论文标题
贝叶斯的射频干扰方法缓解方法
Bayesian approach to radio frequency interference mitigation
论文作者
论文摘要
在涉及电磁频谱的物理观察的田野中，干扰信号（例如无处不在卫星星座的射频干扰）正在成为一个流行问题。为了解决这个问题，我们提出了一种新颖的数据清洁方法。污染是在可能性层面上同时标记和管理的。它是通过贝叶斯的可能性以贝叶斯的可能性来建模的，该分段可能受到伯努利先前分布的约束。本文中描述的技术只能使用几行代码来实现。
Interfering signals such as Radio Frequency Interference from ubiquitous satellite constellations are becoming an endemic problem in fields involving physical observations of the electromagnetic spectrum. To address this we propose a novel data cleaning methodology. Contamination is simultaneously flagged and managed at the likelihood level. It is modeled in a Bayesian fashion through a piecewise likelihood that is constrained by a Bernoulli prior distribution. The techniques described in this paper can be implemented with just a few lines of code.
