Compressed Sensing in ISAR imaging with Sparse Sub-aperture

摘要：

In this paper, a reconstruction method of 2-D ISAR image with sparse sub-aperture based on Compressive Sensing (CS) is proposed. The method is revealed as follows. In the range, the conventional processing can be carried out to obtain sparse spectrogram. In the cross-range, the CS theory can be utilized to reconstruct 2-D ISAR image. According to CS theory, a random partial unit matrix can be considered as the measurement matrix and the DFT matrix can be designed as the sparsity matrix, whose multiplication satisfies RIP. In addition, the modified OMP algorithm can be utilized to achieve the reconstructed results avoiding sparsity estimation. By using the proposed method, the well 2-D ISAR imaging can be obtained on condition of the data in cross-range is reduced apparently. The effectiveness of the method can be validated in simulation results.

关键词： ISAR imaging Sparse Sub-aperture Compressive Sensing Random partial unit matrix Modified OMP agorithm

作者: F. Zhu Q. Zhang J.B. Yan F.F. Gu S. Liu

作者单位: Inst. of Telecommunication Engineering, AFEU, Shaanxi, Xi’an, 710077 Faculty of Biomedical Engineering, The Fourth Military Medical University, 710032

会议类型: 国际会议

会议名称: 2011 IEEE CIE International Conference on Radar(2011年IEEE国际雷达会议RADAR 2011)

会议地点: 成都

会议语种:英文

页码: 1463-1466

在线出版日期: 2011-10-24（万方平台首次上网日期，不代表论文的发表时间）