Doppler-Aware Odometry from FMCW Scanning Radar

- 1 min read

Abstract

This work explores Doppler information from a millimetre-Wave (mm-W) Frequency-Modulated Continuous-Wave (FMCW) scanning radar to make odometry estimation more robust and accurate. Firstly, doppler information is added to the scan masking process to enhance correlative scan matching. Secondly, we train a Neural Network (NN) for regressing forward velocity directly from a single radar scan; we fuse this estimate with the correlative scan matching estimate and show improved robustness to bad estimates caused by challenging environment geometries, e.g. narrow tunnels. We test our method with a novel custom dataset which is released with this work at https://ori.ox.ac.uk/publications/datasets.

Paper: https://doi.org/10.1109/itsc57777.2023.10422412

Preprint: https://arxiv.org/abs/2308.10597

Bibtex

@inproceedings{dopplerawareodometry2023,
  author={Rennie, Fraser and Williams, David and Newman, Paul and De Martini, Daniele},
  title={Doppler-Aware Odometry from FMCW Scanning Radar},
  year={2023},
  booktitle={2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)},
  pages={5126--5132},
  doi={10.1109/itsc57777.2023.10422412},
  url={https://doi.org/10.1109/itsc57777.2023.10422412},
}