系统模型误差问题不易调整的弊端,其中的中心差分卡尔曼滤波(CDKF)精度高,且对状态协方差阵不敏感。仿真结果表明,在大方位失准角下采用CDKF进行初始对准,比用传统的EKF更精确且收敛速度更快。

CDKF in Initial Alignment of SINS for Land Vehicle

A method for the initial alignment of the strap-down inertial navigation system of land vehicle on stationary base is presented.The extended Kalman filter (EKF) is used as the standard technique for the initial alignment of SINS.However,it is based on a sub-optimal im- plementation of the recursive Bayesian estimation framework applying Gaussian random variables.It requires analytic Jacobians.To overcome these shortages,a new extension method of Kalman filters-Sigma point Kalman filters (SPKF) is proposed.Central-difference Kalman filter (CDKF),a precise and robust method belonged to SPKF,is used to the self initial alignment of SINS.Simulation results show that CDKF is superior to the EKF and it is an efficient method in the initial alignment of SINS for land vehicle on stationary base.