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首页> 外文期刊>Radar, Sonar & Navigation, IET >Squint-minimised chirp scaling algorithm for bistatic forward-looking SAR imaging
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Squint-minimised chirp scaling algorithm for bistatic forward-looking SAR imaging

机译：用于双基地前视SAR成像的最小斜率线性调频缩放算法

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A new focusing solution for one-stationary bistatic forward-looking synthetic aperture radar (BFSAR) is presented in this study. Due to the potential applications of BFSAR, such as aircraft self-landing, missile terminal guidance, BFSAR technique receives considerable attention. However, the BFSAR system usually has a large forward-looking (or squint) angle. It brings severe range cell migration and strong range dependence of effective frequency-modulation rate. Therefore, the focusing depths of traditional imaging algorithms, such as the range Doppler algorithm, chirp scaling algorithm (CSA), are not enough to process the BFSAR data. To accommodate for this problem, a squint-minimisation method for BFSAR is studied in thisarticle. Squint-minimisation method is used to shear the highly squint data to small squint data. Then, the authors propose a modified CSA based on the sheared data to implement imaging. Numerical simulations are carried out and show that the proposed algorithm still has a good focusing depth under a large forward-looking angle.
机译：本研究提出了一种新的单站双基地前视合成孔径雷达（BFSAR）聚焦解决方案。由于BFSAR的潜在应用，例如飞机自动着陆，导弹终端制导，BFSAR技术受到了广泛的关注。但是，BFSAR系统通常具有较大的前视（或斜视）角度。它带来了严重的距离小区迁移和有效频率调制率的很大范围依赖性。因此，传统的成像算法（如距离多普勒算法，线性调频缩放算法（CSA））的聚焦深度不足以处理BFSAR数据。为了解决这个问题，本文研究了BFSAR的斜视最小化方法。最小压缩方法用于将高度斜视的数据剪切为较小的斜视数据。然后，作者提出了一个基于剪切数据的改进的CSA，以实现成像。数值仿真表明，该算法在大前视角度下仍具有良好的聚焦深度。

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