论文标题
基于二维空间变化反卷积的近场SAR图像恢复
Near-Field SAR Image Restoration Based On Two Dimensional Spatial-Variant Deconvolution
论文作者
论文摘要
近场SAR的图像包含空间变化的旁观者和混乱，从而制服了图像质量。当前的图像恢复方法仅适用于小观察角，因为它们假设2D空间不变的降解操作。这限制了其对大型物体成像的潜力，例如飞机。为了缓解这种限制，在这项工作中提出了基于2D空间变化反卷积的图像恢复方法。首先，图像降解被视为具有2D空间变化操作的复杂卷积过程。然后，为了恢复图像，通过循环坐标下降算法进行反卷积的过程。关于模拟和测量数据的实验验证了所提出方法的有效性和优越性。与当前方法相比，获得了目标振幅和位置的更高精度估计。
Images of near-field SAR contains spatial-variant sidelobes and clutter, subduing the image quality. Current image restoration methods are only suitable for small observation angle, due to their assumption of 2D spatial-invariant degradation operation. This limits its potential for large-scale objects imaging, like the aircraft. To ease this restriction, in this work an image restoration method based on the 2D spatial-variant deconvolution is proposed. First, the image degradation is seen as a complex convolution process with 2D spatial-variant operations. Then, to restore the image, the process of deconvolution is performed by cyclic coordinate descent algorithm. Experiments on simulation and measured data validate the effectiveness and superiority of the proposed method. Compared with current methods, higher precision estimation of the targets' amplitude and position is obtained.
