A Modern Space Situational Awareness System

T. Jackson, H. Holland, G. Tuparev, M. Steinbatz, W. Promper, D. Weinzinger
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Abstract

We, Tuparev AstroTech in partnership with Astro Syteme Austria, present a next-generation Space Situational Awareness (SSA) system currently being created for the tracking and characterisation of satellites and space debris in the age of big-data astronomy. Our SSA system will be based on the image processing of white-light images to detect streaks produced by satellites and space debris. These images will be obtained by a network of 20-30 custom and in-house built SSA observatory stations, which will be made operational worldwide over the coming decade. The system will use machine learning algorithms to choose the optimal part of the sky to observe at any given moment, analyse the incoming data on-site and in real-time, and deliver various standardised data packages and science-quality images to be stored on a bespoke central archive capable of storing petabytes of data. With this system, we aim to cover a greater geographical and celestial area than any previous SSA system, to create a scalable system that is both fast and efficient, and to enable access to orders of magnitude more storage capacity and information than any other system currently available, commercial or governmental.
现代空间态势感知系统
我们,Tuparev AstroTech与Astro system Austria合作,推出了下一代空间态势感知(SSA)系统,该系统目前正在开发中,用于大数据天文学时代卫星和空间碎片的跟踪和表征。我们的SSA系统将基于对白光图像的图像处理,以检测卫星和空间碎片产生的条纹。这些图像将由一个由20-30个定制和内部建造的SSA观测站组成的网络获得,这些观测站将在未来十年内在全球范围内投入使用。该系统将使用机器学习算法来选择在任何给定时刻观测天空的最佳部分,现场实时分析传入的数据,并提供各种标准化数据包和科学质量的图像,存储在能够存储pb数据的定制中央存档中。有了这个系统,我们的目标是覆盖比任何以前的SSA系统更大的地理和天体区域,创建一个可扩展的系统,既快速又高效,并且能够访问比任何其他现有系统(商业或政府)更多的存储容量和信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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