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
相关论文
共 50 条
  • [1] Robust cubature Kalman filter method for the nonlinear alignment of SINS
    Shi-luo Guo
    Ying-jie Sun
    Li-min Chang
    Yang Li
    [J]. Defence Technology, 2021, 17 (02) : 593 - 598
  • [2] Robust cubature Kalman filter method for the nonlinear alignment of SINS
    Guo, Shi-luo
    Sun, Ying-jie
    Chang, Li-min
    Li, Yang
    [J]. DEFENCE TECHNOLOGY, 2021, 17 (02): : 593 - 598
  • [3] SINS Initial Alignment Based on Fifth-degree Cubature Kalman Filter
    Zhang, Yonggang
    Huang, Yulong
    Li, Ning
    Wu, Zhemin
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (ICMA), 2013, : 401 - 406
  • [4] Moving State Marine SINS Initial Alignment Based on Transformed Cubature Kalman Filter
    Zhang, Yonggang
    Huang, Yulong
    Wu, Zhemin
    Li, Ning
    [J]. 26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC), 2014, : 3262 - 3267
  • [5] Cubature Kalman Filter In Initial Alignment of Large Heading Error In SINS
    Wang Zhenkai
    Huang Xianlin
    [J]. 2013 32ND CHINESE CONTROL CONFERENCE (CCC), 2013, : 313 - 316
  • [6] SINS Alignment Using Velocity Matching and Simplified Cubature Kalman Filter
    Ran Changyan
    Cheng Xianghong
    Wang Lei
    [J]. AUTOMATIC CONTROL AND MECHATRONIC ENGINEERING III, 2014, 615 : 255 - 258
  • [7] Variational Bayesian Adaptive Embedded Cubature Kalman Filter Algorithm for Initial Alignment of SINS with Uncertain Observations
    Wang Guangcai
    Xu Xiaosu
    Wang Jian
    [J]. 2019 IEEE 7TH INTERNATIONAL CONFERENCE ON CONTROL, MECHATRONICS AND AUTOMATION (ICCMA 2019), 2019, : 438 - 442
  • [8] Robust fading cubature Kalman filter and its application in initial alignment of SINS
    Guo, Shiluo
    Chang, Limin
    Li, Yang
    Sun, Yingjie
    [J]. OPTIK, 2020, 202
  • [9] UWB Localization Based on Improved Robust Adaptive Cubature Kalman Filter
    Dong, Jiaqi
    Lian, Zengzeng
    Xu, Jingcheng
    Yue, Zhe
    [J]. SENSORS, 2023, 23 (05)
  • [10] Improved square root adaptive cubature Kalman filter
    Zhang, Lei
    Li, Sheng
    Zhang, Enze
    Chen, Qingwei
    Guo, Jian
    [J]. IET SIGNAL PROCESSING, 2019, 13 (07) : 641 - 649