低空条带图SAR相位梯度自动对焦算法的扩展

D. Thompson, J.S. Bates, D. Arnold
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引用次数: 13

摘要

相位梯度自动对焦(PGA)算法被广泛应用于聚束合成孔径雷达(SAR)中,以消除图像中的运动模糊。PGA算法已被证明是一种优越的自动对焦方法。将该算法扩展到低空条形SAR中,该算法假设波束较窄,适用于大多数SAR系统。然而,较低海拔sar具有不可忽视的较大距离依赖性。引入了一种新的相位估计器,并对其进行了扩展,使其具有距离依赖性。利用三幅具有不同特征的SAR图像进行了仿真,将新估计方法与广泛使用的最大似然方法进行了比较,并演示了距离相关的PGA算法。通过一种新的压缩方法,将PGA算法扩展到条带图模式SAR数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extending the phase gradient autofocus algorithm for low-altitude stripmap mode SAR
The phase gradient autofocus (PGA) algorithm has been widely used in spotlight synthetic aperture radar (SAR) to remove motion-induced blurs in the images. The PGA algorithm has been proven to be a superior autofocus method. This algorithm is extended for application to low-altitude stripmap mode SAR. PGA assumes a narrow beam, which is valid for most SAR systems. However, lower altitude SARs have large range dependencies that cannot be ignored. A new phase estimator for PGA is introduced and extended to allow range dependence. Three SAR images with different characteristics are used in simulations comparing the new estimator to the widely used maximum likelihood approach and in demonstrating the range-dependent PGA algorithm. The PGA algorithm is also extended to stripmap mode SAR data through a new compression method.
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