In the race towards higher levels of vehicle autonomy, from advanced driver assistance systems (ADAS) like AEB and L2+ to full self-driving capabilities at L4, radar technology plays a pivotal role in ensuring true safety. Exploring the architectural tradeoffs and overall design considerations shaping modern automotive radar systems. Comparing three key approaches:
- Massive MIMO and dense array solutions from high-end chipsets from Arbe and Mobileye, leveraging very high channel count and optimized ASIC edge computing for real-time data processing, enhanced resolution and high dynamic range.
- Sparse array techniques deployed by leading Tier1 suppliers with 4-chip cascade designs from TI/NXP (up to 16x16), focusing on the balance between channel count, compute power and resolution/dynamic-range performance.
- Distributed aperture systems with centralized compute, based on highly sparse designs, utilizing cheap TI/NXP 4x4 based Radars with OTA synchronization - emphasizing scalable design and easier packaging of simple, common radars with performance, wiring & compute tradeoffs.
Providing an in-depth look at how these architectures fit the next generation of autonomous driving, balancing factors such as resolution, latency, dynamic range, packaging, scalability, and cost in attempt to enable true safety.