A curated list of radar datasets, detection, tracking and fusion.
Keep updating.
Author: Yi Zhou
Contact: [email protected]
Update some public-available codes, see useful_codes.md

In my review paper (still under review), there is a table with more detials.

| Dataset | Radar Type | Task | Link | | ---- |----| ---- | ---- | ---- | | HawkEye | SAR | Static vehicle classification | Website| | PREVENTION | Conti ARS308 + SRR208 x2 | Trajectory Prediction | Website| | SCORP | 76GHz | Open space segmentation | Website | | Ghost | 77GHz long range *2 | Ghost object detection | Github | | DopNet | 24Ghz | Gesture Classification | Website | Radar signatures of human activities | Soli | Indoor human activities | Dataset | | Solinteraction Data | Soli | Tangible interactions| Github | | GROUNDED | Ground Penetrating Radar | Localization | Website| |FloW Dataset | TI AWR1843 | Floating waste detection | Website |

| Dataset | Radar Type | Task | Link | | ---- |----| ---- | ---- | ---- | | Oxford Radar Robocar | Navtech Spinning Radar | Odometry | Website | |RADIATE| Navtech Spinning Radar | Odometry, Detection, Tracking | Website| | MulRan | Navtech Spinning Radar | Place Recognition |Website| | Boreas | Navtech Spinning Radar| Long-term Odometry, Localization, Detection | Website| | EU Long-term Dataset | Conti ARS 308 | Long-term SLAM | Website| | ColoRadar | TI AWR2243 Cascade + AWR1843 |Odometry | Website | | USVInland | TI AWR1843 | SLAM in inland waterways, Water segmentation| Website | | Endeavour Radar Dataset | Conti ARS 430 x5 | Odometry | Website|

RaDICaL's Toolbox: SDK; PyRapid: SDK OpenRadar : SDK Pymmw: SDK Open radar initiative: SDK RADIal's Emptyband-DDM Script: Code

NXP Premium Radar SDK: Link TI mmWAVE Studio: Link TI Toolbox: Link Matlab Radar Toolbox: Link

Ainstein Radar ROS Node: ROS Node Continental ARS 408 ROS Node: ROS Node TI mmWave ROS Driver: Guide RaDICaL's TI ROS Node: ROS Node UoA's TI ROS Package: ROS Node

• Automotive Radar – An Overview on State-of-the-Art Technology [Video]
• Automotive Radar – A Signal Processing Perspective on Current Technology and Future Systems [Video][Slides]
• Radar Old but Gold- current research challenges and activities in radar micro-Doppler signatures [Video]
• Soli: Millimeter-wave radar for touchless interaction [Video]
• 2021 CVPR Workshop on Autonomous Driving (Tesla's Famous Talk) [Video]
• 2021 ICRA Radar Perception for All-Weather Autonomy [Website]
• 2021 ICASSP Recent Advances in mmWave Radar Sensing for Autonomous Vehicles [Website]
• IEEE AESS Virtual Distinguished Lecturer Webinar Series [Website]
• Journal of Radar Webinar Series (in Chinese) [Video]

• Fundamentals of Radar Signal Processing by Mark A. Richard
• Radar Systems Analysis and Design using Matlab by Bassem R. Mahafza

• Introduction to mmwaveSensing: FMCW Radars
• The fundamentals of millimeter wave sensors
• Signal Processing for TDM MIMO FMCW Millimeter-Wave Radar Sensors

• Quadrature Signals: Complex, But Not Complicated
• Using a complex-baseband architecture in FMCW radar systems

• TI MIMO radar
• TI EmptyBand DDM

Antenna:

• Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz Frequency Band
• Antenna Concepts for Millimeter-Wave Automotive Radar Sensors

Radar Signal Processing

• Automotive Radar Signal Processing: Research Directions and Practical Challenges
• Recent Evolution of Automotive ImagingRadar and Its Information content
• Automotive Radars A review of signal processing techniques
• A Review of Recent Advancements Including Machine Learning on Synthetic Aperture Radar using Millimeter-Wave Radar
• A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing
• Micro-Doppler Effect in Radar: Phenomenon, Model, and Simulation Study

Deep Learning Applications:

• Interference Suppression Using Deep Learning: Current Approaches and Open Challenges
• A Machine Learning Perspective on Automotive Radar Direction of Arrival Estimation
• Application of Deep Learning on Millimeter-Wave Radar Signals: A Review
• MMW Radar-Based Technologies in Autonomous Driving: A Review
• Application of Deep Learning on Millimeter-Wave Radar Signal A Review

Detection:

• 3D Object Detection from Images for Autonomous Driving: A Survey
• Deep Learning for 3D Point Clouds: A Survey
• A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving
• Attention Mechanisms in Computer Vision: A Survey

Sensor Fusion:

• Lidar for Autonomous Driving
• Multisensor data fusion: A review of the state-of-the-art
• Information Decomposition of Target Effects from Multi-Source Interactions: Perspectives on Previous, Current and FutureWork

Uncertainty Estimation:

• Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods

2018-Review of Radar Classification & RCS Characterisation Techniques for Small UAVs or Drones 2021-Machine Learning-Based Target Classification for MMW Radar in Autonomous Driving

• 2017-Radar Reflection Characteristics of Vehicles for Contour and Feature Estimation
• 2018-Radar and Lidar Target Signatures of Various Object Types and Evaluation of Extended Object Tracking Methods for Autonomous Driving Applications

• 2017-A Novel Target-Height Estimation Approach Using Radar-Wave Multipath Propagation for Automotive Applications
• 2018-Automotive Radar Multipath Propagation in Uncertain Environments
• 2018-Analysis of Multipath and DOA Detection Using a Fully Polarimetric Automotive Radar
• 2020-Using Machine Learning to Detect Ghost Images in Automotive Radar
• 2020-Seeing Around Street Corners Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar
• 2021-Ghost Target Detection in 3D Radar Data using Point Cloud based Deep Neural Network

• 2006-Micro-Doppler Effect in Radar: Phenomenon, Model, and Simulation Study
• 2020-New Radar Micro-Doppler Tag for Road Safety Based on the Signature of Rotating Backscatters

• 2016-A Polarimetric 76-79 GHz Radar-Frontend for Target Classification in Automotive Use
• 2018-Performance Analysis of 79 GHz Polarimetric Radar Sensors for Autonomous Driving
• 2018-Autonomous Driving Features based on 79 GHz Polarimetric Radar Data
• 2019-Polarimetric Signatures of a Passenger Car

• Diversified Radar Micro-Doppler Simulations as Training Data for Deep Residual Neural Networks
• Measurements revealing Challenges in Radar Sensor Modeling for Virtual Validation of Autonomous Driving
• Virtual Radar: Real-Time Millimeter-Wave Radar Sensor Simulation for Perception-Driven Robotics
• Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition
• Scalable and Physical Radar Sensor Simulation for Interacting Digital Twins
• A Multi-Layered Approach for Measuring the Simulation-to-Reality Gap of Radar Perception for Autonomous Driving

• 2017-Deep Stochastic Radar Models
• 2020-GenRadar: Self-supervised Probabilistic Camera Synthesis based on Radar Frequencies
• 2019-Automotive radar and camera fusion using Generative Adversarial Networks
• 2020-L2R GAN: LiDAR-to-Radar Translation
• 2020-There and Back Again: Learning to Simulate Radar Data for Real-World Applications

• Auto-Calibration of Automotive Radars in Operational Mode Using Simultaneous Localisation and Mapping
• Multi-Radar Self-Calibration Method using High-Definition Digital Maps for Autonomous Driving

• Obstacle Detection Using Millimeter-wave Radar and Its Visualization on Image Sequence
• Radar and vision sensors calibration for outdoor 3D reconstruction
• Spatio-Temporal Multisensor Calibration Based on Gaussian Processes Moving Object Tracking
• Targetless Rotational Auto-Calibration of Radar and Camera for Intelligent Transportation Systems
• A Continuous-Time Approach for 3D Radar-to-Camera Extrinsic Calibration

• Extrinsic 6DoF calibration of 3D LiDAR and radar
• Extrinsic and Temporal Calibration of Automotive Radar and 3D LiDAR
• Automatic Targetless Extrinsic Calibration of Multiple 3D LiDARs and Radars

• Extrinsic 6DoF Calibration of a Radar – LiDAR– Camera System Enhanced by Radar Cross Section Estimates Evaluation
• An Joint Extrinsic Calibration Tool for Radar, Camera and Lidar
• Online multi-sensor calibration based on moving object tracking

• 2018-Precise Ego-Motion Estimation with Millimeter-Wave Radar under Diverse and Challenging Conditions
• 2019-An Instantaneous 3D Ego-Velocity Measurement Algorithm for Frequency Modulated Continuous Wave Doppler Radar Data
• 2020-Radar-Inertial Ego-Velocity Estimation for Visually Degraded Environments
• 2020-milliEgo: Single-chip mmWave Aided Egomotion Estimation with Deep Sensor Fusion

• 2016-Potential of Radar for Static Object Classification using Deep Learning Methods
• 2017-Object Classification in Radar Using Ensemble Methods

• 2018-Semantic Segmentation on Radar Point Clouds
• 2019-Scene Understanding With Automotive Radar
• 2019-Road Scene Understanding by Occupancy Grid Learning from Sparse Radar Clusters using Semantic Segmentation
• 2020-Semantic Segmentation on 3D Occupancy Grids for Automotive Radar
• 2020-Deep Open Space Segmentation using Automotive Radar
• 2020-Statistical Image Segmentation and Region Classification Approaches for Automotive Radar
• 2021-PolarNet Accelerated Deep Open Space Segmentation Using Automotive Radar in Polar Domain

• 2019-Probably Unknown Deep Inverse Sensor Modelling Radar
• 2019-Occupancy Grids Generation Using Deep Radar Network for Autonomous Driving
• 2020-Kidnapped Radar Topological Radar Localisation using Rotationally-Invariant Metric Learning
• 2020-RadarSLAM Radar Based Large-Scale SLAM in All Weathers
• 2021-Unsupervised Place Recognition with Deep Embedding Learning over Radar Videos
• 2020-Deep Learning for Autonomous and Driver Assistant Systems
• 2020-A Scalable Framework for Robust Vehicle State Estimation with a Fusion of a Low-Cost IMU, the GNSS, Radar, a Camera and Lidar
• 2020-See Through Smoke: Robust Indoor Mapping with Low-cost mmWave Radar
• 2021-AutoPlace: Robust Place Recognition with Low-cost Single-chip Automotive Radar
• 2021-Do We Need to Compensate for Motion Distortion and Doppler Effects in Spinning Radar Navigation
• 2021-Cross-Modal Contrastive Learning of Representations for Navigation using Lightweight, Low-Cost Millimeter Wave Radar for Adverse Environmental Conditions

• 2012-Grid-Based DBSCAN for Clustering Extended Objects in Radar Data
• 2016-Adaptive Clustering for Contour Estimation of Vehicles for High-Resolution Radar
• 2018-Supervised Clustering for Radar Applications On the Way to Radar Instance Segmentation
• 2019-A Multi-Stage Clustering Framework for Automotive Radar Data
• 2019-Robust and Adaptive Radar Elliptical Density-Based Spatial Clustering and labeling for mmWave Radar Point Cloud Data
• 2021-Anomaly Detection in Radar Data Using PointNets
• 2021-Fast Rule-Based Clutter Detection in Automotive Radar Data

• 2015-Making Bertha See Even More
• 2017-Comparison of Random Forest and Long Short-Term Memory Network Performances in Classification Tasks Using Radar
• 2018-Radar-based Feature Design and Multiclass Classification for Road User Recognition
• 2019-Radar-based Road User Classification and Novelty Detection with Recurrent Neural Network Ensembles
• 2020-Off-the-shelf sensor vs. experimental radar - How much resolution is necessary in automotive radar classification
• 2021-Deep Learning for Automotive Object Classification with Radar Reflections

• 2019-2D Car Detection in Radar Data with PointNets
• 2020-Detection and Tracking on Automotive Radar Data with Deep Learning
• 2020-Pointillism Accurate 3D Bounding Box Estimation with Multi-Radars
• 2020-Radar-based 2D Car Detection Using Deep Neural Networks
• 2021-Radar Voxel Fusion for 3D Object Detection
• 2021-Kernel Point Convolution LSTM Networks for Radar Point Cloud Segmentation

• 2019-Deep Radar Detector
• 2019-mID Tracking and Identifying People with Millimeter Wave Radar
• 2020-Improved and Optimal DBSCAN for Embedded Applications Using High-Resolution Automotive Radar
• 2020-MmWave Radar Point Cloud Segmentation using GMM in Multimodal Traffic Monitoring
• 2020-Through Fog High Resolution Imaging Using MillimeterWave Radar
• 2020-Deep Learning on Radar Centric 3D Object Detection
• 2021-Radar Transformer An Object Classification Network Based on 4D MMW Imaging Radar
• 2021-mmPose-NLP A Natural Language Processing Approach to Precise Skeletal Pose Estimation using mmWave Radars
• 2021-RPFA-Net: a 4D RaDAR Pillar Feature Attention Network for 3D Object Detection

• 2020-High Resolution Radar Dataset for Semi-Supervised Learning of Dynamic Objects
• 2021-MIMO-SAR A Hierarchical High-Resolution Imaging Algorithm for mmWave FMCW Radar in Autonomous Driving
• 2021-Classification Of Automotive Targets Using Inverse Synthetic Aperture Radar Images

• 2019-Deep Learning-based Object Classification on Automotive Radar Spectra
• 2020-Image Segmentation and Region Classification in Automotive High-Resolution Radar Imagery
• 2020-YOLO-Based Simultaneous Target Detection and Classification in Automotive FMCW Radar Systems
• 2020-300 GHz radar object recognition based on deep neural networks and transfer learning
• 2020-2020-Probabilistic Oriented Object Detection in Automotive Radar
• 2021-Perception Through 2D-MIMO FMCW Automotive Radar Under Adverse Weather
• 2021-Deep-Learning Based Decentralized Frame-to-Frame Trajectory Prediction Over Binary Range-Angle Maps for Automotive Radars

• 2018-Single-Frame Vulnerable Road Users Classification with a 77 GHz FMCW Radar Sensor and a Convolutional Neural Network
• 2018-Moving Target Classification in Automotive Radar Systems Using Convolutional Recurrent Neural Networks
• 2019-A Study on Radar Target Detection Based on Deep Neural Networks
• 2020-Object Detection and 3d Estimation Via an FMCW Radar Using a Fully Convolutional Network
• 2021-Detecting High-Speed Maneuvering Targets by Exploiting Range-Doppler Relationship for LFM Radar
• 2021-DeepHybrid: Deep Learning on Automotive Radar Spectra and Reflections for Object Classification

• 2021-Radar Object Detection Using Data Merging, Enhancement and Fusion
• 2021-Squeeze-and-Excitation network-Based Radar Object Detection with Weighted Location Fusion
• 2021-Scene-aware Learning Network for Radar Object Detection
• 2021-DANet: Dimension Apart Network for Radar Object Detection
• 2021-Efficient-ROD: Efficient Radar Object Detection based on Densely Connected Residual Network
• 2021-ROD2021 Challenge: A Summary for Radar Object Detection Challenge for Autonomous Driving Applications

• 2019-Experiments with mmWave Automotive Radar Test-bed
• 2019-Vehicle Detection With Automotive Radar Using Deep Learning on Range-Azimuth-Doppler Tensors
• 2020-CNN Based Road User Detection Using the 3D Radar Cube
• 2020-RAMP-CNN A Novel Neural Network for Enhanced Automotive Radar Object Recognition
• 2021-Multi-View Radar Semantic Segmentation
• 2021-High-resolution radar road segmentation using weakly supervised learning
• 2021-Graph Convolutional Networks for 3D Object Detection on Radar Data

• 2018-Classification of Intra-Pulse Modulation of Radar Signals by Feature Fusion Based Convolutional Neural Networks

• 2018-Practical classification of different moving targets using automotive radar and deep neural networks
• 2018-DNN Transfer Learning From Diversified Micro-Doppler for Motion Classification
• 2020-Uncertainty Analysis of Deep Neural Network for Classification of Vulnerable Road Users using micro-Doppler
• 2021-A Bayesian Framework for Integrated Deep Metric Learning and Tracking of Vulnerable Road Users using Automotive Radars

• 2019-Distant Vehicle Detection Using Radar and Vision
• 2019-RVNet: Deep Sensor Fusion of Monocular Camera and Radar for Image-based Obstacle Detection in Challenging Environments
• 2019-Radar and Camera Early Fusion for Vehicle Detection in Advanced Driver Assistance Systems
• 2019-A Deep Learning-based Radar and Camera Sensor Fusion Architecture for Object Detection
• 2019-Deep Learning Based 3D Object Detection for Automotive Radar and Camera
• 2020-YOdar Uncertainty-based Sensor Fusion for Vehicle Detection with Camera and Radar Sensors
• 2020-Radar+ RGB Fusion For Robust Object Detection In Autonomous Vehicle
• 2020-Low-level Sensor Fusion for 3D Vehicle Detection using Radar Range-Azimuth Heatmap and Monocular Image
• 2021-Radar Camera Fusion via Representation Learning in Autonomous Driving
• 2021-Robust Small Object Detection on the Water Surface through Fusion of Camera and MillimeterWave Radar
• 2021-RVDet:Feature-level Fusion of Radar and Camera for Object Detection

• 2019-RRPN: Radar Region Proposal Network for Object Detection in Autonomous Vehicles
• 2020-CenterFusion: Center-based Radar and Camera Fusion for 3D Object Detection
• 2020-Radar-Camera Sensor Fusion for Joint Object Detection and Distance Estimation in Autonomous Vehicles
• 2020-GRIF Net: Gated Region of Interest Fusion Network for Robust 3D Object Detection from Radar Point Cloud and Monocular Image
• 2021-milliEye: A Lightweight mmWave Radar and Camera Fusion System for Robust Object Detection
• 2021-CFTrack: Center-based Radar and Camera Fusion for 3D Multi-Object Tracking
• 2021-3D Detection and Tracking for On-road Vehicles with a Monovision Camera and Dual Low-cost 4D mmWave Radars

• 2020-Radar as a Teacher: Weakly Supervised Vehicle Detection using Radar Labels
• 2021-RODNet: A Real-Time Radar Object Detection Network Cross-Supervised by Camera-Radar Fused Object 3D Localization
• 2020-RSS-Net: Weakly-Supervised Multi-Class Semantic Segmentation with FMCW Radar
• 2020-Warping of Radar Data into Camera Image for Cross-Modal Supervision in Automotive Applications
• 2020-Weakly Supervised Deep Learning Method for Vulnerable Road User Detection in FMCW Radar

• 2011-Integrating Millimeter Wave Radar with a Monocular Vision Sensor for On-Road Obstacle Detection Applications
• 2017-Comparative Analysis of RADAR- IR Sensor Fusion Methods for Object Detection
• 2019-People Tracking by Cooperative Fusion of RADAR and Camera Sensors
• 2019-A DNN-LSTM based Target Tracking Approach using mmWave Radar and Camera Sensor Fusion
• Autonomous Obstacle Avoidance for UAV based on Fusion of Radar and Monocular Camera
• 2019-Extending Reliability of mmWave Radar Trackingand Detection via Fusion With Camera
• 2019-People Tracking by Cooperative Fusion ofRADAR and Camera Sensors
• 2019-TargetDetection Algorithm Based on MMW Radar and Camera Fusion
• 2019-A DNN-LSTM based Target Tracking Approachusing mmWave Radar and Camera Sensor Fusion
• 2020-A Roadside Camera-Radar Sensing Fusion System for Intelligent Transportation
• 2020-Cooperative Multi-Sensor Tracking of VulnerableRoad Users in the Presence of Missing Detections
• 2020-Robust Target Detection and Tracking Algorithm Based on Roadside Radar and Camera
• 2021-Full-Velocity Radar Returns by Radar-Camera Fusion

• 2017-Vehicle Tracking Using Extended Object Methods: An Approach for Fusing Radar and Laser
• 2019-Automated Ground Truth Estimation of Vulnerable Road Users in Automotive Radar Data Using GNSS
• 2019-Learning to see through haze: Radar-based Human Detection for Adverse Weather Conditions
• 2020-LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion
• 2020-RadarNet: Exploiting Radar for Robust Perception of Dynamic Objects
• 2021-Robust Multimodal Vehicle Detection in Foggy Weather Using Complementary Lidar and Radar Signals

• 2016-Multiple Sensor Fusion and Classification for Moving Object Detection and Tracking
• 2020-High Dimensional Frustum PointNet for 3D Object Detection from Camera, LiDAR, and Radar
• 2020-Seeing Through FogWithout Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather
• 2021-Radar Voxel Fusion for 3D Object Detection

• 2020-Camera-Radar Fusion for 3-D Depth Reconstruction
• 2021-Depth Estimation from Monocular Images and Sparse Radar Data
• 2021-Radar-Camera Pixel Depth Association for Depth Completion
• 2021-R4Dyn: Exploring Radar for Self-Supervised Monocular Depth Estimation of Dynamic Scenes

• 2010-Road Intensity Based Mapping Using Radar Measurements With a Probability Hypothesis Density Filter
• 2015-Tracking of Extended Objects with High-Resolution Doppler Radar
• 2018-Rfcm for Data Association and Multitarget Tracking Using 3D Radar
• 2018-Classification Assisted Tracking for Autonomous Driving Domain
• 2019-Extended Object Tracking assisted Adaptive Clustering for Radar in Autonomous Driving Applications
• 2020-BAAS: Bayesian Tracking and Fusion Assisted Object Annotation of Radar Sensor Data for Artificial Intelligence Application
• 2020-An RLS-Based Instantaneous Velocity Estimator for Extended Radar Tracking
• 2020-Extended Object Tracking Using Hierarchical Truncation Measurement Model with Automotive Radar
• 2020-Extended Object Tracking Using Spatially Resolved Micro-Doppler Signatures
• 2021-A Graph-Based Track-Before-Detect Algorithm for Automotive Radar Target Detection
• 2021-Learning-Based Extended Object Tracking Using Hierarchical Truncation Measurement Model With Automotive Radar
• 2021-Road-Map Aided GM-PHD Filter for Multi-Vehicle Tracking with Automotive Radar
• 2021-Extended Object Tracking assisted Adaptive Multi-Hypothesis Clustering for Radar in Autonomous Driving Domain