Hyper-spectral Compressive Radio-interferometric Imaging in the SKA era

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"This is a PhD research project in Electrical Engineering.With the advent of the next-generation radio-interferometric telescopes like the Square Kilometre Array, novel signal processing methods are needed to provide the expected imaging resolution and sensitivity from extreme amounts of hyper-spectral data. In this context, the idea is to propose a convex optimisation problem for hyper-spectral data reconstruction and analyse the possible regularisation priors. Posing the problem as a convex optimisation task based on sparsity priors as a regulariser was shown superior to the conventional radio-interferometric imaging techniques like CLEAN. However, extending these methods is essential to process large-scale data. Efficient and fast solvers for the ill-posed inverse problem related to the image reconstruction need also to be tailored. They should employ parallel and distributed computations to achieve scalability, in terms of memory and computational requirements."