Synthetic aperture radar autofocus based on time-frequency transform

Yin-wei Li, M. Xiang, Li-deng Wei
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Abstract

Phase gradient autofocus (PGA) is a robust tool for high resolution synthetic aperture radar (SAR) phase estimation and correction under the assumption that some strong scatterers with high signal-to-clutter ratio (SCR) are available within the unfocused image. In this paper, an advanced PGA algorithm is proposed, where the short-time Fourier transform (STFT) firstly is used to estimate the quadratic phase error (QPE) and the PGA is applied with a more effective filtering in the short-time Fourier domain (STFD). The proposed algorithm can relax the limitation on the scene content and achieve well-focused images without iteration. The validity of the proposed algorithm is demonstrated with the experimental results of simulation data and real radar data.
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基于时频变换的合成孔径雷达自动对焦
相位梯度自动对焦(PGA)是高分辨率合成孔径雷达(SAR)相位估计和校正的有力工具,但前提是非聚焦图像中存在高信杂比的强散射体。本文提出了一种改进的PGA算法,该算法首先利用短时傅立叶变换(STFT)估计二次相位误差(QPE),然后在短时傅立叶域(STFD)进行更有效的PGA滤波。该算法可以放松对场景内容的限制,无需迭代即可获得聚焦良好的图像。仿真数据和实际雷达数据的实验结果验证了该算法的有效性。
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