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Over the last years, millimeter-wave radars have been established as automotive sensors. Generally, radars deal better than optical sensing modalities with adverse weather conditions, with the main drawback being the angular resolution. To increase robustness toward fog or heavy rain, full autonomous driving requires radar systems to achieve higher angular reso-lution. Sparse array radar is a practical approach to achieving higher angular resolution while managing the drawbacks. Despite sparse radar systems acquiring less measurement data, the possibility of a stronger degradation of the performance in adverse weather conditions usually is not considered. The work shown in this paper attempts to close this gap by evaluating experimental data of sparse array radar acquired in a specialized rain chamber to model heavy rain under realistic but controllable conditions.
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Kawaguchi et al. (Mon,) studied this question.
www.synapsesocial.com/papers/68e6b5f5b6db6435876372d0 — DOI: https://doi.org/10.1109/radarconf2458775.2024.10548312
Takuya Kawaguchi
Kazuki Shinotsuka
Stefan Malterer
Infineon Technologies (Germany)
Fujikura (Japan)
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