Improved radio astronomical imaging based on sparse reconstruction

Shuimei Zhang; Yujie Gu; William C. Barott; Yimin D. Zhang

doi:10.1117/12.2307643

14 May 2018 Improved radio astronomical imaging based on sparse reconstruction

Shuimei Zhang, Yujie Gu, William C. Barott, Yimin D. Zhang

Proceedings Volume 10658, Compressive Sensing VII: From Diverse Modalities to Big Data Analytics; 106580O (2018) https://doi.org/10.1117/12.2307643
Event: SPIE Commercial + Scientific Sensing and Imaging, 2018, Orlando, FL, United States

Abstract

Modern radio telescopes commonly use antenna arrays, and high-resolution imaging techniques exploiting radio astronomical signals collected at these antenna arrays play a critical role to achieve their missions. Beamforming techniques have been developed in radio astronomy to generate dirty images with limited image resolutions for many years. Because the manifold of a radio telescope array varies over time due to the Earth rotation, beamformers are separately designed and implemented at each time epoch, and the resulting images are averaged to form enhanced dirty images. Considering the fact that astronomical scenes are typically sparse, we present a new method through sparse reconstruction to obtain clean astronomical images. Sparse reconstruction methods that fuse the measured data observed at multiple time epochs are examined and compared. Unlike beamforming techniques which require an additional deconvolution procedure for clean image formation, the proposed technique provides clean astronomical images with accurate estimation of the source position and a high dynamic range.

Citation Download Citation

Shuimei Zhang, Yujie Gu, William C. Barott, and Yimin D. Zhang "Improved radio astronomical imaging based on sparse reconstruction", Proc. SPIE 10658, Compressive Sensing VII: From Diverse Modalities to Big Data Analytics, 106580O (14 May 2018); https://doi.org/10.1117/12.2307643

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