Journal
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 471, Issue 4, Pages 4300-4313Publisher
OXFORD UNIV PRESS
DOI: 10.1093/mnras/stx1775
Keywords
techniques: image processing; techniques: interferometric
Categories
Funding
- UK Engineering and Physical Sciences Research Council (EPSRC) [EP/M008843/1, EP/M011089/1]
- UK Science and Technology Facilities Council (STFC) [ST/M00113X/1]
- Australian Research Council Centre of Excellence for All-Sky Astrophysics (CAASTRO) [CE11E0090]
- gSTAR national facility at Swinburne University of Technology - Swinburne
- Australian Government's Education Investment Fund
- ARC Discovery Early Career Researcher Award [DE170100356]
- EPSRC [EP/M008843/1, EP/M008886/1, EP/M011852/1, EP/M011089/1] Funding Source: UKRI
- STFC [ST/M00113X/1, ST/N000811/1] Funding Source: UKRI
- Australian Research Council [DE170100356] Funding Source: Australian Research Council
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Modern radio telescopes, such as the Square Kilometre Array, will probe the radio sky over large fields of view, which results in large w-modulations of the sky image. This effect complicates the relationship between the measured visibilities and the image under scrutiny. In algorithmic terms, it gives rise to massive memory and computational time requirements. Yet, it can be a blessing in terms of reconstruction quality of the sky image. In recent years, several works have shown that large w-modulations promote the spread spectrum effect. Within the compressive sensing framework, this effect increases the incoherence between the sensing basis and the sparsity basis of the signal to be recovered, leading to better estimation of the sky image. In this article, we revisit the w-projection approach using convex optimization in realistic settings, where the measurement operator couples the w-terms in Fourier and the de-gridding kernels. We provide sparse, thus fast, models of the Fourier part of the measurement operator through adaptive sparsification procedures. Consequently, memory requirements and computational cost are significantly alleviated at the expense of introducing errors on the radio interferometric data model. We present a first investigation of the impact of the sparse variants of the measurement operator on the image reconstruction quality. We finally analyse the interesting superresolution potential associated with the spread spectrum effect of the w-modulation, and showcase it through simulations. Our C++ code is available online on GitHub.
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