一种基于AOFlagger 3的干扰检测策略
An interference detection strategy for Apertif based on AOFlagger 3
摘要：
上下文1.1.5 GHz是Westerbork综合射电望远镜的一个多波束接收器系统，与各种无线电服务重叠，导致天文信号受到射频干扰的污染。目标。我们分析的方法，以减轻反相干扰，并设计了一个自动化的检测程序，其成像模式。使用这种方法，我们提出了长期RFI检测结果超过300个观测。方法.我们的方法是基于AOFlagger检测方法。我们引入了几个新功能，包括在SumThreshold和尺度不变秩运算符步骤中处理无效数据范围（例如由阴影引起）的方法;预校准带通校准;自相关标记;和HI标记避免。这些方法在一个新的框架中实现，该框架使用Lua语言进行脚本编写，这是AOFlagger版本3中的新内容。结果我们的方法完全自动地去除RFI，并且对于这些数据的进一步校准和（连续）成像是足够鲁棒和有效的。对304个观测值的分析显示，由于RFI的大范围传播，平均有11.1%的数据丢失。我们观察到14.6%的自相关RFI。在计算方面，AOFlagger在单个计算节点上实现了370 MB/s的吞吐量。与已发表的机器学习结果相比，该方法快了一到两个数量级。
英文摘要：
Context. Apertif is a multi-beam receiver system for the Westerbork Synthesis Radio Telescope that operates at 1.1-1.5 GHz, which overlaps with various radio services, resulting in contamination of astronomical signals with radio-frequency interference (RFI). Aims. We analyze approaches to mitigate Apertif interference and design an automated detection procedure for its imaging mode. Using this approach, we present long-term RFI detection results of over 300 Apertif observations. Methods. Our approach is based on the AOFlagger detection approach. We introduce several new features, including ways to deal with ranges of invalid data (e.g. caused by shadowing) in both the SumThreshold and scale-invariant rank operator steps; pre-calibration bandpass calibration; auto-correlation flagging; and HI flagging avoidance. These methods are implemented in a new framework that uses the Lua language for scripting, which is new in AOFlagger version 3. Results. Our approach removes RFI fully automatically, and is robust and effective enough for further calibration and (continuum) imaging of these data. Analysis of 304 observations show an average of 11.1% of lost data due to RFI with a large spread. We observe 14.6% RFI in auto-correlations. Computationally, AOFlagger achieves a throughput of 370 MB/s on a single computing node. Compared to published machine learning results, the method is one to two orders of magnitude faster.
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