Phoenix is Arbe's high-resolution perception radar for autonomy systems that need weather-robust sensing across automotive, robotaxi, heavy-machinery, and all-terrain applications.
Target environment: Autonomous vehicles, robotaxis, industrial vehicles, off-road equipment, and mobile machines exposed to weather, dust, lighting variation, or long-range detection needs.
Workflow context: Perception radar, obstacle detection, Doppler velocity sensing, safety redundancy, and sensor-fusion input for autonomy systems.
Customer context: Autonomy developers, automotive and industrial-vehicle OEMs, Tier 1 suppliers, robotaxi programs, and heavy-equipment autonomy teams.
Deployment model: Sensor module integrated into vehicle and machine perception stacks alongside cameras, LiDAR, compute, and autonomy software.
Commercial maturity: Commercial perception-radar platform positioned for autonomy markets that need weather-robust sensing.
Adoption constraints: Adoption depends on radar perception software integration, sensor-fusion tuning, validation against use-case safety requirements, and competition from camera/LiDAR-heavy stacks.
Market position: Perception-radar component for robotics and autonomous mobility supply chains where radar redundancy is valuable.
Adjacent products: Atlas Ultra 4D LiDAR, JT16 Mini 3D LiDAR, UST-10LX Scanning Rangefinder
Audience
Auto OEMs
Workflow
Perception radar, obstacle detection, Doppler velocity sensing, safety redundancy, and sensor-fusion input for autonomy systems.
Deployment environment
Autonomous vehicles, robotaxis, industrial vehicles, off-road equipment, and mobile machines exposed to weather, dust, lighting variation, or long-range detection needs.
Specifications
Virtual Channels: 2,304 virtual channels
Field Of View Hv: 120 degrees azimuth x 30 degrees elevation
Range: 300 m
Frame Rate: 20 FPS
Range Resolution: 10 cm to 80 cm
Doppler Resolution: 0.1 m/s
Target Use Cases: Passenger vehicles, trucks, robotaxis, counter-drone, heavy machinery and all-terrain/industrial applications
Tags
Peer Group: Automotive imaging radars
Workflow: Mobile Robot Navigation
Capability: Radar Perception, Robot perception
Stack Layer: Radar Sensor, Sensing stack, Radar system hardware