基于多矢量定姿的动基座最优化对准算法

针对车载捷联惯导系统（Strapdown Inertial Navigation System, SINS）的传统动基座粗对准方法精度低且环境适应性差的问题，提出了一种基于多矢量定姿的动基座最优化粗对准算法。在传统的基于重力矢量的初始对准方法基础上，将姿态矩阵求解问题转化为Wahba问题，实现对多个时刻重力矢量信息的充分利用，并通过SVD算法实现对Wahba问题的求解，结合全球导航卫星系统（Global Navigation Satellite System, GNSS）输出信息和SINS输出信息，构建状态方程和量测方程，采用Sage-Husa自适应滤波算法以解决量测噪声不准确问题，不断修正载体系变换矩阵以获得更加精确的姿态转换矩阵。仿真和半物理实验表明，改进算法能够明显提高惯导系统在动基座下的姿态精度，转台实验对准方位误差小于0.05°。

Optimal Alignment Algorithm for Moving Base Based on Multi Vector Attitude Determination

Aiming at the problems of low precision and poor adaptability of traditional moving base coarse alignment method for vehicle strapdown inertial navigation system (SINS), an optimal coarse alignment algorithm for moving base based on multi vector attitude determination is proposed. On the basis of the traditional initial alignment method based on gravity vector, the problem of solving attitude matrix is transformed into Wahba problem to make full use of the information of gravity vector at multiple times. The problem of solving Wahba is solved by SVD algorithm. Combining the output information of global navigation satellite system (GNSS) and SINS, the process equation and measurement equation are constructed. Sage-Husa adaptive filtering algorithm is used to solve the problem of measurement noise inaccuracy, and the transform matrix of carrier frame is continuously modified to obtain more accurate attitude conversion matrix. Simulation and semi physical experiments show that the improved algorithm can significantly improve the alignment accuracy, and the alignment azimuth error of turntable experiment is less than 0.05 °.