利用熵对逆合成孔径雷达(ISAR)图像进行聚焦

Y. Mohan-Ram, L. Jain
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摘要

逆合成孔径雷达(ISAR)对具有大旋转角或非线性旋转运动的目标生成的图像,如果不考虑旋转运动,则会产生模糊。如果旋转运动是已知的,则可以通过从收集数据的极网格重新采样到矩形网格来校正数据。然后可以使用二维FFT形成聚焦的ISAR图像。实际上,旋转运动是不知道先验的,所以它必须从数据本身估计。本文提出了一种估计目标旋转运动的方法。旋转运动建模为二次型,其参数通过最小化数据的单个交叉范围轮廓的熵来设置。最小熵交叉距离像是最佳聚焦的交叉距离像,可以得到聚焦的ISAR图像。另外,图像本身的熵也可以最小化,但这并没有被考虑,因为它是计算密集型的
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The use of entropy to focus inverse synthetic aperture radar (ISAR) images
Inverse synthetic aperture radar (ISAR) images generated of targets which have a large angle of rotation or non-linear rotational motion are blurred if the rotational motion is not taken into account. If the rotational motion is known, the data can be corrected by resampling from the polar grid on which the data is collected, to a rectangular grid. A focused ISAR image can be then formed by using a 2D FFT. In practice the rotational motion is not known a priori and so it must be estimated from the data itself. This paper presents a technique for estimating the target's rotational motion. The rotational motion is modelled as a quadratic, the parameters of which are set by minimising the entropy of a single cross range profile of the data. The minimum entropy cross range profile is the best focused cross range profile which should result in a focused ISAR image. Alternatively the entropy of the image itself could be minimised, but this has not been considered as it is computationally intensive.<>
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