基于幅度的CLEAN天文图像重建算法

An Amplitude-Based CLEAN Astronomical Image Reconstruction Algorithm

射电干涉成像的质量部分依赖于图像重建算法。CLEAN算法是一种应用非常广泛的射电天文数据的重建算法,已经成为射电天文干涉数据处理软件的标准配置。典型的CLEAN算法使用delta函数集合来逼近我们真实的天文图像,然而当前没有工作来优化这种集合,从而达到提高图像重建效果的目的。本文改进了当前的CLEAN算法,提出了一种基于幅度的重建算法。通过通用天文软件程序包(Common Astronomy Software Applications, CASA)模拟美国甚大干涉阵(VLA)进行了观测,对得到测量数据MS (Measurement Sets)使用常规的CLEAN算法和本文改进的CLEAN算法进行了重建。实验显示本文改进的算法的重建图像有更高动态范围。

The quality of radio interference imaging partly depends on the image reconstruction algorithm. The CLEAN algorithm is a widely used reconstruction algorithm for radio astronomy data and has become the standard configuration of radio interferometric data processing software. A typical CLEAN algorithm uses a set of delta functions to approximate a real astronomical image. However, currently there is no work to optimize such a set to achieve the purpose of improving the image reconstruction effect. This paper improves the current CLEAN algorithm and proposes an amplitude-based reconstruction algorithm. The VLA observation was simulated by the Common Astronomy Software Applications (CASA), and the conventional CLEAN algorithm and the improved CLEAN algorithm were used to reconstruct the measured data MS (Measurement Sets). Experiments show that the improved algorithm has a higher dynamic range of the reconstructed image.