Concurrency Analysis and Implementation of SAR Imaging Algorithm Oriented to Hybrid Storage System

Recently, the real-time synthetic aperture radar (SAR) imaging technique is a hotspot of research in the field of remote sensing and military applications. As the SAR imaging algorithm is associated with high data and computation intensive, it is suitable for using hybrid storage systems, e.g. A cluster, for the performance acceleration. To design a SAR algorithm with high performance, we need consider a prerequisite to maximize the parallelizability of the algorithm due to multi-level parallelization features of the cluster platform. Focusing on the large-scale data, we explore concurrency characteristics of the SAR imaging algorithm on a hybrid storage system, and propose some parallel optimization techniques to accelerate the SAR imaging algorithm. According to the study, we implement a parallel SAR imaging algorithm and evaluate its performance. Experiment results show that the optimized SAR imaging program has high-speed network utilization, and can realize obvious improvement on the performance.