A Sparse Reconstruction Algorithm for Multi-Frequency Radio Images
A Sparse Reconstruction Algorithm for Multi-Frequency Radio Images
复制标题
一种多频无线电图像稀疏重建算法
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
M. Magnor
中科院分区：
文献类型：
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作者：
S. Wenger;Urvasshi Rau;S. Bhatnagar;M. Magnor
在无线电干涉测量中，阵列中的每对天线在天空图像的傅立叶域中定义一个采样点。通过组合来自不同波长的信息，可以提高样品覆盖率，从而提高重建质量。然而，在不同波长的图像可能是显着不同的，这一事实必须考虑到重建多频图像时。在本文中，我们提出了一种新的重建算法的基础上的假设，频谱是连续的。与以前的工作相比，我们允许稀疏偏离这个假设：这允许，例如，精确重建叠加在连续谱上的线光谱。使用模拟测量的合成多频图像，我们表明，所提出的方法提供了显着的改进，一个可比的方法，仅基于连续性假设。
In radio interferometry, every pair of antennas in an array defines one sampling point in the Fourier domain of the sky image. By combining information from different wavelengths, sample coverage - and therefore reconstruction quality - can be increased. However, the images at different wavelengths can be dramatically dissimilar; this fact must be taken into account when reconstructing multi-frequency images. In this paper, we present a novel reconstruction algorithm based on the assumption that the spectrum is continuous. In contrast to prior work, we allow for sparse deviations from this assumption: this allows, for example, for accurate reconstruction of line spectra superimposed on a continuum. Using simulated measurements on synthetic multi-frequency images, we show that the proposed approach provides significant improvements over a comparable method based solely on a continuity assumption.