A GPU‐based real‐time processing system for frequency division multiple‐input‐multiple‐output radar

Abstract

Multiple‐Input‐Multiple‐Output (MIMO) radar has the characteristic of multiple antenna channels, bringing on a big data volume for signal processing. Therefore, the trade‐off between detection ability and computational efficiency is always considered. In this article, an optimisation system is proposed to enhance the real‐time performance of frequency division MIMO radar without compromising accuracy. For the scenario of low‐altitude small target detection, a signal processing acceleration method is proposed and a MIMO radar optimisation system based on graphics processing unit (GPU) architecture is built. The signal model of frequency division MIMO radar is first established, improving the classical signal processing flow efficiency from the perspective of reducing fast Fourier transform (FFT) times and windowing operation times. To achieve an advanced acceleration, the parallel architecture of ArrayFire‐library in GPU is then employed. Distinct minimum parallel units are extracted by analysing the principle of digital beamforming (DBF), pulse compression, moving target detection (MTD), and constant false‐alarm rate (CFAR) algorithms. And the corresponding parallel algorithms are designed to constitute a parallel acceleration system of frequency division MIMO. Simulation results indicate that the proposed method significantly improves the efficiency of MIMO system with a maximum acceleration ratio of 65 times, meeting the real‐time processing requirements.