# Radar Odometry for Autonomous Ground Vehicles: A Survey of Methods and Datasets

arXiv: https://arxiv.org/abs/2307.07861 · HTML: https://mlsanity.com/paper/2307.07861/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Jul 2023.

## Built on by (most cited first, 6 of 6)

- [Radarize: Enhancing Radar SLAM with Generalizable Doppler-Based Odometry](https://mlsanity.com/paper/2311.11260/) (2023)
- [Pointing the Way: Refining Radar-Lidar Localization Using Learned ICP Weights](https://mlsanity.com/paper/2309.08731/) (2023)
- [Uncertainty-Driven Radar-Inertial Fusion for Instantaneous 3D Ego-Velocity Estimation](https://mlsanity.com/paper/2506.14294/) (2025)
- [Towards Multi-Object-Tracking with Radar on a Fast Moving Vehicle: On the Potential of Processing Radar in the Frequency Domain](https://mlsanity.com/paper/2604.14013/) (2026)
- [Dr-BA: Separable Optimization for Direct Radar Bundle Adjustment & Localization](https://mlsanity.com/paper/2605.07041/) (2026)
- [Image Frame Dynamic Object Segmentation and Ego Motion Estimation using Radar Image Fusion](https://mlsanity.com/paper/2609.22857/) (2026)

## Abstract (arXiv)

Radar odometry has been gaining attention in the last decade. It stands as one of the best solutions for robotic state estimation in unfavorable conditions; conditions where other interoceptive and exteroceptive sensors may fall short. Radars are widely adopted, resilient to weather and illumination, and provide Doppler information which make them very attractive for such tasks. This article presents an extensive survey of the latest work on ground-based radar odometry for autonomous robots. It covers technologies, datasets, metrics, and approaches that have been developed in the last decade in addition to in-depth analysis and categorization of the various methods and techniques applied to tackle this problem. This article concludes with challenges and future recommendations to advance the field of radar odometry making it a great starting point for newcomers and a valuable reference for experienced researchers.