无线电干涉测量的基线相关采样和加窗：数据压缩、感兴趣场整形和外场抑制
Baseline-dependent sampling and windowing for radio interferometry: data compression, field-of-interest shaping and outer field suppression
摘要：
传统的无线电干涉测量仪通过在恒定的离散时间-频率间隔上对信号进行平均来产生真实$uv$分布的规则网格样本。然后，这种规则采样和平均转换为$uv$空间中的不规则网格化样本，并导致幅度和相位相干性的基线长度相关损失，这取决于与图像相位中心的距离。该效应通常被称为$uv$空间中的“去相关”，其在源域中等同于“拖尾”。这项工作讨论并实现了一个规则的网格采样计划，在$uv$空间（基线依赖采样）和窗口，允许数据压缩，字段的兴趣整形和源抑制。基线依赖采样要求时频空间中的不规则网格采样，即时频间隔变得依赖于基线。分析模型和模拟表明，去相关保持恒定的所有基线时，应用基线依赖的采样和窗口。使用MeerKAT望远镜和欧洲甚长基线干涉测量网络的模拟表明，数据压缩，感兴趣的领域成形和外部感兴趣的领域抑制。
英文摘要：
Traditional radio interferometric correlators produce regular-gridded samples of the true $uv$-distribution by averaging the signal over constant, discrete time-frequency intervals. This regular sampling and averaging then translate to be irregular-gridded samples in the $uv$-space, and results in a baseline-length-dependent loss of amplitude and phase coherence, which is dependent on the distance from the image phase centre. The effect is often referred to as "decorrelation" in the $uv$-space, which is equivalent in the source domain to "smearing". This work discusses and implements a regular-gridded sampling scheme in the $uv$-space (baseline-dependent sampling) and windowing that allow for data compression, field-of-interest shaping and source suppression. The baseline-dependent sampling requires irregular-gridded sampling in the time-frequency space i.e. the time-frequency interval becomes baseline-dependent. Analytic models and simulations are used to show that decorrelation remains constant across all the baselines when applying baseline-dependent sampling and windowing. Simulations using MeerKAT telescope and the European Very Long Baseline Interferometry Network show that both data compression, field-of-interest shaping and outer field-of-interest suppression are achieved.
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