A fast imaging algorithm for sparse array imaging based on PCA and modified SLIM methods
Received:October 18, 2019  Revised:April 16, 2020  download
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Author NameAffiliationE-mail
MENG Xiang-Xin Brainware Terahertz Information Technology Co. Ltd 15856969462@163.com 
WU Shuai Brainware Terahertz Information Technology Co. Ltd shuaiwu52@163.com 
TU Hao Brainware Terahertz Information Technology Co. Ltd  
LIU Tao-Rong Brainware Terahertz Information Technology Co. Ltd  
JIN Xue-Ming Brainware Terahertz Information Technology Co. Ltd  
Abstract:An algorithm combining frequency domain imaging algorithm and compressed sensing (CS) framework is proposed in here for millimeter-wave multi-static sparse array imaging. The algorithm consists of two major steps. Firstly, the typical fast Fourier transform (FFT) algorithm used in square boundary array with phase center approximation (PCA) is carried out. However, the residual phase error introduced by the PCA at close range cannot be compensated completely, so in the second step, the modified sparse learning via iterative minimization (SLIM) algorithm which is in the CS framework is introduced to refocus the initial images. By combining PCA and the modified SLIM algorithm, the proposed algorithm reaches a better computational efficiency, improves the image quality, and alleviates the requirement for iterations of the original SLIM algorithm. Simulation results verify the effectiveness of this algorithm.
keywords:sparse array imaging  fft imaging algorithm  the modified SLIM algorithm  compressed sensing
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