School of Electronic Engineering, Xidian University, Xi'an 710071, China.
Sensors (Basel). 2022 Jan 5;22(1):396. doi: 10.3390/s22010396.
The data volume and computation task of MIMO radar is huge; a very high-speed computation is necessary for its real-time processing. In this paper, we mainly study the time division MIMO radar signal processing flow, propose an improved MIMO radar signal processing algorithm, raising the MIMO radar algorithm processing speed combined with the previous algorithms, and, on this basis, a parallel simulation system for the MIMO radar based on the CPU/GPU architecture is proposed. The outer layer of the framework is coarse-grained with OpenMP for acceleration on the CPU, and the inner layer of fine-grained data processing is accelerated on the GPU. Its performance is significantly faster than the serial computing equipment, and satisfactory acceleration effects have been achieved in the CPU/GPU architecture simulation. The experimental results show that the MIMO radar parallel simulation system with CPU/GPU architecture greatly improves the computing power of the CPU-based method. Compared with the serial sequential CPU method, GPU simulation achieves a speedup of 130 times. In addition, the MIMO radar signal processing parallel simulation system based on the CPU/GPU architecture has a performance improvement of 13%, compared to the GPU-only method.
MIMO 雷达的数据量和计算任务巨大，其实时处理需要非常高的计算速度。本文主要研究时分 MIMO 雷达信号处理流程，提出了一种改进的 MIMO 雷达信号处理算法，在结合先前算法的基础上，提高了 MIMO 雷达算法的处理速度，并在此基础上提出了一种基于 CPU/GPU 架构的 MIMO 雷达并行仿真系统。该框架的外层采用 OpenMP 进行粗粒度加速，内层采用 GPU 加速细粒度数据处理。其性能明显快于串行计算设备，并在 CPU/GPU 架构模拟中取得了令人满意的加速效果。实验结果表明，基于 CPU/GPU 架构的 MIMO 雷达并行仿真系统极大地提高了基于 CPU 的方法的计算能力。与串行顺序 CPU 方法相比，GPU 模拟实现了 130 倍的加速。此外，与仅使用 GPU 的方法相比，基于 CPU/GPU 架构的 MIMO 雷达信号处理并行仿真系统的性能提高了 13%。
