Volume 40, Number 1, February 2022
|Page(s)||103 - 109|
|Published online||02 May 2022|
An improved initial alignment method based on adaptive robust CKF algorithm
National University of Defense Technology, Changsha 410073, China
2 China Academy of Launch Vehicle Technology, Beijing 100076, China
When the misalignment angle is a large angle in the strapdown inertial navigation system (SINS), it is necessary to establish a nonlinear error model to estimate the error. Hence, an improved initial alignment method based on adaptive robust CKF algorithm is proposed in this paper. Firstly, based on the analysis results, SINS/GPS nonlinear error model is established. Secondly, in the view of observation gross errors and inaccurate noise statistical characteristics, adaptive robust CKF algorithm is designed. Finally, according to simulation analysis and experiment, adaptive robust CKF algorithm can augment the stability, improve filter estimation accuracy and convergence rate, which significantly improves the initial alignment ability of strapdown inertial navigation system at large azimuth misalignment angle.
捷联惯导初始对准过程中存在大方位失准角的情况, 需要通过建立非线性误差模型来对误差进行估计, 因此对相应初始对准技术进行了研究。通过分析, 构建捷联惯性导航系统和全球定位系统的精准非线性误差模型; 基于自适应抗差理论对容积卡尔曼滤波(CKF)算法对随机干扰的统计特性以及观测粗差计算模型进行改进; 设计相应的仿真评估测试和实物验证方法, 试验结果证明提出的方法在初始对准中具有更强的滤波稳定性、更高的滤波估计精度和更短的算法收敛时间。
Key words: large azimuth misalignment / integrated alignment / nonlinear error model / adaptive robust CKF
关键字 : 大方位失准角 / 初始对准 / 非线性误差模型 / 自适应抗差CKF
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