DOI码：10.1016/j.dsp.2023.104149

所属单位：中国科技大学电子工程与信息科学系

发表刊物：Digital Signal Processing

关键字：One-bit SAR, MC penalty function, TV-norm, Fast Low-rank Sparse Decomposition

摘要：Synthetic Aperture Radar (SAR) imaging is generally characterized by a large amount of data and a high sampling rate. The traditional one-bit compressed sensing will generate virtual targets when recovering images at a low SNR, resulting in low reconstruction accuracy and obvious noise impact of the algorithm. In this paper, a one-bit SAR imaging algorithm based on the Minimax Concave (MC) penalty function and the Total Variation (TV) norm is proposed, which can potentially improve the reconstruction accuracy. At the same time, to solve the problem of speckle noise generated in the imaging process, this paper proposes a Fast Low-rank Sparse Decomposition (FLRSD) algorithm based on the one-bit contaminated image, which potentially improves the anti-noise performance and reconstruction efficiency. The results of simulation and measured data show that the proposed algorithms have better reconstruction accuracy and focusing performance than other algorithms. Even at low SNR, they also have good reconstruction effect.

合写作者：Mengru Tian,Yongfei Zhai,Falin Liu

第一作者：Mingyu Niu (牛明宇)

论文类型：期刊论文

学科门类：工学

文献类型：J

卷号：141

页面范围：104149

是否译文：否

发表时间：2023-07-17

收录刊物：SCI、EI