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A Robust Translational Motion Compensation Method for ISAR Imaging Based on Keystone Transform and Fractional Fourier Transform Under Low SNR Environment

机译:低SNR环境下基于Keystone变换和分数阶Fourier变换的ISAR成像鲁棒平移运动补偿方法。

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摘要

In this work, a parametric-based approach is proposed to perform joint range alignment and phase adjustment based on the intention of fully exploiting the energy of all the scatterers in the moving target and the two-dimensional coherent accumulation gain of both range and azimuth compressions. To that end, first, translational motion is modeled as a polynomial signal, and inspired by the fact that all the scatterers in the moving target experience the same translational range history, the phase difference operation and keystone transform (KT) are utilized to transform the energy of all the scatterers into one range cell. Second, by the virtue of the fractional Fourier transform (FrFT), the energy of all the scatterers is coherently accumulated into a peak point, and from which the polynomial coefficients can be obtained accurately. With the estimated polynomial coefficients, the dechirp operation and KT are applied jointly to compensate range misalignment and phase error. The analysis of the proposed method shows that it is of low computational complexity due to avoiding multidimensional search and improves the output SNR providing satisfactory low SNR performance. The experimental results are provided to demonstrate the performance of the proposed method compared with the state-of-the-art algorithms.
机译:在这项工作中,基于充分利用运动目标中所有散射体的能量以及范围和方位压缩的二维相干累积增益,提出了一种基于参数的方法来执行联合范围对准和相位调整。 。为此,首先,将平移运动建模为多项式信号,并受到以下事实的启发:运动目标中的所有散射体都经历相同的平移范围历史,因此利用相差运算和梯形失真变换(KT)来变换将所有散射体的能量合并到一个范围单元中。其次,借助分数傅里叶变换(FrFT),所有散射体的能量都相干地累积到一个峰值点,从中可以精确地获得多项式系数。利用估计的多项式系数,可以共同应用去chirp运算和KT来补偿范围失准和相位误差。对该方法的分析表明,由于避免了多维搜索,该方法具有较低的计算复杂度,并改善了输出SNR,从而提供了令人满意的低SNR性能。实验结果提供了与最新算法相比证明所提出方法的性能。

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