A Cascade Compress Method of SAR Data Based on Compressed Sensing and Vector Quantization

A new kind of compression method is proposed to solve the problem of transmitting huge SAR data. Firstly,compressed sensing( CS) is used to down-sample the radar echo signal. Secondly,the down-sampled SAR echo data is compressed and encoded by using the block adaptive tree-structure Vector Quantization( BATSVQ),and then be transferred. Meanwhile,the sparse representation of SAR data in the range-doppler domain is accurately recovered by the algorithms of BATSVQ decoding and CS reconstruction,which is conducted in the receiver or the warning command on the ground. Afterward,the chirp scaling algorithm is executed to achieve 2-d high resolution image. Lastly,the compression ratio of this compression method is quantitative analyzed,which shows that this new method could still imaging on the basis of slash echo data. The effectiveness of the proposed method can be validated by simulation results.