Adaptive Weighting in Radio Interferometric Imaging

TL;DR

This paper introduces a new weighting scheme for radio interferometric imaging that enhances sensitivity and reduces PSF sidelobe variation, improving ultra deep imaging quality.

Contribution

The paper proposes a novel weighting method tailored for ultra deep radio imaging, optimizing sensitivity and PSF sidelobe stability across frequencies and epochs.

Findings

Simulation results show improved sensitivity.

Reduced PSF sidelobe variation.

Outperforms existing weighting schemes.

Abstract

Radio interferometers observe the Fourier space of the sky, at locations determined by the array geometry. Before a real space image is constructed by a Fourier transform, the data is weighted to improve the quality of reconstruction. Two criteria for calculation of weights are maximizing sensitivity and minimizing point spread function (PSF) sidelobe levels. In this paper, we propose a novel weighting scheme suitable for ultra deep imaging experiments. The proposed weighting scheme is used to maximize sensitivity while minimizing PSF sidelobe variation across frequency and multiple epochs. We give simulation results that show the superiority of the proposed scheme compared with commonly used weighting schemes in achieving these objectives.