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An In-Motion Initial Alignment Algorithm for SINS Using Lie Group Matrix Kalman Filter

机译:李群矩阵卡尔曼滤波器的捷联惯导运动初始对准算法

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In this paper, an in-motion initial alignment algorithm based on Lie group matrix kalman filter is proposed. According to the Lie group’s properties and the attitude optimization-based initial alignment idea, the attitude matrix is decomposed into three continuous special orthogonal matrices to separate the rotation information and motion information under the in-motion conditions. A linear system model is established based on the differential equation of Lie group, which can replace the traditional quaternion model and avoid the non-uniqueness of unit quaternion representation. Then the Lie Group Matrix Kalman Filter is proposed for estimating the initial inertial matrix directly. And the Simplified Lie Group Matrix Kalman Filter with special process noise is proposed in some specific situations. From the simulation, the alignment accuracy and stability of the two algorithms satisfies the SINS navigation requirements. These two methods have good application prospects for the in-motion initial alignment of SINS.
机译:提出了一种基于李群矩阵卡尔曼滤波器的运动中初始对准算法。根据Lie小组的属性和基于姿态优化的初始对齐思路,将姿态矩阵分解为三个连续的特殊正交矩阵,以分离运动条件下的旋转信息和运动信息。基于李群的微分方程建立了线性系统模型,该模型可以代替传统的四元数模型,避免了单元四元数表示的不唯一性。然后提出李群矩阵卡尔曼滤波器,直接估计初始惯性矩阵。在某些特定情况下,提出了具有特殊过程噪声的简化李群矩阵卡尔曼滤波器。从仿真结果看,两种算法的对准精度和稳定性都满足了捷联惯导系统的导航要求。这两种方法在SINS运动初始对准中都具有良好的应用前景。

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