3-D Ego-Motion Estimation Using Multi-Channel FMCW Radar

Abstract

The problem of estimating the 3D ego-motion velocity using multi-channel FMCW radar sensors has been studied. For the first time, the problem of ego-motion estimation is treated using radar raw signals. A robust algorithm using multi-channel FMCW radar sensors to instantly determine the complete 3D motion state of the ego-vehicle (i.e., translational speed and rotational speed) is proposed. The angle information of targets is extracted, and then their phase information from different times instances is used to determine vehicle ego-motion through an optimization process. Any pre-processing steps, such as clustering or clutter suppression, are not required. The performance of the algorithm is compared with the state-of-the-art algorithms based on real-world data, and superior performance has been demonstrated. The algorithm proposed can be easily integrated into radar signal processing pipelines for other tasks relevant to autonomous driving.