第6回スペースデブリワークショップ (2014年12月17-19日. 宇宙航空研究開発機構調布航空宇宙センター(JAXA)(CAC)), 調布市, 東京

6th Space Debris Workshop (December 17-19, 2014. Chofu Aerospace Center, Japan Aerospace Exploration Agency (JAXA)(CAC)), Chofu, Tokyo, Japan

地球周辺の宇宙空間がより過密化し、多国間の競争が激化する中、宇宙状況認識 (SSA)は宇宙を利用するすべての国にとって重要な技能であり続けると考えられる。しかし、観測が希薄であるがゆえ、同定仮定を初期軌道決定の的確さによって判定する従来の方法は、しばしば失敗することが確認されてきた。Direct Bayesian admissible region 手法は、先験的な状態を必要としない、観測同定・初期軌道決定の方法である。経過時間の短い光学観測の弧を元に、観測された物体までの、もっとも可能性の高い距離・距離の変化率の値を含んだ、コンパクト空間を定義することが可能である。Admissible region とは、このコンパクト空間上に定義された連続一様分布である。本研究では、上の手法をベルン大学から提供された実データを元に検証し、新たに2つの物体を検出することに成功した。

As space becomes ever more congested, contested, and competitive, space situational awareness (SSA) capabilities will continue to be important for all spacefaring nations. In almost all SSA related tasks, the first step is to track, detect, and identify active satellites, space debris, and other resident space objects (RSOs). Conventional approaches of testing association hypotheses based upon IOD quality, however, can often fail since sparse measurements lead to poor, if not divergent, estimates. The direct Bayesian admissible region approach is an a priori state free measurement association and IOD technique. Given a short-arc series of optical data, or a tracklet, a compact region in the range / range-rate space is defined based on a set of physical constraints such that all likely and relevant orbits are contained within it. The admissible region (AR) is a uniform probability density function (pdf) whose support is this compact region. Multiple ARs may be propagated to a common epoch and an a posteriori pdf directly computed based on Bayes' rule. The proposed approach has been applied to tracklets from a survey of geostationary (GEO) objects taken at the Zimmerwald Observatory of the Astronomical Institute of the University of Bern. Processing a set of 212 tracklets resulted in 20 objects detected; 2 of which are newly detected by the proposed method. Furthermore, it was noted that the direct Bayesian approach would allow one to reevaluate future observational strategies in order to minimize false positive / negative association solutions. As such, this work ultimately aims to "close the loop" on the short-arc optical track association problem by enhancing the survey strategy based on the association results and vice versa.

形態: カラー図版あり

Physical characteristics: Original contains color illustrations

資料番号: AA1530025041

レポート番号: JAXA-SP-14-013