Initial alignment is one of the key technologies in strapdown inertial navigation system (SINS) to provide initial state information for vehicle attitude and navigation. For some situations, such as the attitude heading reference system, the position is not necessarily required or even available, then the self-alignment that does not rely on any external aid becomes very necessary. This study presents a new self-alignment method under swaying conditions, which can determine the latitude and attitude simultaneously by utilizing all observation vectors without solving the Wahba problem, and it is different from the existing methods. By constructing the dyadic tensor of each observation and reference vector itself, all equations related to observation and reference vectors are accumulated into one equation, where the latitude variable is extracted and solved according to the same eigenvalues of similar matrices on both sides of the equation, meanwhile the attitude is obtained by eigenvalue decomposition. Simulation and experiment tests verify the effectiveness of the proposed methods, and the alignment result is better than TRIAD in convergence speed and stability and comparable with OBA method in alignment accuracy with or without latitude. It is useful for guiding the design of initial alignment in autonomous vehicle applications.

翻译：初始对准是捷联惯性导航系统（SINS）中的关键技术之一，旨在为车辆姿态与导航提供初始状态信息。在某些场景下（如航姿参考系统），位置信息并非必需甚至无法获取，此时无需外部辅助的自对准方法变得尤为重要。本文提出一种摇摆环境下的新型自对准方法，该方法无需解算Wahba问题即可利用全部观测矢量同时确定纬度和姿态，与现有方法存在本质差异。通过构建各观测矢量与其对应参考矢量的并矢张量，将全部观测-参考矢量方程累积为单一方程，基于方程两侧相似矩阵特征值相等的原理提取并解算纬度变量，同时通过特征值分解获得姿态。仿真与实验验证了所提方法的有效性：与TRIAD算法相比，该方法在收敛速度与稳定性方面表现更优；与OBA算法相比，无论在是否已知纬度的条件下均能达到相当的精度。本研究对自主车辆应用场景下的初始对准设计具有指导意义。