LAUSR

Abstract This paper proposes an autonomous image-based navigation method for estimating the target-relative position of a spacecraft for distant small body exploration. The main focus is position estimation at high altitude where the outlines of a target body can be seen in images. The asteroid explorer Hayabusa2 touched down on the asteroid Ryugu with pin-point accuracy in February 2019. For this mission, the asteroid-relative position was estimated by ground operators from 20 km to 50 m above the surface of Ryugu. For the exploration of small bodies farther than the asteroid main belt, the delay of communication with Earth is unacceptably large for feedback guidance. This situation becomes worse for larger bodies because the time constant of the dynamics becomes smaller. Therefore, real-time autonomous navigation is required for distant small body exploration even at high altitude. To accomplish high-accuracy and real-time autonomous navigation, an autonomous position estimation method based on terrain-relative navigation (TRN) that estimates deviation by comparing nominal terrain information and actual terrain information is proposed. In addition to TRN, the vector code correlation (VCC) algorithm is used for the luminance comparison of terrain information. This algorithm is a type of correlation calculation method for template matching that finds the maximum correlated region in images. With the VCC algorithm, correlation can be calculated in real time via XOR operations suitable for FPGA. The estimation accuracy and processing time of the proposed method were evaluated with a comparison to those of other methods. The results show that a high estimation accuracy, similar to the image resolution, was accomplished in real time. Finally, an evaluation using flight data from Hayabusa2 shows that the estimation accuracy and processing time of the proposed method are suitable for a real mission environment. The proposed method will be a key technology for distant small body exploration.