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High-resolution SAR imaging with angular diversity

机译:具有角度分集的高分辨率SAR成像

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摘要

We propose to use the APES (amplitude and phase estimation) approach for the spectral estimation of gapped data and synthetic aperture radar (SAR) imaging with angular diversity. A relaxation-based algorithm, referred to as GAPES (Gapped-data APES), is proposed, which includes estimating the spectrum via APES and filling in the gaps via a least squares (LS) fitting. For SAR imaging with angular diversity data fusion, we perform one-dimensional (1-D) windowed fast Fourier transforms (FFTs) in range, use the GAPES algorithm to interpolate the gaps in the aperture for each range, apply 1-D inverse FFTs (IFFTs) and dewindow in range, and finally apply the two-dimensional (2-D) APES algorithm to the interpolated matrix to obtain the 2-D SAR image. Numerical results are presented to demonstrate the effectiveness of the proposed algorithm
机译:我们建议将APES(幅度和相位估计)方法用于带隙数据的光谱估计和具有角度分集的合成孔径雷达(SAR)成像。提出了一种基于松弛的算法,称为GAPES(间隙数据APES),该算法包括通过APES估计频谱并通过最小二乘(LS)拟合来填充间隙。对于具有角度分集数据融合的SAR成像,我们在范围内执行一维(1-D)加窗快速傅里叶变换(FFT),使用GAPES算法对每个范围内的孔径进行插值,应用一维逆FFT (IFFT)并缩小范围,最后将二维(2-D)APES算法应用于插值矩阵以获得2-D SAR图像。数值结果表明了该算法的有效性。

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