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An Azimuth-Variant Autofocus Scheme of Bistatic Forward-Looking Synthetic Aperture Radar

机译:双基地前视合成孔径雷达的方位-方差自动聚焦方案

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In bistatic forward-looking synthetic aperture radar (BFSAR), conventional autofocus algorithms cannot estimate the phase errors accurately when the range walk is compensated in the azimuthal time domain. This problem stems from the influence of the azimuth-variant Doppler coefficients after linear range cell migration correction in azimuthal time domain. In principle, nonlinear chirp scaling processing can be carried out to remove the azimuth variance. Nevertheless, Doppler azimuth variations of the Doppler parameters induced by the motion errors are not taken into consideration and serious defocus would emerge in the final image. To cope with such a problem, an estimation-evaluation-equalization scheme is proposed before conventional autofocus for BFSAR. Different from the conventional autofocus method, the azimuth-variant Doppler coefficients are additionally estimated and equalized before autofocus, and as a consequence, phase errors can be precisely estimated. The BFSAR data processing results demonstrate the validity of the proposed method on the improvement of autofocus in BFSAR.
机译:在双基地前视合成孔径雷达(BFSAR)中,当在方位角时域中补偿距离游走时,传统的自动聚焦算法无法准确估计相位误差。此问题源于在方位角时域中进行线性范围单元偏移校正后的方位变多普勒系数的影响。原则上,可以执行非线性线性调频缩放处理以去除方位角方差。然而,由于运动误差引起的多普勒参数的多普勒方位角变化没有被考虑,并且最终图像中会出现严重的散焦。为了解决这样的问题,提出了在BFSAR的传统自动聚焦之前的估计-评估-均衡方案。与传统的自动聚焦方法不同,方位变量多普勒系数在自动聚焦之前需要额外估算和均衡,因此可以精确估算相位误差。 BFSAR数据处理结果证明了该方法对改善BFSAR自动对焦的有效性。

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