Understanding Automotive Radar: Present and Future

Wednesday, May 23, 10:40 AM - 11:10 AM
Summit Track: 
Mission City Ballroom M1-M3

Thanks to its proven, all-weather range detection capability, radar is increasingly used for driver assistance functions such as automatic emergency braking and adaptive cruise control. Radar is considered a crucial sensing technology for autonomous vehicles not only for its range finding ability, but also because it can be used to determine target velocity and target angle. In this tutorial, we introduce the basic principles of operation of a radar system, highlighting its main parameters and comparing radar with computer vision and other types of sensors typically found in ADAS and autonomous vehicles. After examining the features and the limitations of current automotive radar systems, we discuss how automotive radar is evolving, particularly in light of safety performance assessment programs such as the European New Car Assessment Programme (eNCAP). We conclude with a discussion of how radar systems may compete with or complement vision-based sensors in future ADAS-equipped and autonomous vehicles.


Arunesh Roy

Radar Algorithms Architect, NXP

Dr. Arunesh Roy is a Systems Architect leading the Advanced Radar Algorithms group at NXP Semiconductors, investigating algorithms and system requirements for high resolution Radar sensors for ADAS and autonomous driving. Previously, he was Systems Program Manager at Oculii Corp, where he led the definition of system architecture for Radar sensors used in ADAS and traffic surveillance systems. Arunesh received his Ph.D. from Wright State University in Dayton, Ohio where he worked on sensor fusion algorithms and multi-target tracking for unmanned aerial vehicles, unmanned ground vehicles and unattended ground sensors.

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