未知纬度的捷联惯导系统晃动基座自对准方法（英文）

Novel self-alignment algorithm with unknown latitude for SINS on swing base

传统捷联惯导系统晃动基座对准方法中,一般要求提供当地准确的地理纬度信息,如果给定的纬度存在误差,会对初始对准精度造成影响。针对纬度未知情况下的晃动基座对准问题,提出了利用三个不同时刻的重力视运动向量的运算进行对准的方法,推导了三矢量定姿对准的基本原理。针对含有随机噪声的加速度计测量值构造的重力视运动向量会导致向量运算时出现共线向量的问题,设计了一种基于平均权重系数的自适应卡尔曼滤波器,能在未知动态环境下有效去除加速度计随机噪声,提高对准精度。仿真和试验结果表明,该方法可在纬度未知条件下完成捷联惯导系统晃动基座下的自对准并估计出纬度值,对准精度可达惯性器件误差所决定的对准极限精度。

Traditional initial alignment method for strapdown inertial navigation system on swing base requires accurate local geographic latitude information. In view of the alignment on swing base with unknown latitude, an alignment method using gravitational apparent motion vectors at three different moments is proposed to implement the vector calculations. The basic principle of the self-alignment method using three vectors of gravitational apparent motion is deduced. Since the random noise in the accelerometer measurements would affect the accuracy of the constructed gravitational apparent motion vectors and generate collinear vectors in the process of vector operations, an adaptive Kalman filter based on average weighting coefficient is designed, which can effectively reduce the accelerometer random noises in dynamic uncertain environment and improve the alignment accuracy. Simulation and experimental results show that the proposed method can realize the self-alignment of the SINS on swing base when the latitude information is unknown, and the alignment accuracy can reach the extreme accuracy determined by the errors of inertial devices.