4D Radar Perception Algorithms for Autonomous Driving: A Review

arXiv:2609.19216 · cs.RO, cs.CV, eess.SP · Submitted 2026-09-16 · Read on arXiv

cs.RO, cs.CV, eess.SP

Submitted: 2026-09-16

Updated: 2026-09-16

Terminology

• Point Clouds — 25× in this paper · explained in 2 episodes
• Consistency — 13× in this paper · explained in 3 episodes
• Distillation — 11× in this paper · explained in 2 episodes
• Calibration — 9× in this paper · explained in 7 episodes
• Knowledge Distillation — 8× in this paper · explained in 11 episodes
• Multimodal Fusion — 8× in this paper · explained in 3 episodes
• Transformer — 8× in this paper · explained in 2 episodes
• Robustness — 7× in this paper · explained in 5 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Clustering — 5× in this paper · explained in 2 episodes
• Computer Vision and Pattern Recognition — 4× in this paper
• Generalization — 4× in this paper · explained in 13 episodes
• Pseudo-labels — 4× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Instance Segmentation — 3× in this paper · explained in 3 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Aperture — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• IEEE Intelligent Vehicles Symposium — 2× in this paper
• IEEE International Conference on Robotics and Automation — 2× in this paper
• Representation Learning — 2× in this paper · explained in 2 episodes
• Self-Supervised Learning — 2× in this paper · explained in 8 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 1× in this paper
• Domain Shift — 1× in this paper · explained in 4 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• IEEE International Conference on Image Processing — 1× in this paper
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Physical Constraints — 1× in this paper · explained in 7 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Temporal Reasoning — 1× in this paper · explained in 2 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• Two-Stage Architecture — 1× in this paper · explained in 2 episodes

Sources

• L2RDaS: Synthesizing 4D Radar Tensors for Model Generalization via Dataset Expansion
• HyperDet: 3D Object Detection with Hyper 4D Radar Point Clouds
• 4D Radar Gaussian Modeling and Scan Matching with RCS
• R4Det: 4D Radar-Camera Fusion for High-Performance 3D Object Detection
• 4D Millimeter-Wave Radar in Autonomous Driving: A Survey
• MetaOcc: Spatio-Temporal Fusion of Surround-View 4D Radar and Camera for 3D Occupancy Prediction with Dual Training Strategies
• 4DRC-OCC: Robust Semantic Occupancy Prediction Through Fusion of 4D Radar and Camera
• 4DRadar-GS: Self-Supervised Dynamic Driving Scene Reconstruction with 4D Radar
• RAMBA: 4D Radar Mapping by Bundle Adjustment
• DSERT-RoLL: Robust Multi-Modal Perception for Diverse Driving Conditions with Stereo Event-RGB-Thermal Cameras, 4D Radar, and Dual-LiDAR
• RCBEVDet++: Toward High-accuracy Radar-Camera Fusion 3D Perception Network
• 4DR360: State Reasoning for Joint 3D Detection and Occupancy Prediction in 4D Radar-Camera Full-Scene Perception

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