Metawave claims it is the first to add a Micro Doppler Signature Extraction AI algorithm to its automotive 77 GHz radar platform. The Company’s WARLORD smart radar platform is now capable of distinguishing non-metallic objects like pedestrians, cyclists, and road animals like deer, squirrels, or coyotes, by analyzing their micro-motions. While Micro-Doppler Signatures are great for recognizing non-metallic objects, which are intrinsically harder for radars, they can still be used for providing additional information about metallic objects like cars, motorcycles or trucks – Doppler signatures associated with the rotations of the wheels can be exploited for enhanced discrimination, even between different classes of vehicles.
W-band Advanced Radar for Long-range Object Recognition and Detection (WARLORD)
Autonomous cars operation depends on both the maturity of the decision-making algorithms and performance of its critical sensors – camera, lidar, radar. The only sensor that can operate at full speed and in all-weather conditions is a radar sensor. Radar can detect, track, and image objects at long ranges, and it can process received signals an order of magnitude faster than today’s digital-only radar.
Metawave is building a new breed of high-resolution, imaging radars, capable of reconstructing its environment and interpreting the world around it like humans. Metawave’s radar platform uses engineered metamaterial structures capable of beamforming and beamsteering, and powered by an Artificial Intelligence (AI) engine that detects, recognizes, tracks, and classifies objects.
For more info, checkout WARLORD.