Hardy Tyler, Cain Stephen, Blake Travis
Appl Opt. 2016 May 20;55(15):4036-46. doi: 10.1364/AO.55.004036.
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.
本文研究了通过增加空间监视传感器可探测到的在轨空间物体（RSO）数量来提高空间域感知（SDA）能力的方法。利用基于匹配滤波器的技术，将预期的脉冲响应或点扩散函数（PSF）与接收到的数据进行比较。在图像空间欠采样的情况下，如果RSO不在像素中心，建模的PSF可能与接收到的数据不匹配。这种混叠可以通过多重假设检验（MHT）来解决。以前提出的MHT采用了具有相等先验概率假设的检验。本文研究使用不相等先验概率的MHT。为了确定准确的先验概率，计算了三个指标；它们是相关性、物理距离和经验值。利用计算出的先验概率，开发了一种新算法，并对空间监视望远镜（SST）的图像进行了分析。在保持误报率不变的情况下，比较了相等和不相等先验概率下检测到的物体数量。任何额外检测到的物体数量都将有助于提高SDA能力。
