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Unequal a priori probability multiple hypothesis testing in space domain awareness with the space surveillance telescope

机译：空间监视望远镜在空间领域感知中的不等先验概率多重假设检验

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This paper investigates the ability to improve Space Domain Awareness (SDA) by increasing the number of detectable Resident Space Objects (RSOs) from space surveillance sensors. With matched filter based techniques, the expected impulse response, or Point Spread Function (PSF), is compared against the received data. In the situation where the images are spatially undersampled, the modeled PSF may not match the received data if the RSO does not fall in the center of the pixel. This aliasing can be accounted for with a Multiple Hypothesis Test (MHT). Previously, proposed MHTs have implemented a test with an equal a priori prior probability assumption. This paper investigates using an unequal a priori probability MHT. To determine accurate a priori probabilities, three metrics are computed; they are correlation, physical distance, and empirical. Using the calculated a priori probabilities, a new algorithm is developed, and images from the Space Surveillance Telescope (SST) are analyzed. The number of detected objects by both an equal and unequal prior probabilities are compared while keeping the false alarm rate constant. Any additional number of detected objects will help improve SDA capabilities. (C) 2016 Optical Society of America
机译：本文研究了通过增加来自太空监视传感器的可检测驻地空间物体（RSO）的数量来提高空间域感知（SDA）的能力。使用基于匹配滤波器的技术，将预期的脉冲响应或点扩展函数（PSF）与接收到的数据进行比较。在图像在空间上欠采样的情况下，如果RSO不在像素中心，则建模的PSF可能与接收到的数据不匹配。可以使用多重假设检验（MHT）来解决此混叠问题。以前，提出的MHT在先验概率相等的前提下实施了测试。本文研究使用不相等的先验概率MHT。为了确定准确的先验概率，计算了三个度量;它们是相关性，物理距离和经验。使用计算出的先验概率，开发了一种新算法，并对来自太空监视望远镜（SST）的图像进行了分析。比较相等概率和不相等的先验概率检测到的对象数量，同时使误报率保持恒定。检测到的任何其他数量的对象将有助于提高SDA功能。 （C）2016美国眼镜学会

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