In-Motion Forward-Forward Backtracking Fine Alignment Based on Displacement Observation for SINS/GNSS

被引:0
|
作者
Zhu, Yongyun [1 ]
Zhu, Yaohui [1 ]
Wei, Xinhua [1 ]
Cui, Bingbo [1 ]
Liu, Shede [2 ]
机构
[1] Jiangsu Univ, Sch Agr Engn, Zhenjiang 212013, Peoples R China
[2] Southeast Univ, Sch Instrument Sci & Engn, Nanjing 210096, Peoples R China
关键词
fine alignment; SINS/GNSS; forward-forward backtracking; displacement observation; KALMAN FILTER; NAVIGATION; SYSTEM; SINS;
D O I
10.3390/s24247916
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
To solve the problem of slow convergence seen in the traditional fine alignment algorithm based on linear Kalman filtering, a forward-forward backtracking fine alignment algorithm for SINS is proposed after reanalyzing the fine alignment model in this paper. First, the forward-forward backtracking fine alignment model in initial navigation frame was derived. The displacement vector of the carrier in the initial navigation frame solved by GNSS positioning was utilized as the observation of the fine alignment model. Second, under the premise of storing only part of the navigation data, the initial alignment convergence speed was improved by backtracking and reusing the navigation data. The experimental results of the simulation and vehicle tests showed that each backtracking alignment can improve the accuracy of the fine alignment to the performance requirements of the initial alignment, which proved the effectiveness and feasibility of the backtracking fine alignment algorithm proposed in this paper.
引用
收藏
页数:17
相关论文
共 42 条
  • [41] A New Kalman Filter-Based In-Motion Initial Alignment Method for DVL-Aided Low-Cost SINS
    Luo, Li
    Huang, Yulong
    Zhang, Zheng
    Zhang, Yonggang
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 70 (01) : 331 - 343
  • [42] Mechanism of butterfly forward flight and prototype verification based on characteristic motion observation
    Zhang Y.
    Wang X.
    Wang S.
    Chi X.
    Du S.
    Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics, 2023, 49 (07): : 1651 - 1660