中文摘要：

针对具有单目视觉和惯导组件（IMU）的航天器相对导航问题,研究了以量测信息为修正手段的异速滤波算法.异速滤波也就是多速率卡尔曼滤波器,其中滤波过程被分解为量测更新和时间更新,根据实际情况选取滤波器周期,一般可选取频率较快的系统采样周期作为组合导航系统的滤波周期,根据是否有慢速信息决定在滤波时刻进行时间更新或者量测更新.为增强滤波器对观测信息的适应能力,设计利用量测信息对滤波量测噪声阵和状态估计误差协方差阵进行后验修正.理论分析和数学仿真均表明,基于量测修正的多速率卡尔曼算法能够提高滤波器的数据更新频率,同时改善滤波器的性能,提高导航系统的冗余度.

英文摘要：

This paper proposed a measurement correction based multi-rate Kalman integrated method for the problem of spacecraft relative navigation using monocular vision and IMU. This algorithm divides the entire filtering process into two separate stages： measurement updating stage and time updating one. The sampling rate of the IMU as a fast one is generally chosen as the filtering period of the integrated naviga-tion system. Moreover, in each sampling period, the filter determinates whether to update the measure-ments of the vision system with slow sampling rate, andthe measurements are also used to modify the covariance matrix of measurement noise and state estimation error. Both theoretical analysis and mathematical simulations indicate that multi-rate Kalman filtering algorithm using measurement correction can increase the data output rate and improve filter performance as well as the redundancy of the relative navigation system.