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Accurate range profile alignment method based on minimum entropy for inverse synthetic aperture radar image formation

机译:基于最小熵的精确距离轮廓对准方法用于逆合成孔径雷达成像

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摘要

Accurate range profile alignment is an essential step for achieving the subsequent azimuth coherent processing for inverse synthetic aperture radar image formation. In this study, an iterative method based on minimum entropy is first proposed for accurate range profile alignment, which constructs a series of local quadratic curves to gradually approach the extremum of the entropy of range profiles. The accuracy of range profile alignment depends on whether the iteration could be convergent to the optimal extremum. Unfortunately, the entropy of misaligned range profiles usually has numerous local extrema. The low-pass profile filtering is able to smooth the entropy surface and eliminate the local extrema. Nevertheless, the detailed features of range profiles are also lost due to the filtering so that the alignment accuracy could be reduced. Finally, a circulation cascade processing by appropriately combining the proposed iterative method and the low-pass filtering is presented to make the range profile alignment both convergent and accurate. Simulations and real data are used to validate the performance of the proposed method on iteration convergence and alignment accuracy.
机译:精确的距离剖面对准是实现用于逆合成孔径雷达图像形成的后续方位角相干处理的重要步骤。在这项研究中,首先提出了一种基于最小熵的迭代方法以实现精确的距离剖面对齐,该方法构造了一系列局部二次曲线,以逐渐逼近距离剖面的熵的极值。范围轮廓对齐的准确性取决于迭代是否可以收敛到最佳极值。不幸的是,未对准范围轮廓的熵通常具有许多局部极值。低通轮廓滤波能够使熵表面平滑并消除局部极值。然而,由于滤波,距离分布图的详细特征也丢失了,从而可能降低对准精度。最后,通过适当地结合所提出的迭代方法和低通滤波,提出了一种循环级联处理,以使距离轮廓对准既收敛又准确。仿真和真实数据用于验证所提出方法在迭代收敛性和对准精度上的性能。

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