Welcome to the University of Arizona Radar Lab! We focus on radar signal processing, multimodal sensor fusion, machine learning with an emphasis on sensors, and radar imaging.
Our newly developed website provides details about our research projects, members, publications, resources, and latest news. Please visit the site for the most up-to-date information:
TI mmWave radar ROS driver (with sensor fusion and hybrid)
Multiple Patients Behavior Detection in Real-time using mmWave Radar and Deep CNNs
Automatic Radar-Camera Dataset Generation for Sensor-Fusion Applications
Source codes and results from the skeletal pose estimation using Seq2Seq architecture
Development of Intelligent Multimodal Traffic Monitoring using Radar Sensor at Intersections
ROS 1 Package to collect, visualize, and process data from Hesai Lidar, TI mmWave Radar, and USB Camera for sensor fusion
Code for our paper: TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection
Code for our paper: Online Targetless Radar-Camera Extrinsic Calibration Based on the Common Features of Radar and Camera
Code for our paper: Radar-Camera Fused Multi-Object Tracking: Online Calibration and Common Feature
CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR–Camera Calibration with Iterative and Attention-Driven Post-Refinement
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