軌道上データを用いた膜面宇宙構造物の運動推定における最適観測点の提案

抄録

Membrane structures are highly sensitive to shape deformation, and even minute disturbances in outer space can affect motion, so it is desirable to grasp and control the exact shape in orbit. However, the membrane shape data that can be acquired in orbit is lost due to various factors such as the influence of sunlight, camera placement, angle of view, and sampling rate. So far, the motion has been estimated by estimating the main modes of membrane motion from the missing data and optimizing the mode coefficients in the sense of sparse estimation. However, the weighting coefficient that adjusts the sparseness of the mode coefficient was arbitrarily determined, and it was unclear whether it was the optimum solution. In this research, we propose a motion estimation method using a learning algorithm that determines the optimum weighting coefficient from the obtained data, and consider the results and the validity of the estimation accuracy.