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SAR PRF-Ambiguity Resolving by Range-Doppler Domain Normalized Variance Maximization

机译:距离多普勒域归一化方差最大化的SAR PRF模糊度解决

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摘要

By exploiting the statistical property of synthetic aperture radar (SAR) range migration (RM) in the range compressed range-Doppler (RD) domain, we discovered that the 'averaged range image' of the range compressed RD domain, which is obtained by averaging the signal intensity over the RM curve, has the highest normalized variance (NV). Based on this fact, a novel method for resolving SAR pulse repetition frequency (PRF)-ambiguity in the RD domain is proposed in this paper. With high computational efficiency and easiness of being incorporated into existing SAR imaging algorithms, the proposed method is robust to scene contrast, and has little dependence on the ambiguous Doppler centroid estimation accuracy for large ambiguity number case. Experimental results with real space-borne SAR data demonstrate its effectiveness.
机译:通过利用合成孔径雷达(SAR)距离压缩多普勒(RD)域中的统计特性,我们发现距离压缩RD域的“平均距离图像”是通过平均获得的RM曲线上的信号强度具有最高的归一化方差(NV)。基于这一事实,提出了一种解决RD域SAR脉冲重复频率(PRF)模糊性的新方法。该方法具有较高的计算效率,并且易于集成到现有的SAR成像算法中,对场景对比度具有鲁棒性,并且在多模数情况下对多普勒重心估计的准确性几乎没有依赖性。真实SAR数据的实验结果证明了其有效性。

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