摘要
为了提高动基座下车载捷联惯导系统(strapdown inertial navigation system,SINS)的初始对准精度和缩短对准时间,在不进行粗对准的前提下,利用5阶容积卡尔曼滤波(cubature Kalman filter,CKF)完成非线性对准。针对3阶CKF滤波精度不高、5阶高斯厄密特滤波器计算量过大的问题,基于多项式逼近的思想详细推导了5阶球面径向容积规则,继而提出了5阶CKF并分析了该算法的滤波精度、采样量和数值稳定性,利用奇异值分解代替Cholesky分解来增强滤波稳定性。实验结果表明,该方法能够有效完成大失准角下的非线性对准,精度高于3阶CKF。
In order to improve alignment precision and reduce time for the initial alignment of strapdown inertial navigation system （SINS） under the moving base, a new method that nonlinear alignment with 5th-degree cubature Kalman filter （CKF） without coarse alignment is proposed. Because of lower accuracy of 3rd-degree CKF and too much calculation work of the 5th-degree Gauss Hermite quadrature filter, a new sampling rule named 5th-degree spherical radial cubature rule based on polynomials approximation and a new CKF with 5th- degree accuracy from this rule are deduced. The filter accuracy, sampling points, numerical stability are analyzed. The singular value decomposition algorithm is used to replace Cholesky decomposition for stronger stability. The experiment results demonstrate that the method is able to complete nonlinear alignment on big misalignment angles and has higher estimation accuracy than 3rd degree CKF.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2015年第3期633-638,共6页
Systems Engineering and Electronics
基金
军队计划项目资助课题
关键词
容积卡尔曼滤波
球面径向容积规则
初始对准
动基座
cubature Kalman filter （CKF）
spherical radial eubature rule
initial alignment
moving base
