嵌入式GPU滑动聚束SAR实时成像方法

针对SAR实时成像系统的传统计算平台实时性不足与功耗过高的问题,研究了一种基于嵌入式GPU的实现方法.为了充分利用嵌入式GPU中有限的内存资源,提出一种内存分割与重配置方案,采用页锁定内存和zero-copy技术,实现数传-计算并行化处理;为解决实时性问题,在算法并行计算环节,利用共享内存、寄存器等资源实现大规模数据并行.结果表明,在TX2上完成16 384×8 192点滑聚SAR成像处理时间为12.66 s,功耗为15 W.该优化方法也适用于其他模式的雷达处理算法,并可为未来嵌入式实时成像处理提供参考. 

The Real-Time Imaging Method for Sliding Spotlight SAR Based on Embedded GPU

For the real-time SAR imaging systems, aiming at the problems of low real-time performance and high power consumption of traditional computing platforms, an implementation method was studied for embedded GPU. In order to make full use of the limited memory in the embedded GPU, a memory partitioning and reconfiguration scheme was proposed. The page-locked memory and zero-copy technology were used to realize the transmission-calculation parallelization. To achieve high real-time performance, large-scale parallelism was realized by using shared memory, registers, et. The result shows that sliding spotlight SAR imaging processing on the TX2 can only take 12.66 s time and consume 15 W power. This method is also applicable to other modes radar processing algorithms, and can provide reference for the future embedded real-time SAR imaging processing.