Accurate image reconstruction in radio interferometry
type: CreativeWork
description: This thesis is concerned with accurate imaging from radio interferometry data and with subsequent analysis so as to determine source positions and fluxes in the radio sky. The thesis makes proposals and implementations of new algorithms, which substantially improve the accuracy of image products and the results of source extraction. These improvements in accuracy promise to assist scientific research into astronomical objects and phenomena in radio astronomy. The thesis contains six chapters, beginning with an overview of the imaging process in radio interferometry in Chapter 1. Chapter 2 focuses on improving the accuracy of source extraction, by utilising the Bayesian methodology. The proposed Bayesian method has been implemented in a software package called 'BaSC' which uses the Markov Chain Monte Carlo (MCMC) technique. By design, it works with intermediate radio interferometry image products, such as dirty images, rather than with reconstructed images. BaSC achieves greater precision in source location and better resolving power than mainstream source extraction software such as SExtractor, which works with reconstructed images. This finding confirms that reconstructed images are not a true representation of the radio sky, whereas dirty images already contain full information about the observations. This piece of work has been accepted by Monthly Notices of the Royal Astronomical Society (Hague et al. 2018). Chapter 2 is based on this paper, but has been rewritten and expanded. Based on this conclusion, Chapter 3 seeks to optimise the gridding process so as to make accurate dirty images. Since the Fast Fourier transform (FFT) produces dirty images with a much lower computational cost than the Direct Fourier transform (DFT), a new gridding function is needed which minimises the difference between DFT and FFT dirty images. The 'Least-misfit' gridding function is proposed, so as to minimise the image misfit between the DFT and FFT dirty images, and this is implemen…
abstract: This thesis is concerned with accurate imaging from radio interferometry data and with subsequent analysis so as to determine source positions and fluxes in the radio sky. The thesis makes proposals and implementations of new algorithms, which substantially improve the accuracy of image products and the results of source extraction. These improvements in accuracy promise to assist scientific research into astronomical objects and phenomena in radio astronomy. The thesis contains six chapters, beginning with an overview of the imaging process in radio interferometry in Chapter 1. Chapter 2 focuses on improving the accuracy of source extraction, by utilising the Bayesian methodology. The proposed Bayesian method has been implemented in a software package called 'BaSC' which uses the Markov Chain Monte Carlo (MCMC) technique. By design, it works with intermediate radio interferometry image products, such as dirty images, rather than with reconstructed images. BaSC achieves greater precision in source location and better resolving power than mainstream source extraction software such as SExtractor, which works with reconstructed images. This finding confirms that reconstructed images are not a true representation of the radio sky, whereas dirty images already contain full information about the observations. This piece of work has been accepted by Monthly Notices of the Royal Astronomical Society (Hague et al. 2018). Chapter 2 is based on this paper, but has been rewritten and expanded. Based on this conclusion, Chapter 3 seeks to optimise the gridding process so as to make accurate dirty images. Since the Fast Fourier transform (FFT) produces dirty images with a much lower computational cost than the Direct Fourier transform (DFT), a new gridding function is needed which minimises the difference between DFT and FFT dirty images. The 'Least-misfit' gridding function is proposed, so as to minimise the image misfit between the DFT and FFT dirty images, and this is implemen…
author: Ye, Haoyang
language: en
keywords: radio interferometry, image processing, gridding, degridding, MCMC, Astronomical source extraction, N-Faceting method, wide field imaging, high accuracy imaging, Clustering
license: https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/4525e96e-14f7-45d6-ba51-36ca8c9f45bf/download
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
date published: 2019-05-18
date modified: 2026-07-22T22:24:20Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.39448