基于背景和变化稀疏性的瞬变源图像重建算法

针对射电干涉测量通过结合长时间观测的多组可见度数据对静态源进行高空间分辨率成像，但无法得到时变信息的问题，提出了一种基于背景和目标变化的直和空间上稀疏性的稀疏基线综合孔径动态场景图像重建算法。将起始时刻的亮温和相邻时刻的亮温变化作为待求解矢量，不同时刻的亮温表示为它们的和，构造测量方程，并利用起始时刻亮温和相邻时刻亮温的稀疏性进行求解，重建出不同时刻的瞬变源图像。仿真实验结果表明，对于小区域背景下的瞬变源，所提算法与已有方法相当，对于大区域背景下的瞬变源，所提算法优于已有方法。 

A image reconstruction algorithm of transient sources based on combined sparsities of background and variation

Radio interferometers can achieve high spatial resolution imaging by combining multiple groups of visibility data measured over long periods of time. However, the variable information of temporally variable source is missing. A image reconstruction algorithm of varied sources by sparse baseline aperture synthesis based on sparse constraint on direct sum of background and inter-frame difference is proposed. The brightness temperature at initial moment and the brightness temperature difference of adjacent moments are taken as the vector of solution to seek, and the brightness temperatures at different moments are the sums of them, which leads to the measuring equation of the brightness temperature at initial moment and the difference. Transient source images at different moments are reconstructed by solving the sparsity of brightness temperature at initial moment and brightness temperature difference of adjacent moments. The results of numerical experiments show that the proposed method matches the best on transient source in a local background and outperforms the existing methods on varying source in a global background.