基于长椭球面波函数去卷积方法的高动态范围太阳射电成像

利用综合孔径射电望远镜对太阳进行观测时，通过对图像中存在的明亮扩展源进行准确建模并移除，可以更好地观测视场内的微弱源并提高图像的动态范围。在射电天文领域，主要利用CLEAN算法对图像中的明亮源进行移除，以显示微弱的背景。然而，使用图像像素作为基函数的CLEAN算法的固有限制导致其对扩展源的建模效果较差。为了克服这种限制，将基于长椭球面波函数（Prolate Spheroidal Wave Functions,PSWF）的去卷积方法应用于太阳射电成像。PSWF最优正交基由脏图中的感兴趣区域（Region of Interest,ROI）和UV覆盖共同决定。为了验证该方法的有效性，基于PSWF正交基对均匀圆环阵观测的太阳射电图像进行去卷积，并从动态范围和保真度两个方面定量化对比了CLEAN算法和基于PSWF正交基方法的性能。基于PSWF正交基去卷积方法剩余脏图中的微弱源更接近真实情况且动态范围更高。

High Dynamic Range Solar Radio Imaging Based on Deconvolution Using Prolate Spheroidal Wave Functions

When the synthetic aperture radio telescope is used to observe the Sun, faint sources can be revealed by accurately removing the bright extended sources. Moreover, high dynamic range imaging can be achieved. The inherent limitations of using image pixels as basis functions in the CLEAN algorithm commonly used in radio astronomy lead to poor results for modeling extended sources. In this paper, a deconvolution method based on Prolate Spheroidal Wave Functions (PSWF) is applied to solar radio imaging to overcome the limitations of the CLEAN algorithm. The optimal PSWF orthogonal basis is determined by the Region of Interest (ROI) in dirty images and UV coverage of the interferometric array. The PSWF orthogonal basis is applied to the deconvolution of the solar radio images observed by the uniform circular array to confirm its efficiency. Moreover, the performance of the CLEAN algorithm and the method using PSWF were quantitatively compared from two aspects including dynamic range and fidelity. The faint sources in the residual dirty images produced by deconvolution using PSWF orthogonal basis are closer to the true model. A higher dynamic range imaging can also be obtained by using PSWF.