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Micro-Doppler Effect Removal in ISAR Imaging by Promoting Joint Sparsity in Time-Frequency Domain

机译:通过促进时频域的联合稀疏性去除ISAR成像中的微多普勒效应

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摘要

For micromotion scatterers with small rotating radii, the micro-Doppler (m-D) effect interferes with cross-range compression in inverse synthetic aperture radar (ISAR) imaging and leads to a blurred main body image. In this paper, a novel method is proposed to remove the m-D effect by promoting the joint sparsity in the time-frequency domain. Firstly, to obtain the time-frequency representations of the limited measurements, the short-time Fourier transform (STFT) was modelled by an underdetermined equation. Then, a new objective function was used to measure the joint sparsity of the STFT entries so that the joint sparse recovery problem could be formulated as a constrained minimization problem. Similar to the smoothed l0 (SL0) algorithm, a steepest descend approach was used to minimize the new objective function, where the projection step was tailored to make it suitable for m-D effect removal. Finally, we utilized the recovered STFT entries to obtain the main body echoes, based on which cross-range compression could be realized without m-D interference. After all contaminated range cells were processed by the proposed method, a clear main body image could be achieved. Experiments using both the point-scattering model and electromagnetic (EM) computation validated the performance of the proposed method.
机译:对于旋转半径较小的微动散射体,微多普勒(m-D)效应会干扰合成孔径雷达(ISAR)逆向成像中的跨范围压缩,并导致主体图像模糊。本文提出了一种通过在时频域中提高联合稀疏度来消除m-D效应的新方法。首先,为了获得有限测量的时频表示,通过一个不确定方程式对短时傅立叶变换(STFT)进行建模。然后,使用新的目标函数来测量STFT条目的联合稀疏性,从而可以将联合稀疏恢复问题表述为约束最小化问题。与平滑的l0(SL0)算法相似,使用了最陡峭的下降方法来最小化新的目标函数,在该目标函数中调整了投影步骤以使其适合于m-D效果消除。最后,我们利用恢复的STFT条目获得主体回波,基于该回波可以在没有m-D干扰的情况下实现跨范围压缩。用提出的方法处理所有受污染的测距单元后,就可以获得清晰的主体图像。使用点散射模型和电磁(EM)计算的实验验证了该方法的性能。

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