"WAVERAD: An mmWave Radar-Centered Multimodal Dataset for Environmental Perception in Inland Waterways"

"WAVERAD is an open-access, multimodal dataset designed for environmental perception and navigation research in inland waterway environments, with a particular focus on the evaluation and development of mmWave radar systems for maritime and riverine applications.The dataset comprises synchronized recordings from two 77 GHz FMCW automotive radar sensors, one Velodyne VLP-32C 3D LiDAR, an inertial measurement unit (IMU), two stereo camera systems, and GNSS. It contains 65 complex scenes with a total of 48,618 frames, recorded over more than five hours along 37 km of the Berlin waterways (River Spree). The data captures diverse and challenging real-world conditions, including ship locks, underpasses, bridges, vessel encounters, container terminals, docking maneuvers, and urban waterfront environments with buildings, sidewalks, and railway infrastructure.In addition to the raw sensor data, WAVERAD provides radar and LiDAR-based environmental maps generated using two approaches: FAST-LIO2, a state-of-the-art LiDAR-based SLAM algorithm used for high-accuracy ground truth and ego-motion estimation and a filtered mapping method, a partially LiDAR-dependent radar mapping approach optimized for inland waterway perception.The dataset structure and organization are illustrated in the accompanying Dataset_Structure diagram."

WAVERAD是一款开源多模态数据集，专为内陆航道环境下的环境感知与导航研究设计，尤其聚焦于海事及内河应用场景中毫米波雷达（mmWave radar）系统的评估与开发。该数据集包含两台77 GHz调频连续波（FMCW）车载雷达传感器、一台Velodyne VLP-32C型3D激光雷达（LiDAR）、一个惯性测量单元（IMU）、两套立体摄像系统以及全球导航卫星系统（GNSS）的同步采集数据。数据集涵盖65个复杂场景，总计48618帧数据，采集时长超5小时，覆盖柏林施普雷河（River Spree）沿线37公里的航道区域。所采集的数据囊括了多样且极具挑战性的真实环境工况，包括船闸、下穿通道、桥梁、船舶交会、集装箱码头、停靠操作，以及包含建筑、人行道与铁路基础设施的城市滨水环境。除原始传感器数据外，WAVERAD还提供基于雷达与激光雷达的环境地图，此类地图通过两种方案生成：一是当前前沿的基于激光雷达的同步定位与地图构建（SLAM）算法FAST-LIO2，用于高精度真实参考值与自运动估计；二是滤波建图方法，该方法属于部分依赖激光雷达的雷达建图方案，专为内陆航道环境感知优化。数据集的结构与组织形式详见随附的Dataset_Structure示意图。