Raw SAR data Compression by Structurally Random Matriz based Compressive Sampling
Synthetic aperture radar (SAR) is an imaging system which can provide high resolution images of earth surface.It transmits chirp signals and the received echoes are sampled into I and Q components,thus producing a huge amount of raw SAR data which may exceed the on-board storage and downlink bandwidth.In this paper,we compress the raw SAR data by sampling the signal below the well-known Nyquist rate using a novel framework of compressive sampling (CS),i.e,a fast and efficient sampling with structurally random matrices(SRM) which is developed on the provable mathematical model.In this framework,a 2DFFT and a structurally random matrix whose columns are permuted randomly are employed in the encoder. At the decoder the basis pursuit reconstruction then proceeds to find the sparsest signal.Simulation results are also presented to prove the feasibility of our proposed scheme.
SAR compressed sampling structurally random matrices basis pursuit
Min Wang
Key National Lab of Radar Signal Processing Xidian University,710071,Xian,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
1119-1122
2009-10-26（万方平台首次上网日期，不代表论文的发表时间）