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An efficient NLCS algorithm for maneuvering forward-looking linear array SAR with constant acceleration

机译:高效的NLCS算法,用于以恒定加速度操纵前瞻性线性阵列SAR

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摘要

HighlightsA realistic geometry configuration of the forward-looking linear array SAR is built.Efficient range nonlinear chirp scaling algorithm is proposed for the forward looking linear-array SAR imaging.Thorough algorithm derivation and approximation error analysis are presented.Numerical simulation illustrates easy implementation and high efficiency of the method.AbstractForward-looking linear-array synthetic aperture radar (FLLA-SAR), which can overcome the deficiency of the traditional SAR on forward-looking imaging, continues to gain in significance due to the various applications, such as unmanned aerial vehicle (UAV) reconnaissance. To compensate the space-variant characteristic of along-track frequency modulation (FM) rate caused by the high speed maneuvering UAV, an efficient nonlinear chirp scaling (NLCS) algorithm is proposed in this paper. Based on the analysis of novel geometric configuration and the introduction of NLCS operation, the linear-array UAV SAR can reconstruct the 2-D image of the scout area. Finally, the validation of the proposed algorithm is done by exploiting the simulated data based on 3 × 3 array point targets and an airplane scattering model.
机译: 突出显示 已构建了前瞻性线性阵列SAR的逼真的几何配置。 为前瞻性线性阵列SAR提出了有效范围非线性线性调频缩放算法成像。 提供了详尽的算法推导和近似误差分析。 < / ce:simple-para> 摘要 前瞻性线性阵列合成孔径雷达(FLLA-SAR)可以克服传统SAR在前视成像方面的不足的技术,由于诸如无人机(UAV)侦察等各种应用而继续变得越来越重要。为了补偿由于高速机动无人机引起的航迹调频率的空间变化特性,提出了一种有效的非线性线性调频标度算法。基于对新型几何构型的分析和NLCS操作的引入,线性阵列无人机SAR可以重建侦察区域的二维图像。最后,通过利用基于3××array3阵列点目标和飞机散射模型的仿真数据对所提出的算法进行验证。

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