Doppler Correspondence: Outlier-Robust Correspondence Estimation Based on Doppler Velocity

Abstract

Achieving successful scan matching is essential for LiDAR odometry. However, in challenging environ- ments with adverse weather conditions or repetitive geometric patterns, LiDAR odometry performance is degraded due to incorrect scan matching. Recently, the emergence of frequency-modulated continu- ous wave 4D LiDAR and 4D radar technologies have provided the potential to address these unfavorable conditions. The term 4D refers to point cloud data characterized by range, azimuth, and elevation along with Doppler velocity. Although 4D data is available, most scan matching methods for 4D LiDAR and 4D radar still establish correspondence by repeatedly identifying the closest points between consecutive scans, overlooking the Doppler information. This paper introduces, for the first time, a simple Doppler velocity-based correspondence—Doppler Correspondence—that is invariant to translation and small rotation of the sensor, with its geometric and kinematic foundations. Extensive experiments demon- strate that the proposed method enables the direct matching of consecutive point clouds without an iterative process, making it (i) computationally efficient. Additionally, it provides a more (ii) robust cor- respondence estimation in environments with repetitive geometric patterns and (iii) maintains reliable performance even with extreme outlier rates reaching up to 90%. The implementation of our proposed method is publicly available at https://github.com/Tars0523/Doppler_Correspondence.