Turbo-like Iterative Thresholding for SAR Image Recovery from Compressed Measurements

摘要：

Compressive sensing (CS) has attracted many researchers since it offers a novel paradigm that one can acquire sparse signals at a sub-Nyquist rate without information losses.In 123,the authors have presented some schemes for CS application on remote sensing imaging,some of which are related to SAR.CS remote sensing imaging includes two steps:on-board encoding imaging and off-line decoding recovery.Based on the on-board encoding imaging scheme proposed in 1,this paper focuses on the off-line decoding recovery algorithm.We proposed a Turbo-like Iterative Residual Thresholding algorithm (RTIT) to decode the compressed SAR data with approximately sparse property. The experimental results show that it outperforms the state-of-the-art Iterative Thresholding algorithm (IT).

关键词： Compressive Sensing SAR Iterative Thresholding RTIT

作者: Lei YU Yi YANG Hong SUN Chu He

作者单位: Signal Processing Laboratory,Electronic Information School,Wuhan University,China,430079

会议类型: 国际会议

会议名称: 2009 2nd Asian-Pacific Conference on Synthetic Aperture Radar(第二届亚太合成孔径雷达会议)

会议地点: 西安

会议语种:英文

页码: 664-667

在线出版日期: 2009-10-26（万方平台首次上网日期，不代表论文的发表时间）