Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109-2122, USA.
IEEE Trans Image Process. 2011 Dec;20(12):3544-52. doi: 10.1109/TIP.2011.2156421. Epub 2011 May 19.
Synthetic aperture radar (SAR) imaging suffers from image focus degradation in the presence of phase errors in the received signal due to unknown platform motion or signal propagation delays. We present a new autofocus algorithm, termed Fourier-domain multichannel autofocus (FMCA), that is derived under a linear algebraic framework, allowing the SAR image to be focused in a noniterative fashion. Motivated by the mutichannel autofocus (MCA) approach, the proposed autofocus algorithm invokes the assumption of a low-return region, which generally is provided within the antenna sidelobes. Unlike MCA, FMCA works with the collected polar Fourier data directly and is capable of accommodating wide-angle monostatic SAR and bistatic SAR scenarios. Most previous SAR autofocus algorithms rely on the prior assumption that radar's range of look angles is small so that the phase errors can be modeled as varying along only one dimension in the collected Fourier data. And, in some cases, implicit assumptions are made regarding the SAR scene. Performance of such autofocus algorithms degrades if the assumptions are not satisfied. The proposed algorithm has the advantage that it does not require prior assumptions about the range of look angles, nor characteristics of the scene.
合成孔径雷达(SAR)成像在接收信号中存在相位误差时会导致图像聚焦退化,这是由于未知的平台运动或信号传播延迟造成的。我们提出了一种新的自动聚焦算法,称为傅里叶域多通道自动聚焦(FMCA),该算法是在线性代数框架下推导出来的,允许以非迭代的方式对 SAR 图像进行聚焦。受多通道自动聚焦(MCA)方法的启发,所提出的自动聚焦算法利用了低回波区域的假设,该区域通常位于天线旁瓣内。与 MCA 不同,FMCA 直接使用收集的极坐标傅里叶数据工作,并且能够适应广角单基地 SAR 和双基地 SAR 场景。以前的大多数 SAR 自动聚焦算法都依赖于雷达视场角度范围较小的先验假设,因此相位误差可以建模为仅在收集的傅里叶数据的一个维度上变化。并且,在某些情况下,对 SAR 场景做出了隐含的假设。如果不满足这些假设,这些自动聚焦算法的性能就会下降。所提出的算法具有不需要对视场角度范围或场景特征的先验假设的优点。