Vision／IMU based multi-rate filtering for spacecraft relative navigation using measurement correction

Abstract:

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.