An Improved SINS Alignment Method Based on Adaptive Cubature Kalman Filter

被引:8
|
作者
Zhang, Yonggang [1 ]
Xu, Geng [1 ]
Liu, Xin [1 ]
机构
[1] Harbin Engn Univ, Dept Automat, Harbin 150001, Peoples R China
基金
中国国家自然科学基金;
关键词
adaptive Kalman filter; initial alignment; cubature Kalman filter; variational Bayesian method; INERTIAL NAVIGATION SYSTEM; INITIAL ALIGNMENT; INTEGRATION; ATTITUDE;
D O I
10.3390/s19245509
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Initial alignment is critical and indispensable for the inertial navigation system (INS), which determines the initial attitude matrix between the reference navigation frame and the body frame. The conventional initial alignment methods based on the Kalman-like filter require an accurate noise covariance matrix of state and measurement to guarantee the high estimation accuracy. However, in a real-life practical environment, the uncertain noise covariance matrices are often induced by the motion of the carrier and external disturbance. To solve the problem of initial alignment with uncertain noise covariance matrices and a large initial misalignment angle in practical environment, an improved initial alignment method based on an adaptive cubature Kalman filter (ACKF) is proposed in this paper. By virtue of the idea of the variational Bayesian (VB) method, the system state, one step predicted error covariance matrix, and measurement noise covariance matrix of initial alignment are adaptively estimated together. Simulation and vehicle experiment results demonstrate that the proposed method can improve the accuracy of initial alignment compared with existing methods.
引用
收藏
页数:24
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