预测-校正EKF算法在自主导航中的应用

Applying of Forecast-Revise EKF Algorithm in Autonomous Navigation System

为提高航天器自主导航系统非线性估计精度,通过分析EKF线性化方法的缺点,基于数学分析理论研究了非线性函数线性化展开点以及雅可比矩阵取值点不同对线性化逼近程度的影响,然后对传统EKF算法的线性化展开方式进行了改进,提出了一种基于中值定理和平滑估计的预测-校正EKF(FR-EKF)新算法。仿真结果表明,该算法在精度上优于EKF算法。

In order to improve the nonlinear estimation accuracy in autonomous navigation of spacecraft, via analyzing the drawbacks of linearization in EKF（Extended Kalman Filter）, the influence of the difference expansion point in linearization of non- linear function and the difference valued point in Jacobin matrix to the accuracy of linearization was studied based on the theory of mathematics analyzing. Then the linearization expansion way of generic EKF was improved, and a new algorithm called Forecast- Revise EKF （FR-EKF） based on mean value theorem and the smoothing estimation was proposed. Simulation result shows that the new algorithm is prior to EKF regard to accuracy.