High-resolution Automotive Radar Point Cloud Imaging and Processing

2022 Photonics & Electromagnetics Research Symposium (PIERS) Pub Date : 2022-04-25 DOI:10.1109/piers55526.2022.9792662

Meng Jiang, Gang Xu, Haonan Pei, Hui Zhang, Kunpeng Guo

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引用次数: 1

Abstract

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.

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高分辨率汽车雷达点云成像与处理

汽车雷达具有体积小、硬件成本低、全天候工作、高分辨率等公认的优点，是高级驾驶辅助系统(ADAS)必不可少的一类重要传感器。然而，低角度分辨率和低成像性能的限制很难满足下一阶段ADAS的需要。新兴的四维成像雷达(4D-radar)采用多芯片级联多输入多输出(MIMO)技术，可以在方位角和仰角尺寸上实现高分辨率，提供高质量的三维点云图像。本文提出了一种集成高分辨率MIMO雷达点云成像与处理的新算法。首先，我们对称地研究了MIMO雷达技术，将其分为三种主要模式:TDM-MIMO，相位编码MIMO, DDM-MIMO。特别地，我们设计了一个用于点云成像的混合TDM-DDM-MIMO框架。最后进行了仿真实验分析，验证了该方法的有效性。

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2022 Photonics & Electromagnetics Research Symposium (PIERS)

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