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Improving space domain awareness through unequal-cost multiple hypothesis testing in the space surveillance telescope

机译:通过在空间监视望远镜中进行的不等成本的多重假设检验来提高空间领域的意识

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This paper investigates algorithms to improve the detection of space objects with the space surveillance telescope (SST) system. These space objects include natural objects such as asteroids and artificial satellites in Earth orbit. Using a proposed multiple hypothesis test (MHT), the detection performance is compared to the currently used algorithm as well as a matched filter and an equal-cost MHT algorithm. To compare these algorithms, a data set collected by the SST of a geosynchronous Earth orbit satellite, ANIK-F1 entering the Earth's eclipse, is utilized. It is found that an unequal-cost MHT gives increased performance over a point detector, a matched filter, and equal-cost MHT over a large range of potential intensities. Results are presented as probability of detection and receiver operating characteristic curves. In addition, the performance of the algorithm as a function of number of hypotheses used is investigated. (C) 2015 Optical Society of America
机译:本文研究了利用空间监视望远镜(SST)系统改善空间物体检测的算法。这些空间物体包括自然物体,例如小行星和地球轨道上的人造卫星。使用提出的多重假设检验(MHT),将检测性能与当前使用的算法以及匹配滤波器和等价MHT算法进行比较。为了比较这些算法,利用了由地球同步地球轨道卫星ANIK-F1的SST收集的数据集,该数据集进入了日食。发现不等成本的MHT在点检测器,匹配滤波器和较大成本的潜在强度范围内的等价MHT上提供了更高的性能。结果表示为检测概率和接收器工作特性曲线。另外,研究了算法的性能与所使用的假设数量的关系。 (C)2015年美国眼镜学会

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