High Performance Parallel Implementation of Compressive Sensing SAR Imaging
School of Electronic and Information Engineering, Beihang University, Beijing, China
Progress In Electromagnetics Research Symposium Proceedings, 2012
The compressive sensing (CS) theory has been applied to SAR imaging systems in many ways. And it shows a significant reduction in the amount of sampling data at the cost of much longer reconstruction time. In this paper, we investigate the development and optimization of Iterative Shrinkage/Thresholding (IST) algorithm applying to CS reconstruction of SAR images on two parallel architectures, standard vectorized multi-core processors (e.g., quad-core CPUs) and graphics processing units (GPUs). Meanwhile, we modify the IST algorithm according to the characteristic of SAR images to obtain a faster recovery speed. The experiment results show that CS reconstruction of SAR images on parallel architecture has a significant speedup in comparison with implemented on conventional serial architectures.
September 7, 2012 by hgpu
