BYD's 4D Radar Chip Adds Height to Self-Driving Vision

BYD's 4D Radar Chip Adds Height to Self-Driving Vision

BYD Semiconductor mass-produced a 28nm 4D radar chip with 8T8R and 400m range, adding elevation data to help vehicles distinguish pedestrians from obstacles in complex traffic.

gg
gizmo guru
Sep 2, 2026
2 min read

BYD Semiconductor has officially launched its next-generation automotive-grade 4D millimeter-wave radar chip, marking a significant step forward in the company's push to strengthen its position in the intelligent driving supply chain. The new chip is designed to deliver higher resolution and more precise object detection compared to traditional 3D radar, enabling vehicles to better distinguish between stationary and moving objects, pedestrians, and obstacles in complex traffic scenarios.

The 4D technology adds elevation data to the standard three dimensions of range, velocity, and azimuth, effectively giving the radar a "height" perspective. This allows autonomous driving systems to more accurately map the environment around the vehicle, particularly in crowded urban settings or during adverse weather conditions where cameras and LiDAR may struggle. The launch comes as BYD continues to vertically integrate its supply chain, reducing reliance on external suppliers while advancing its self-developed intelligent driving capabilities.

Industry analysts view the move as part of a broader trend among Chinese automotive manufacturers to localize key components for advanced driver-assistance systems. The millimeter-wave radar chip market has become increasingly competitive, with both domestic and international players racing to deliver higher-performance solutions for the growing electric and autonomous vehicle sectors. BYD Semiconductor's latest offering positions the company to capture a larger share of this expanding market. Radar technology has emerged as a critical enabler for autonomous vehicles, and researchers continue to push its capabilities further. For example, by developing AI-powered systems that allow robots and self-driving cars to detect objects hidden around corners. Energy-efficient memory chips are also being developed to support AI workloads on edge devices, which is essential for real-time processing in autonomous driving systems.

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