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arXiv · 2408.05811

Landmark-based Vehicle Self-Localization Using Automotive Polarimetric Radars

Fabio Weishaupt·Julius F. Tilly·Nils Appenrodt·Pascal Fischer·Jürgen Dickmann·Dirk Heberling
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Abstract

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.

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Fabio Weishaupt, Julius F. Tilly, Nils Appenrodt, Pascal Fischer, Jürgen Dickmann, Dirk Heberling. 2024-08-11. Landmark-based Vehicle Self-Localization Using Automotive Polarimetric Radars. https://doi.org/10.1109/tits.2024.3397075

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