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MCA: A Multichannel Approach to SAR Autofocus

机译:MCA:SAR自动对焦的多渠道方法

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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.
机译:我们提出了一种新的非迭代方法来合成孔径雷达(SAR)自动对焦,称为多通道自动对焦(MCA)算法。该方法的关键是利用散焦操作的多通道冗余来创建线性子空间,其中存在未知的完美聚焦图像,以从给定散焦图像形成的已知基础表示。然后,通过调用其他图像支持条件,通过线性代数公式直接确定完美聚焦图像的唯一解决方案。发现MCA方法在计算上是有效且稳健的,不需要先验假设现有方法中使用的SAR场景。此外,MCA的向量空间公式使清晰度度量优化可以轻松地作为规则项纳入恢复框架。我们目前的实验结果表征了MCA与传统自动对焦方法相比的性能,并讨论了该技术的实际实现。

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