Morrison Robert L, Do Minh N, Munson David C
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
IEEE Trans Image Process. 2009 Apr;18(4):840-53. doi: 10.1109/TIP.2009.2012883.
We present a new noniterative approach to synthetic aperture radar (SAR) autofocus, termed the multichannel autofocus (MCA) algorithm. The key in the approach is to exploit the multichannel redundancy of the defocusing operation to create a linear subspace, where the unknown perfectly focused image resides, expressed in terms of a known basis formed from the given defocused image. A unique solution for the perfectly focused image is then directly determined through a linear algebraic formulation by invoking an additional image support condition. The MCA approach is found to be computationally efficient and robust and does not require prior assumptions about the SAR scene used in existing methods. In addition, the vector-space formulation of MCA allows sharpness metric optimization to be easily incorporated within the restoration framework as a regularization term. We present experimental results characterizing the performance of MCA in comparison with conventional autofocus methods and discuss the practical implementation of the technique.
我们提出了一种用于合成孔径雷达（SAR）自动聚焦的新的非迭代方法，称为多通道自动聚焦（MCA）算法。该方法的关键在于利用散焦操作的多通道冗余来创建一个线性子空间，未知的完美聚焦图像存在于该子空间中，它可以用由给定散焦图像形成的已知基来表示。然后，通过调用额外的图像支持条件，通过线性代数公式直接确定完美聚焦图像的唯一解。发现MCA方法计算效率高且稳健，并且不需要对现有方法中使用的SAR场景进行先验假设。此外，MCA的向量空间公式允许将锐度度量优化作为正则化项轻松纳入恢复框架。我们展示了与传统自动聚焦方法相比表征MCA性能的实验结果，并讨论了该技术的实际实现。
