Airborne SAR Real-time Imaging Algorithm Design and Implementation with CUDA on NVIDIA GPU

Abstract

Synthetic Aperture Radar (SAR) image processing requires a considerable amount of computational resources. Traditionally, this task runs on a workstation or a server based on Central Processing Units (CPUs) and is rather time-consuming, making real-time processing of SAR data impossible. Based on Compute Unified Device Architecture (CUDA) technology, a new plan for a SAR imaging algorithm operated on an NVIDIA Graphic Processing Unit (GPU) is proposed. The new proposal makes it possible for the data processing procedure and the CPU/GPU data exchange to execute concurrently, especially when the size of SAR data exceeds the total GPU global memory size. A multi-GPU is suitably supported by the new proposal, and all computational resources are fully exploited. It has been shown by an experiment on an NVIDIA K20C and INTEL E5645 that the proposed solution accelerates SAR data processing by tens of times. Consequently, a GPU based SAR processing system that embeds the proposed solution is much more efficient and portable, thereby making it qualified to be a real-time SAR data processing system. Experiments showed that SAR data can be processed in real-time at a rate of 36 megapixels per second by a K20C when the new solution is implemented.