Baseline-dependent sampling and windowing for radio interferometry: data compression, field-of-interest shaping and outer field suppression
M. Atemkeng, O. Smirnov, C. Tasse, G. Foster, A. Keimpema, Z. Paragi, and J. Jonas

TL;DR
This paper introduces a baseline-dependent sampling and windowing scheme for radio interferometry that improves data compression, shapes the field of interest, and suppresses outer fields, while maintaining decorrelation consistency across baselines.
Contribution
It proposes a novel baseline-dependent sampling method and windowing technique that enable effective data compression and field shaping in radio interferometry without increasing decorrelation.
Findings
Achieves data compression and field-of-interest shaping.
Maintains constant decorrelation across baselines.
Demonstrates effectiveness with MeerKAT and VLBI data.
Abstract
Traditional radio interferometric correlators produce regular-gridded samples of the true -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 -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 -space, which is equivalent in the source domain to "smearing". This work discusses and implements a regular-gridded sampling scheme in the -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…
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