Prediction of terrain occlusion in Chang'e-4 mission

Abstract

This paper proposes a precise terrain occlusion prediction algorithm based on stereo image sequences from the China's Chang'e-4 Yutu-2 rover’ visual system, which includes an on orbit stereo camera calibration method and a camera pose estimation method. The main advantage of the proposed algorithm is that the above two methods consider the problem that the coefficient matrix and observation vector should also be considered with regard to the error during optimization. In this case, the total least squares solution is applied instead of the ordinary least squares solution. Experimental results show that the proposed algorithm has higher precision (with average differences in the altitude angles and azimuthal angles of −0.37 degrees and −0.29 degrees) and application stability than the ordinary least squares method. The proposed algorithm has been successfully used in Chang'e-4 mission operations.