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Bernoulli generalized likelihood ratio test for signal detection from photon counting images
Journal of Astronomical Telescopes, Instruments, and Systems ( IF 2.3 ) Pub Date : 2021-06-01 , DOI: 10.1117/1.jatis.7.2.028006
Mengya (Mia) Hu 1 , He Sun 2 , Anthony Harness 1 , N. Jeremy Kasdin 3
Affiliation  

Because exoplanets are extremely dim, an electron multiplying charge-coupled device operating in photon counting (PC) mode is necessary to reduce the detector noise level and enable their detection. Typically, PC images are added together as a co-added image before processing. We present a signal detection and estimation technique that works directly with individual PC images. The method is based on the generalized likelihood ratio test (GLRT) and uses a Bernoulli distribution between PC images. The Bernoulli distribution is derived from a stochastic model for the detector, which accurately represents its noise characteristics. We show that our technique outperforms a previously used GLRT method that relies on co-added images under a Gaussian noise assumption and two detection algorithms based on signal-to-noise ratio. Furthermore, our method provides the maximum likelihood estimate of exoplanet intensity and background intensity while doing detection. It can be applied online, so it is possible to stop observations once a specified threshold is reached, providing confidence for the existence (or absence) of planets. As a result, the observation time is efficiently used. In addition to the observation time, the analysis of detection performance introduced in the paper also gives quantitative guidance on the choice of imaging parameters, such as the threshold. Lastly, though our work focuses on the example of detecting point source, the framework is widely applicable.

中文翻译:

用于从光子计数图像中检测信号的伯努利广义似然比检验

由于系外行星非常暗淡,因此需要在光子计数 (PC) 模式下运行的电子倍增电荷耦合器件,以降低探测器噪声水平并使其能够被探测到。通常,PC 图像在处理前会作为共同添加图像添加在一起。我们提出了一种信号检测和估计技术,可以直接处理单个 PC 图像。该方法基于广义似然比检验 (GLRT),并使用 PC 图像之间的伯努利分布。伯努利分布源自检测器的随机模型,可准确表示其噪声特性。我们表明,我们的技术优于以前使用的 GLRT 方法,该方法依赖于高斯噪声假设下的共同添加图像和基于信噪比的两种检测算法。此外,我们的方法在进行检测时提供了系外行星强度和背景强度的最大似然估计。它可以在线应用,因此一旦达到指定的阈值就可以停止观测,从而为行星的存在(或不存在)提供信心。结果,有效地利用了观察时间。除了观察时间外,论文中介绍的检测性能分析也对阈值等成像参数的选择给出了定量指导。最后,虽然我们的工作集中在检测点源的例子上,但该框架是广泛适用的。为行星的存在(或不存在)提供信心。结果,有效地利用了观察时间。除了观察时间之外,论文中介绍的检测性能分析也对阈值等成像参数的选择给出了定量指导。最后,虽然我们的工作集中在检测点源的例子上,但该框架是广泛适用的。为行星的存在(或不存在)提供信心。结果,有效地利用了观察时间。除了观察时间之外,论文中介绍的检测性能分析也对阈值等成像参数的选择给出了定量指导。最后,虽然我们的工作集中在检测点源的例子上,但该框架是广泛适用的。
更新日期:2021-06-17
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