Application of Compressed Sensing in Sparse Aperture Imaging of Radar
A new optimal reconstruction method based on compressed sensing (CS) for sparse synthetic aperture radar (SAR)/inverse SAR (ISAR),which can be used in widely sparse aperture,is proposed in this letter.Unlike other parametric estimation method as all-pole algorithm,CS can obtain near-optimal estimation and global-minimal error of gapped signal representation with structured dictionaries and random projections. To resolve the issue of minimization of non-zeros elements,traditional approaches such as orthogonal matching pursuit (OMP) and basis pursuit (BP) may be used. This non-adaptive means performs better than FFT imaging,especially in azimuth focusing of SAR/ISAR. The results with simulation data and real sparse SAR/ISAR data validate the feasibility and superiority of the approach.
compressed sensing sparse aperture random projections synthetic aperture radar inverse SAR
Li Jun Xing Mengdao Wu Shunjun
National Key Lab.of Radar Signal Processing,Xidian Univ.,Xian710071,China
国际会议
2009 2nd Asian-Pacific Conference on Synthetic Aperture Radar(第二届亚太合成孔径雷达会议)
西安
英文
651-655
2009-10-26（万方平台首次上网日期，不代表论文的发表时间）