Robust Centroid Estimation Method with the Rough and Refined Estimation for Interplanetary Optical Navigation

Abstract

As the interest in probing deep space increases, it is necessary to enhance the autonomous navigation capabilities of the spacecraft. Since traditional navigation methods rely on ground-based radiometric tracking, the vehicle has a significant communication delay resulting in no ability to handle unexpected situations on time. Image-based optical navigation allows interplanetary spacecraft to determine their orbits autonomously. This paper explores how to accurately extract optical observations from the original images to perform autonomous navigation. First, we introduce a simple and efficient idea to locate valuable contours of the celestial body based on gradient variations. Then, we establish a rough estimation with RANSAC to remove the outliers around the edges. Next, we propose a refined estimation based on the hybrid genetic algorithm to precisely estimate the navigation observations. Lastly, numerous experiments have confirmed that our method achieves outstanding accuracy and robustness.