A Novel Compressive Sensing Algorithm for SAR Imaging

作者：Dong Xiao^*; Zhang Yunhua

来源：IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(2): 708-720.

DOI：10.1109/JSTARS.2013.2291578

• Chirp-scaling algorithm (CSA)
• compressive sensing (CS)
• orthonormal basis
• synthetic aperture radar (SAR)
• two-dimensional double CS Algorithm (2-D-DCSA)

A novel compressive sensing (CS) algorithm for synthetic aperture radar (SAR) imaging is proposed which is called as the two-dimensional double CS algorithm (2-D-DCSA). We first derive the imaging operator for SAR, which is named as the chirp-scaling operator (CSO), from the chirp-scaling algorithm (CSA), then we show its inverse is a linear map, which transforms the SAR image to the received baseband radar signal. We show that the SAR image can be reconstructed simultaneously in the range and azimuth directions from a small number of the raw data. The proposed algorithm can handle large-scale data because both the CSO and its inverse allow fast matrix-vector multiplications. Both the simulated and real data are processed to test the algorithm and the results show that the 2-D-DCSA can be applied to reconstructing the SAR images effectively with much less data than regularly required.

• 出版日期2014-2
• 单位中国科学院国家空间科学中心; 中国科学院大学