Radar Measurement

Radar measurement research focuses on improving the accuracy, reliability, and application of radar data for various tasks, including object detection, motion estimation, and scene understanding. Current efforts concentrate on developing advanced signal processing techniques (like CFAR-based filtering and pulse compression) and deep learning architectures to overcome challenges posed by noise, sparse data, and uncertain measurements, often incorporating data fusion with other sensor modalities (e.g., LiDAR, cameras). These advancements are driving progress in autonomous driving, robotics, and gesture recognition by enabling more robust and reliable perception systems in diverse and challenging environments.