Millimeter-Wave Radar
Overview
Millimeter-wave radar research turns reflected signals—often represented as range-Doppler maps, point clouds, or raw antenna measurements—into information about people, vehicles, and surroundings. Methods combine signal processing with neural networks for detection, tracking, pose estimation, localization, and mapping, sometimes fusing radar with cameras or lidar. Physics-based simulators and cross-modal supervision help address scarce labels, while radar’s operation in darkness, smoke, and adverse weather supports robust and privacy-preserving sensing. A central challenge is that radar data are sparse, noisy, and affected by multipath and sensor differences, so strong benchmark results do not always transfer across environments or hardware.
Latest papers
51 papers5 papers in the last four weeks, down 29% on the four weeks before. 0.0% of all new papers.