One-bit SAR imaging algorithm based on MC function and TV norm

DOI number:10.1016/j.dsp.2023.104149

Affiliation of Author(s):中国科技大学电子工程与信息科学系

Journal:Digital Signal Processing

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

Abstract: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.

First Author:Mingyu Niu (牛明宇)

Co-author:Mengru Tian,Yongfei Zhai,Falin Liu

Indexed by:Journal paper

Discipline:Engineering

Document Type:J

Volume:141

Page Number:104149

Translation or Not:no

Date of Publication:2023-07-17

Included Journals:SCI、EI