Abstract: According to the specific work environment and the alignment accuracy of Autonomous Underwater Vehicles(AUV), a modified two-position integrated alignment based on Kalman filtering is proposed in this paper. The inertial navigation error model is built and the principle of two-position alignment is analyzed. The systematic observability is improved by changing the strapdown matrix. The degree of observability for Strap-down Inertial Navigation System(SINS) is computed in the context of two-position alignment scheme using the spectral condition number theory. Simulation results show that the device errors can be estimated by the novel two-position alignment, and greatly improve the alignment precision

Key words: Autonomous Underwater Vehicles(AUV), two-position alignment, Kalman filtering, observability, spectral condition number

摘要： 针对自主式水下潜器(AUV)的特定工作环境及导航系统对准精度的需求，提出一种基于Kalman滤波的两位置组合对准方法。建立系统误差模型，分析两位置组合对准原理，通过改变惯导系统误差模型中的捷联矩阵改善系统的可观测性，利用谱条件数求取两位置对准时系统参数可观测度。仿真结果表明，该方法能准确估计器件偏差，经补偿后能提高系统的对准精度。

关键词: 自主式水下潜器, 两位置对准, Kalman滤波, 可观测性, 谱条件数

CLC Number: 

• U666.1