Volume 640, August 2020
|Number of page(s)||10|
|Section||Numerical methods and codes|
|Published online||14 August 2020|
Adaptive-scale wide-field reconstruction for radio synthesis imaging
College of Big Data and Information Engineering, Guizhou University, Guiyang, 550025
2 Computer School of China West Normal University, Nanchong, Sichuan, 637002 PR China
3 Xinjiang Astronomical Observatory, Chinese Academy of Sciences, Urumqi, 830011 PR China
4 Key Laboratory of Radio Astronomy, Chinese Academy of Sciences, Urumqi, 830011 PR China
Accepted: 2 June 2020
Sky curvature and non-coplanar effects, caused by low frequencies, long baselines, or small apertures in wide field-of-view instruments such as the Square Kilometre Array (SKA), significantly limit the imaging performance of an interferometric array. High dynamic range imaging essentially requires both an excellent sky model and the correction of imaging factors such as non-coplanar effects. New CLEAN deconvolution with adaptive-scale modeling already has the ability to construct significantly better narrow-band sky models. However, the application of wide-field observations based on modern arrays has not yet been jointly explored. We present a new wide-field imager that can model the sky on an adaptive-scale basis, and the sky curvature and the effects of non-coplanar observations with the w-projection method. The degradation caused by the dirty beam due to incomplete spatial frequency sampling is eliminated during sky model construction by our new method, while the w-projection mainly removes distortion of sources far from the image phase center. Applying our imager to simulated SKA data and the real observation data of the Karl G. Jansky Very Large Array (an SKA pathfinder) suggested that our imager can handle the effects of wide-field observations well and can reconstruct more accurate images. This provides a route for high dynamic range imaging of SKA wide-field observations, which is an important step forward in the development of the SKA imaging pipeline.
Key words: methods: data analysis / techniques: image processing
© ESO 2020
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