论文标题
使用组件和时间分析对无线电干扰进行分类
Categorize Radio Interference using component and temporal analysis
论文作者
论文摘要
射频干扰（RFI）是当今射电天文学家面临的重大挑战。虽然大多数过去的努力都致力于从数据中清理RFI，但我们开发了一种新颖的方法，用于将RFI分类为法医目的。我们提出一个分类器，该分类器根据使用主成分分析（PCA）和傅立叶分析提取的特征将RFI分类为不同的类型。分类器可以在2个sigma高于2 sigma的窄带非周期性RFI，高于3 sigma的窄带周期性RFI和高于5 Sigma的宽带冲动RFI，而模拟中F1得分在0.87至0.91之间。该分类器可用于识别RFI的来源以及清洁RFI污染（尤其是在Pulsar搜索中）。在对分类RFI的长期分析中，我们发现了一种特殊类型的漂移周期性RFI，这对PULSAR搜索有害。我们还发现，当望远镜指向城市时，脉冲RFI的速率提高了。这些结果证明了该分类器作为RFI环境监测射电望远镜的法医工具的潜力。
Radio frequency interference (RFI) is a significant challenge faced by today's radio astronomers. While most past efforts were devoted to cleaning the RFI from the data, we develop a novel method for categorizing and cataloguing RFI for forensic purpose. We present a classifier that categorizes RFI into different types based on features extracted using Principal Component Analysis (PCA) and Fourier analysis. The classifier can identify narrowband non-periodic RFI above 2 sigma, narrowband periodic RFI above 3 sigma, and wideband impulsive RFI above 5 sigma with F1 scores between 0.87 and 0.91 in simulation. This classifier could be used to identify the sources of RFI as well as to clean RFI contamination (particularly in pulsar search). In the long-term analysis of the categorized RFI, we found a special type of drifting periodic RFI that is detrimental to pulsar search. We also found evidences of an increased rate of impulsive RFI when the telescope is pointing toward the cities. These results demonstrate this classifier's potential as a forensic tool for RFI environment monitoring of radio telescopes.
