Radar is highlighted for robust sensing capabilities in adverse weather conditions (e.g. dense fog, heavy rain, or snowfall). In addition, Radar can cover wide areas and penetrate small particles. Despite these advantages, Radar-based place recognition remains in the early stages compared to other sensors due to its unique characteristics such as low resolution, and significant noise. In this paper, we propose a Radarbased place recognition utilizing a descriptor called ReFeree using a feature and free space. Unlike traditional methods, we overwhelmingly summarize the Radar image. Despite being lightweight, it contains semi-metric information and is also outstanding from the perspective of place recognition performance. For concrete validation, we test a single session from the MulRan dataset and a multi-session from the Oxford Offroad Radar, Oxford Radar RobotCar, and the Boreas dataset.

翻译：雷达因其在恶劣天气条件下（如浓雾、暴雨或降雪）的鲁棒感知能力而备受关注。此外，雷达能够覆盖广阔区域并穿透微小颗粒。尽管具备这些优势，但由于其低分辨率、显著噪声等独特特性，基于雷达的地点识别相较于其他传感器仍处于早期发展阶段。本文提出一种基于雷达的地点识别方法，该方法利用一种名为ReFeree的描述符，该描述符结合了特征与自由空间信息。与传统方法不同，我们以极高的效率对雷达图像进行概括。尽管该描述符结构轻量，但它包含了半度量信息，并且从地点识别性能的角度来看也表现优异。为进行具体验证，我们在MulRan数据集的单次会话数据，以及Oxford Offroad Radar、Oxford Radar RobotCar和Boreas数据集的多会话数据上进行了测试。