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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >A Frequency-Domain Imaging Algorithm for Translational Variant Bistatic Forward-Looking SAR
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A Frequency-Domain Imaging Algorithm for Translational Variant Bistatic Forward-Looking SAR

机译:一种转化变体双向前瞻性SAR的频域成像算法

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摘要

Bistatic forward-looking synthetic aperture radar (BFSAR) breaks through the limitations of the conventional monostatic SAR on the forward-looking imaging. However, the problems of range cell migration (RCM) caused by the linear range walk and 2-D spatial variability of Doppler parameters become more serious and complicated in translational variant BFSAR. In this article, a keystone transform is introduced to correct the linear RCM. Based on the characteristics of a small aperture, the nonlinear chirp scaling (NCS) is discussed in the frequency domain to equalize the azimuth-range-dependent Doppler parameters. The improved NCS in our newly proposed BFSAR imaging algorithm, especially the re-definition of range direction and the model of spatial variant phase, differentiates this article from all the existing studies in the literature on BFSAR signal processing. Simulation results and real data processing further validate the effectiveness of the proposed algorithm.
机译:双面前瞻性的合成孔径雷达(BFSAR)通过传统的单体SAR对前瞻性成像的局限性。然而,由线性范围步行引起的范围细胞迁移(RCM)和多普勒参数的2-D空间可变性引起的范围细胞迁移(RCM)变得更加严重,在转化变体BFSAR中变得更加严重。在本文中,引入了梯形转换以纠正线性RCM。基于小光圈的特性,在频域中讨论非线性啁啾缩放(NCS)以均衡方位范围依赖的多普勒参数。在我们新提出的BFSAR成像算法中的改进的NCS,特别是重新定义范围方向和空间变体阶段的模型,将本文与文献中的所有现有研究区分开来,在文献中的所有现有研究中对BFSAR信号处理。仿真结果和实际数据处理进一步验证了所提出的算法的有效性。

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