日本地球惑星科学連合2018年大会

講演情報

[EE] ポスター発表

セッション記号 P (宇宙惑星科学) » P-PS 惑星科学

[P-PS03] 太陽系小天体研究:現状の理解と将来の展望

2018年5月23日(水) 10:45 〜 12:15 ポスター会場 (幕張メッセ国際展示場 7ホール)

コンビーナ:石黒 正晃(ソウル大学物理天文学科)、中本 泰史(東京工業大学)、荒川 政彦(神戸大学大学院理学研究科、共同)、安部 正真(宇宙航空研究開発機構宇宙科学研究所)

[PPS03-P11] はやぶさ2/LIDAR測距データを用いた着陸点選定のための探査機軌道改良

*松本 晃治1野田 寛大1平田 成2山本 圭香1千秋 博紀3樋口 有理可1川村 太一1並木 則行1渡邊 誠一郎4石原 吉明5田中 智5山口 智宏5三浦 昭5山本 幸生5 (1.国立天文台RISE月惑星探査検討室、2.会津大学、3.千葉工業大学惑星探査研究センター、4.名古屋大学、5.宇宙航空研究開発機構)

キーワード:はやぶさ2、レーザ高度計、軌道補正

Hayabusa2 spacecraft will arrive at the target C-type asteroid Ryugu around June 2018. Hayabusa2 will make a “touchdown” to sample materials on the asteroid surface. Based on near-global observations which will be made soon after arrival by remote sensing instruments, we have to evaluate, in a timely manner, scientific value and touchdown safety to select and rank possible landing sites. Since this procedure is time critical, landing site selection (LSS) training was organized and conducted in 2017. In the training, simulated observations are generated based on a high-resolution model of a hypothetical asteroid (called as Ryugoid) as well as proximity spacecraft operation plan. Here we use the simulated LIDAR range data and a Ryugoid shape model reproduced from the simulated optical navigation camera images, in order to show the possibility to improve the spacecraft trajectory relative to the asteroid.

Given the initial (or erroneous) spacecraft trajectory with respect to the asteroid, the spacecraft attitude information, the observed LIDAR ranges, and the shape model together with asteroid spin information (orientation and period), one can calculate LIDAR footprint positions in asteroid-fixed frame. At the initial stage of the proximity operation, the trajectory errors can be in the order of several tens of meters or sometimes more than a hundred meters, and then considerable deviations will be observed between the calculated LIDAR footprints and the shape model. By assuming that these deviations are mainly due to the trajectory error, orbit correction can be obtained from the residual time series. One simple way is to rotate the residual vectors from Ryugoid-fixed frame to J2000 frame and fit quadratic functions for each of X, Y, Z components of the time series. In the LSS training, this idea worked to some extent, and we were able to quickly provide the improved trajectory to LSS analysis team. In the training, however, point-wise LIDAR footprints as well as a perfect pointing of the LIDAR (zero alignment error) are assumed. We will report how these idealizations affect the results.