How are radar and camera data fused for robust object detection?

Radar-camera fusion combines complementary strengths: radar provides accurate range and velocity; camera provides classification and high angular resolution. Fusion approaches: Early fusion projects radar points into camera image for joint processing; feature-level fusion combines intermediate representations from separate processing; late fusion associates independent detections and combines properties. Association challenges include different fields of view, timing synchronization, and coordinate transformation accuracy. Benefits include improved detection range (radar) with classification (camera), better handling of adverse conditions, and reduced false positives through cross-confirmation. Modern systems increasingly use deep learning for end-to-end fusion.