自主机载近地物体探测

P. Rajan, P. Burlina, M. Chen, D. Edell, B. Jedynak, N. Mehta, Ayushi Sinha, Gregory Hager
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引用次数: 1

摘要

迄今为止,大多数大型小行星群的发现都是由地面望远镜完成的。据推测,大多数直径小于100米的较小的近地天体(NEOs)尚未被发现,它们的撞击可以造成巨大的城市规模的破坏。考虑到它们的大小和/或相对于太阳的位置,许多小行星无法用地球上的望远镜探测到。我们正在研究在航天器上部署小行星探测算法的可行性,从而将费用和下行大量图像的需求降至最低。拥有自主的机载图像分析算法,可以将航天器部署在大约0.7 AU的日心或地球-太阳L1/L2晕轨道上,从而消除了使用地球望远镜探测小行星的一些挑战。我们描述了一种针对机载小行星探测而开发的图像分析算法管道,并表明其性能与在飞行合格硬件上的部署一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autonomous on-board Near Earth Object detection
Most large asteroid population discovery has been accomplished to date by Earth-based telescopes. It is speculated that most of the smaller Near Earth Objects (NEOs) that are less than 100 meters in diameter, whose impact can create substantial city-size damage, have not yet been discovered. Many asteroids cannot be detected with an Earth-based telescope given their size and/or their location with respect to the Sun. We are investigating the feasibility of deploying asteroid detection algorithms on-board a spacecraft, thereby minimizing the expense and need to downlink large collection of images. Having autonomous on-board image analysis algorithms enables the deployment of a spacecraft at approximately 0.7 AU heliocentric or Earth-Sun L1/L2 halo orbits, removing some of the challenges associated with detecting asteroids with Earth-based telescopes. We describe an image analysis algorithmic pipeline developed and targeted for on-board asteroid detection and show that its performance is consistent with deployment on flight-qualified hardware.
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