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FireOPAL: Technical Performance and First Results

机译:灯头:技术性能和第一个结果

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摘要

FireOPAL is a distributed network of standalone, fixed mount optical sensors that is designed to monitor a large number of RSOs at high cadence. Here we describe the technical performance and first results of our prototype network. For each 5 second image, we find that FireOPAL measures apparent angular coordinates with an accuracy of a few arcseconds. The system measures absolute time within milliseconds, absolute flux to within 10%, and detects point sources with visual magnitude of around 16 or brighter. Each unit has sufficient computational resources to completely process an image onboard within seconds, reports measurements to a central server in near real time, which are then used for orbit determination and catalogue maintenance. The data from our prototype network across Australia as used to calculate accurate orbits for hundreds of objects per clear night. When orbits for both LEO and GEO objects are propagated forward more than one day, the predictions match the observations to better than one pixel. Over the past few months, the system has recorded more than one million light curves of satellites which are used to deduce properties such as size, tumbling, composition, pattern of life, etc. Finally, we report on the capture rate of objects of different sizes and in different orbital regimes, and discuss ongoing plans to improve the performance of the network.
机译:丝孔是独立的固定安装光学传感器的分布式网络,旨在监控大量的RSOS。在这里,我们描述了我们原型网络的技术性能和第一个结果。对于每个5秒的图像,我们发现镜头测量明显的角度坐标,精度为少数弧形。该系统在毫秒内测量绝对时间,绝对磁通量在10%以内,并检测视觉距离,视觉幅度约为16或更亮。每个单元都有足够的计算资源来在几秒钟内完全处理图像,在近实时向中央服务器报告测量,然后用于轨道确定和目录维护。来自澳大利亚的原型网络的数据用于计算每晴天数百个对象的准确轨道。当LEO和GEO对象的轨道转发超过一天,预测匹配比一个像素更好地匹配。在过去的几个月里,系统已经录得超过一百万次卫星光线曲线,用于推导尺寸,翻滚,成分,生命模式等的性质。最后,我们报告了不同的物体的捕获率大小和不同的轨道制度,并讨论正在进行的计划,以提高网络性能。

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