Do We Need to Compensate for Motion Distortion and Doppler Effects in Spinning Radar Navigation?

TL;DR

This paper investigates the impact of motion distortion and Doppler effects on spinning radar navigation, demonstrating their significance and proposing a lightweight estimator to improve odometry accuracy in high-speed scenarios.

Contribution

It is the first to analyze and quantify the effects of motion distortion and Doppler effects on spinning radar odometry and localization, proposing an estimator that accounts for both.

Findings

Motion distortion significantly affects radar odometry accuracy.

Doppler effects are less prominent but still relevant.

The proposed estimator improves navigation performance.

Abstract

In order to tackle the challenge of unfavorable weather conditions such as rain and snow, radar is being revisited as a parallel sensing modality to vision and lidar. Recent works have made tremendous progress in applying spinning radar to odometry and place recognition. However, these works have so far ignored the impact of motion distortion and Doppler effects on spinning-radar-based navigation, which may be significant in the self-driving car domain where speeds can be high. In this work, we demonstrate the effect of these distortions on radar odometry using the Oxford Radar RobotCar Dataset and metric localization using our own data-taking platform. We revisit a lightweight estimator that can recover the motion between a pair of radar scans while accounting for both effects. Our conclusion is that both motion distortion and the Doppler effect are significant in different aspects of spinning radar navigation, with the former more prominent than the latter. Code for this project can be found at: https://github.com/keenan-burnett/yeti_radar_odometry