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Simulation of ISAR Imaging for a Space Target and Reconstruction Under Sparse Sampling via Compressed Sensing

机译:压缩感知的稀疏采样下空间目标ISAR成像和重构的仿真

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Simulation of inverse synthetic aperture radar (ISAR) imaging of a space target and reconstruction under sparse sampling via compressed sensing (CS) are developed. The numerical bidirectional analytic ray tracing (BART) method is employed to compute the polarized scattering from an electrically large target. With multiorbit and multistation imaging modes, 2-D and 3-D ISAR images are acquired, leading to information retrieval of the space target, such as shape, structure, attitude, etc. CS is introduced into the reconstruction of ISAR images under sparse sampling. As an example, the models of the Aura satellite and the X-37B orbital test vehicle are presented for ISAR imaging and reconstruction.
机译:研究了空间目标的逆合成孔径雷达(ISAR)成像仿真和稀疏采样下通过压缩感知(CS)进行的重建。数值双向分析射线追踪(BART)方法用于计算来自大目标的极化散射。通过多轨道和多站成像模式,可以获取2-D和3-D ISAR图像,从而获取空间目标的信息,例如形状,结构,姿态等。在稀疏采样的情况下,将CS引入ISAR图像的重建中。例如,提出了用于ISAR成像和重建的Aura卫星和X-37B轨道测试飞行器的模型。

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