Distributed Computing method for Synthetic Aperture Radar Compressed Sensing Imaging based on MapReduce

Abstract

When using the compressed sensing method in Synthetic Aperture Radar(SAR) imaging, there are two major problems: long calculation time and insufficient scalability of t calculation ability. In order to solve the above problems, this paper proposes a distributed imaging method for SAR compressed sensing imaging based on MapReduce. First, the sparse data is labeled, then the range and azimuth image are reconstructed by two MapReduce calculation processes. With parallel computing advantages, the acceleration of SAR compressed sensing imaging is realized.