Optical measurements such as photometric observations and imaging observations have been widely applied for estimating the shape, surface characteristics, and attitude motion of space objects. Photometric observation-based methods use light curves, the time history of the brightness of a space object, whereas imaging observation-based methods use images captured by the optical telescope and processed with adaptive optics. In Kyushu University, studies on the state estimation of space object with photometric observations have been conducted. In addition, an imaging observation-based method to determine an initial value for photometric observations and its feasibility have been studied. The current study describes a photometric observation-based method and verifies its accuracy by numerical simulations. Furthermore, a state estimation method that exploits both photometric observations and imaging observations is presented. The proposed method also shows the efficiency to apply image identification by convolutional neural network, a kind of machine learning, in imaging observations.
内容記述
形態: カラー図版あり
内容記述(英)
Physical characteristics: Original contains color illustrations