Industry Expert Blogs

Radar is cropping up everywhere in new car designs: sensing around the car to detect hazards and feed into decision making for braking, steering, and parking; in the cabin for driver and occupancy monitoring systems. Effective under all weather conditions, now high-definition radar can front-end AI-based object detection complementing other sensor channels to further enhance accuracy and safety. There’s plenty of potential for builders of high value embedded radar systems. However competitively exploiting that potential can be challenging. Here we explore some of those challenges.

Full system challenges

Automotive OEMs aren’t simply adding more electronic features to new vehicles; they are driving unified system architectures for their product lines to manage cost, simplify software development and maintenance, and to enhance safety and security. More compute and intelligence is moving into consolidated zonal controllers, communicating on one side between relatively small sensor units and processors within a small zone of the car, and on the other side between zonal controllers and a central controller managing overall decision making.

Suppliers aiming at automotive radar system markets must track their solution architectures with these changes, providing scalability between relatively simple processing for edge functions and more extensive capability for zonal or central controllers, while being flexible to adapt to different OEM partitioning choices.

One important implication is that however a solution might be partitioned, it must allow for significant amounts of data to be exchanged between edge, zonal and central compute. Which raises the importance of data compression during transmission to manage latency and power.

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