High-resolution Automotive Radar Point Cloud Imaging and Processing

Automotive radar is a class of important and necessary sensor for Advanced Driver Assistance System (ADAS) due to its recognized advantages of small size, low hardware cost, all-weather working, high-resolution and etc. However, the limitation of low angular resolution with low imaging performance can hardly satisfy the need of next-stage ADAS. The emerging 4D imaging radar (4D-radar), adopting the multi-chip cascaded multiple-input multiple-output (MIMO) technology, can achieve high resolution in the azimuth and elevation dimensions with providing high-quality three-dimensional point clouds images. In this paper, a novel algorithm is proposed by integrating the high-resolution MIMO radar point clouds imaging and processing. First, we have symmetrically studied the MIMO radar technologies, classing into three main modes, TDM-MIMO, Phase coding MIMO, DDM-MIMO. In particular, we have designed a mixed TDM-DDM-MIMO framework for point clouds imaging. Finally, the experimental analysis of the simulation is provided to confirm the effectiveness of the proposal.