基于UKF的旋转式SINS大方位失准角初始对准方法

Rotary SINS initial alignment for large heading misalignment based on UKF

旋转调制自补偿技术可以调制惯性元件的常值误差,从而提高惯性导航系统的导航精度。出于实际工程应用需求,研究了旋转式SINS大方位失准角初始对准方法。以单轴旋转式SINS为例,给出了单轴旋转式SINS大方位失准角非线性误差模型;根据系统误差模型的非线性特性,利用简化Unscented卡尔曼滤波(Unscented Kalman Filter UKF)算法,设计了系统的大方位失准角初始对准算法。数字仿真实验结果表明:在相同条件下,提出的UKF算法在收敛速度与对准精度方面均优于EKF算法;系统试验验证结果表明,采用本文提出的初始对准方法,系统的水平对准精度优于0.1′,方位对准精度优于1.5′,证明本文提出的初始对准方法在工程应用中是有效、可行的。

The constant errors of the inertial elements could be modulated by the rotary modulation to improve the accuracy of the inertial navigation system. For the requirement of practical engineering application, the rotary SINS （strapdown inertial navigation system） initial alignment for large heading misalignment angles （LHMA） was studied. With single rotary SINS as an example, the single rotary SINS LHMA nonlinear error models were established. According to the nonlinear characteristic, the LHMA initial alignment arithmetic for the single rotary SINS was designed using the simplified Unscented Kalman Filter （UKF）. The simulation results show that the UKF arithmetic outperforms the extended Kalman filter in convergence and accuracy. The results of the system experiment using the initial alignment arithmetic show that the level initial alignment accuracy is superior to 0.1＇, and the heading accuracy is superior to 1.5＇, showing that the proposed algorithm is effective and feasible in the practical project.