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

Abstract

Synthetic Aperture Radar (SAR) image processing requires huge computation amount. Traditionally, this task runs on the workstation or server based on Central Processing Unit (CPU) and is rather time-consuming, hence real-time processing of SAR data is impossible. Based on Compute Unified Device Architecture (CUDA) technology, a new plan of SAR imaging algorithm operated on NVIDIA Graphic Processing Unit (GPU) is proposed. The new proposal makes it possible that the data processing procedure and CPU/GPU data exchanging execute concurrently, especially when SAR data size exceeds total GPU global memory size. Multi-GPU is suitably supported by the new proposal and all of computational resources are fully exploited. It is shown by experiment on NVIDIA K20C and INTEL E5645 that the proposed solution accelerates SAR data processing by tens of times. Consequently, the GPU based SAR processing system with the proposed solution embedded is much more power saving and portable, which makes it qualified to be a real-time SAR data processing system. Experiment shows that SAR data of 36 Mega points can be processed in real-time per second by K20C with the new solution equipped.