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首页> 外文期刊>IEEE Signal Processing Magazine >Radar-on-Chip/in-Package in Autonomous Driving Vehicles and Intelligent Transport Systems: Opportunities and Challenges
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Radar-on-Chip/in-Package in Autonomous Driving Vehicles and Intelligent Transport Systems: Opportunities and Challenges

机译：自动驾驶车辆和智能运输系统中的芯片/内部包装：机会和挑战

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This article addresses the signal processing challenges for the design of a radar-on-chip/in-package in the autonomous-driving era, taking into account recent integration trends and technology capabilities. Radar signal processing platform specifications are discussed, and the radar sensor is compared with other competing sensors, such as lidars, ultrasonics, and video cameras, that aim at detecting still or moving objects and measuring their motion parameters. This survey first focuses on signal processing techniques for a low-cost and power-efficient radar sensor, which operates in real time while ensuring the automotive coverage-range needs. The main signal processing techniques for velocity-range estimation, direction estimation, waveform design, and beamforming are analyzed with particular emphasis on the radar physical layer codesign. The future evolution of embedded computing platforms and advanced signal processing techniques are explored, such as multiple-input, multiple-output (MIMO) and cognitive radars, along with adaptive waveforms for solving interference and spectrum scarcity issues.
机译：本文介绍了在自主驾驶时代设计雷达片/包装中的信号处理挑战，考虑到最近的集成趋势和技术能力。讨论了雷达信号处理平台规范，并将雷达传感器与其他竞争传感器进行比较，例如LiDAR，超声波和摄像机，其旨在检测静止或移动物体并测量它们的运动参数。本次调查首先侧重于低成本和高效雷达传感器的信号处理技术，其实时运行，同时确保汽车覆盖范围的需求。分析了用于速度范围估计，方向估计，波形设计和波束成形的主要信号处理技术，特别强调雷达物理层代码。探索嵌入式计算平台和高级信号处理技术的未来演变，例如多输入，多输出（MIMO）和认知雷达，以及用于解决干扰和频谱稀缺问题的自适应波形。

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