Modern automotive design relies on a massive influx of real-world data to power autonomous decision-making. While radar is a cornerstone of ADAS, traditional 4D imaging implementations often require complex, multi-chip cascading that increases power consumption and PCB footprint. Emerging single-chip 8-by-8 4D radar transceivers, such as the AWR2188, address these challenges by providing high channel counts (up to 64 virtual antennas) in a compact form factor.
Beyond hardware integration, vehicle architectures are shifting toward software-defined models and satellite configurations. By streaming raw, high-resolution data to a central ECU, manufacturers can leverage AI and sensor fusion to enhance environmental modeling and safety. This session explores how 8-by-8 4D radar transceivers and streaming architectures overcome traditional design constraints, offering a scalable path from cost-effective implementations to premium, long-range sensing systems (>350m) necessary for the next generation of vehicle perception
