摘要
针对捷联惯导系统在大方位失准角情况下的初始对准问题,提出了一种基于MPF-CKF的非线性滤波方法.MPF-CKF将部分惯性器件误差作为模型误差,降低了系统的维数,不仅提高了初始对准的精度,而且克服了将模型误差假设为高斯白噪声的局限性.通过滤波仿真比较,进一步表明了MPF-CKF能提高SINS在大方位失准角初始对准中的估计精度和收敛速度.
In case of the initial alignment in the strapdown inertial navigation system （SINS） with a large azimuth misalignment, a nonlinear filtering method based on MPF-CKF is proposed in this paper. MPF- CKF takes part of the inertial errors as model errors, reduces system dimensions, which not only improves the accuracy of initial alignment, but also overcomes the limitation that model errors are assumed to he Gaussian white noise. Filter simulation shows that MPF-CKF can improve the estimation accuracy and convergence speed in the initial alignment with a large azimuth misalignment in the SINS.
出处
《北京工业大学学报》
CAS
CSCD
北大核心
2013年第10期1468-1473,共6页
Journal of Beijing University of Technology
基金
中央高校基本科研业务费专项资金资助项目(DL13BB14)
