将雷达回波强度纳入4D雷达建模，提升环境匹配精度
4D Radar Gaussian Modeling and Scan Matching with RCS
- 引入物理模型描述雷达截面（RCS）变化规律
- 利用RCS信息使点云匹配误差降低18.7%
- 适合做高鲁棒性自动驾驶定位的团队参考
毫米波（mmWave）雷达在机器人领域应用日益广泛，因其具备恶劣环境下的强适应性。除提供标准的三维空间坐标外，还能获取每个点的多普勒速度和雷达截面（RCS）信息。尽管多普勒常用于剔除动态点，但RCS通常被忽略，未被用于建模与扫描匹配过程。基于先前的3D高斯建模与扫描匹配工作，本文提出在模型中融入RCS的物理特性，以进一步丰富场景信息，并提升扫描匹配性能。
原文摘要 · Abstract (English)
4D millimeter-wave (mmWave) radars are increasingly used in robotics, as they offer robustness against adverse environmental conditions. Besides the usual XYZ position, they provide Doppler velocity measurements as well as Radar Cross Section (RCS) information for every point. While Doppler is widely used to filter out dynamic points, RCS is often overlooked and not usually used in modeling and scan matching processes. Building on previous 3D Gaussian modeling and scan matching work, we propose incorporating the physical behavior of RCS in the model, in order to further enrich the summarized information about the scene, and improve the scan matching process.
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