Compressive Imaging in Radio Interferometry

“无线电干涉测量中的压缩成像”（CIRI）项目旨在通过下一代射电望远镜为干涉成像带来新的进展，以及通用压缩成像的理论和算法发展。无线电干涉测量法（RI）允许以其他难以获得的角度分辨率和灵敏度观测天空，为天体物理学和宇宙学提供独特的信息。新的望远镜正在设计中，例如平方公里阵列（SKA），其科学目标从天体生物学和强场重力，到探索宇宙早期恒星形成时的早期时代。这些仪器的目标是将分辨率和灵敏度提高几个数量级。在这种情况下，他们将不得不处理极其庞大的数据集。因此，相关的成像技术确实需要在未来几年内重新发明。压缩抽样（CS）理论的出现代表了抽样理论的一个重大发展。研究表明，通过适当的迭代算法，可以从亚奈奎斯特采样中恢复具有稀疏表示的信号。CIRI将建立在CS的理论和算法的通用性，并利用新的先进的稀疏性和采样概念来定义，从采集到重建，超高分辨率宽带RI成像和校准技术的下一代CS技术。新技术和相关的快速算法能够处理多核计算架构上的超大数据集，将在模拟和真实数据上进行验证。天文成像不仅是一个目标，而且是触发信号处理新发展的必要手段。CIRI确实旨在为压缩成像提供重大进展，从而加强CS革命，该革命在科学和技术领域，特别是在生物医学成像领域得到广泛应用。因此，CIRI有望通过开发新的成像技术来支持即将到来的天文学挑战，并通过提供新型压缩成像算法来影响科学，经济和社会，这些算法可以转移到许多应用中，从生物医学成像开始。

The project "Compressive Imaging in Radio Interferometry" (CIRI) aims to bring new advances for interferometric imaging with next-generation radio telescopes, together with theoretical and algorithmic evolutions in generic compressive imaging.Radio Interferometry (RI) allows observations of the sky at otherwise inaccessible angular resolutions and sensitivities, providing unique information for astrophysics and cosmology. New telescopes are being designed, such as the Square Kilometer Array (SKA), whose science goals range from astrobiology and strong field gravity, to the probe of early epochs in the Universe when the first stars formed. These instruments will target orders of magnitudes of improvement in resolution and sensitivity. In this context, they will have to cope with extremely large data sets. Associated imaging techniques thus literally need to be re-invented over the next few years.The emerging theory of compressive sampling (CS) represents a significant evolution in sampling theory. It demonstrates that signals with sparse representations may be recovered from sub-Nyquist sampling through adequate iterative algorithms. CIRI will build on the theoretical and algorithmic versatility of CS and leverage new advanced sparsity and sampling concepts to define, from acquisition to reconstruction, next-generation CS techniques for ultra-high resolution wide-band RI imaging and calibration techniques. The new techniques, and the associated fast algorithms capable of handling extremely large data sets on multi-core computing architectures, will be validated on simulated and real data.Astronomical imaging is not only a target, but also an essential means to trigger novel generic developments in signal processing. CIRI indeed aims to provide significant advances for compressive imaging thereby reinforcing the CS revolution, which finds applications all over science and technology, in particular in biomedical imaging.CIRI is thus expected to impact science, economy, and society by developing new imaging technologies essential to support forthcoming challenges in astronomy, and by delivering a new class of compressive imaging algorithms that can in turn be transferred to many applications, starting with biomedical imaging.