A Novel Autofocusing Algorithm for ISAR Imaging Based on Sparsity-driven Optimization

摘要：

A novel algorithm of phase adjustment joint with ISAR imaging based on sparsity-driven is proposed in this paper. In the scheme, both phase adjustment and imaging are established in an optimization problem to seek for phase errors and reconstruct ISAR image by exploiting the prior sparsity of target scattering field. The novelty of this method lies in its capability of de-noising and overcoming phase errors, resulting in well-focused image. Besides, the optimization problem is solved by using fast Fourier transform and matrix Hardmard multiplication, promoting the efficiently. The experimental results using both simulated data and measured data confirm the validation of the proposal.

关键词： Inversed synthetic aperture radar (ISAR) phase adjustment optimization sparsity de-noising

作者: Gang Xu Qian-qian Chen Shuang-xi Zhang Lei Zhang

作者单位: Nationaol Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China

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: 1471-1474

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）