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Sparse Aperture Three-dimensional Reconstruction of Precession Target Based on Compressed Sensing

机译:基于压缩感知的进动目标稀疏孔径三维重建

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As a kind of high speed rotation object, precession target is faced with migration through resolution cell (MTRC) in long synthetic aperture while using translational inverse synthetic aperture radar (ISAR) imaging algorithm. Compressed sensing (CS), by which we can exact recovery sparse signal from very limited samples, suggests that sparse aperture imaging of precession target maybe achievable. A cyclic shift algorithm based on CS is proposed in this paper to exploit the sparse apertures data for high-resolution ISAR imaging. The sparse signal recovery and imaging of precession target is achieved coupled with FOCUSS (focal undetermined system solver) algorithm. A conventional ISAR imaging is a two-dimensional (2-D) range-Doppler projection of a target and does not provide three-dimensional (3-D) information which is more reliable. For missile shaped like a flat-bottom cone, multistatic ISAR geometry model is built, and a 3-D reconstruction method, which is featured with stable structure characteristics, is proposed based on multistatic ISAR images. Simulation and real data results verify the validity and superiority of the proposed method.
机译:进动目标作为一种高速旋转的物体,在使用平移逆合成孔径雷达(ISAR)成像算法的同时,在长合成孔径下面临着通过分辨单元(MTRC)的迁移。压缩传感(CS)使我们可以从非常有限的样本中恢复稀疏信号,这表明进动目标的稀疏孔径成像是可以实现的。提出了一种基于CS的循环移位算法,用于稀疏孔径数据的高分辨率ISAR成像。结合FOCUSS(焦距不确定的系统求解器)算法,可以实现对进动目标的稀疏信号恢复和成像。传统的ISAR成像是目标的二维(2-D)距离多普勒投影,并且不提供更可靠的三维(3-D)信息。针对平底圆锥形导弹,建立了多静态ISAR几何模型,并基于多静态ISAR图像,提出了一种具有稳定结构特征的3-D重建方法。仿真和实际数据结果验证了该方法的有效性和优越性。

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