地磁辅助惯性导航系统的数据融合算法

Data fusing algorithm in geomagnetic aided INS

对地磁辅助导航技术的基本原理进行分析,详细介绍了采样卡尔曼滤波算法并将其用于惯性/地磁导航系统的数据融合,即通过设计少量的sigma点,并计算这些sigma点通过非线性函数的变换,从而获得滤波值基于非线性状态方程的更新。仿真表明,特别是当系统非线性较大时,采样卡尔曼器性能明显优于扩展卡尔曼滤波器。因此,从某种程度上说,采样卡尔曼滤波可以替代扩展卡尔曼滤波在地磁辅助导航系统中使用。

The theory of the geomagnetic aided inertial navigation system（INS） was analyzed. The unscented Kalman filtering was introduced and applied into the integrated system. In unscented Kalman filtering, the updating of the filtering based on the nonlinear state space equation was realized by designing a few sigma points and calculating the transformation of these sigma points via non-linear function. The simulation shows that it is more precise and more convenient in computing, and the performance of unscented Kalman filter is superior to that of extended one, so it can be used in Geomagnetic aided INS.