Landmark-based Vehicle Self-Localization Using Automotive Polarimetric Radars
<|reference_start|>Landmark-based Vehicle Self-Localization Using Automotive Polarimetric Radars: Automotive self-localization is an essential task for any automated driving function. This means that the vehicle has to reliably know its position and orientation with an accuracy of a few centimeters and degrees, respectively. This paper presents a radar-based approach to self-localization, which exploits fully polarimetric scattering information for robust landmark detection. The proposed method requires no input from sensors other than radar during localization for a given map. By association of landmark observations with map landmarks, the vehicle's position is inferred. Abstract point- and line-shaped landmarks allow for compact map sizes and, in combination with the factor graph formulation used, for an efficient implementation. Evaluation of extensive real-world experiments in diverse environments shows a promising overall localization performance of $0.12 \text{m}$ RMS absolute trajectory and $0.43 {}^\circ$ RMS heading error by leveraging the polarimetric information. A comparison of the performance of different levels of polarimetric information proves the advantage in challenging scenarios.<|reference_end|>
@article{weishaupt2024landmark-based,
    title={Landmark-based Vehicle Self-Localization Using Automotive Polarimetric
  Radars},
    author={Fabio Weishaupt, Julius F. Tilly, Nils Appenrodt, Pascal Fischer,
  J"urgen Dickmann, Dirk Heberling},
    journal={arXiv preprint arXiv:2408.05811},
    year={2024},
    doi={10.1109/TITS.2024.3397075},
    archivePrefix={arXiv},
    eprint={2408.05811},
    primaryClass={cs.RO eess.SP}
}