基于中心差分卡尔曼滤波的航天器视觉相对导航算法研究

在航天器视觉相对导航过程中,量测方程的非线性特性会影响航天器相对位姿的估计精度.分析了扩展卡尔曼滤波方法(EKF)将非线性模型线性化时存在的缺点,研究了中心差分卡尔曼滤波方法(CDKF),提出用中心差分卡尔曼滤波方法来解决视觉导航中两航天器的相对位姿估计问题,并给出了EKF与CDKF的仿真结果.仿真结果表明在相同条件下,CD-KF算法比EKF具有更高的精度和稳定性,该方法能够在航天器视觉相对导航中应用.

Study of Relative Navigation for Spacecraft Based on Central Difference Kalman Filter

In the research of vision-based relative navigation for spacecrafts, the .non-linearity of measurement equation shows great influence on the estimation accuracy of relative position and attitude. First, the drawbacks of using Extended Kalman Filte (EKF) on the linearization of nonlinear model is analyzed; then Center Difference Kalman Filter (CDKF) method is discussed and applied to relative position and attitude estimation of spacecraft, last the simulation results using Extended Kalman Filter (EKF) and Center Difference Kalman Filter (CDKF) are presented in the paper. The results demonstrate that under the same condition, CDKF algorithm out-performed EKF in accuracy therefore can be applied to vision-based navigation of spacecrafts.