Radar-on-Chip/in-Package in Autonomous Driving Vehicles and Intelligent Transport Systems: Opportunities and Challenges

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.