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Phaseless Terahertz Coded-Aperture Imaging for Sparse Target Based on Phase Retrieval Algorithm

机译:基于相位检索算法的稀疏目标的无相太赫兹编码孔径成像

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摘要

Phaseless terahertz coded-aperture imaging (PL-TCAI) is a novel radar computational imaging method that utilizes the coded aperture and the incoherent detector array to achieve forward-looking and high-resolution imaging without relying on relative motion. In this paper, we propose a more reasonable and compact architecture for the PL-TCAI system and derive the imaging model of PL-TCAI based on the random frequency-hopping signal. Since most phase retrieval algorithms for PL-TCAI utilize only the intensity of echo signals to accurately reconstruct the target, excessive measurement samples are usually required. In order to reduce the number of measurement samples required for imaging, this paper proposes a sparse Wirtinger flow algorithm with optimal stepsize (SWFOS) by using the sparse prior of the target. The specific procedures of the SWFOS algorithm include the support recovery, initialization by truncated spectral method, iteration via gradient descent scheme, hard threshold operation, and stepsize optimization of iteration. Numerical simulations are performed, and the results show that the SWFOS algorithm not only has good performance for the PR problem, but can also sharply reduce the number of measurement samples required for imaging in the PL-TCAI system.
机译:无相位太赫兹编码孔径成像(PL-TCAI)是一种新颖的雷达计算成像方法,它利用编码孔径和非相干探测器阵列来实现前视和高分辨率成像,而无需依赖相对运动。在本文中,我们为PL-TCAI系统提出了一种更合理,更紧凑的架构,并基于随机跳频信号推导了PL-TCAI的成像模型。由于大多数PL-TCAI的相位检索算法仅利用回波信号的强度来准确地重建目标,因此通常需要过多的测量样本。为了减少成像所需的测量样本数量,本文提出了一种使用目标的稀疏先验的稀疏Wirtinger流算法,该算法具有最佳步长(SWFOS)。 SWFOS算法的具体过程包括支持恢复,通过截短频谱方法进行初始化,通过梯度下降方案进行迭代,硬阈值运算以及逐步优化迭代。进行了数值模拟,结果表明,SWFOS算法不仅对PR问题具有良好的性能,而且可以大大减少PL-TCAI系统中成像所需的测量样本数量。

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