用双正交声呐+激光雷达实现无人船水下到空中无缝三维建图，不依赖卫星信号。
Seabed-to-Sky Mapping of Maritime Environments with a Dual Orthogonal SONAR and LiDAR Sensor Suite
- 双正交声呐融合+激光雷达，无需卫星定位即可建图。
- 实测每秒更新2.65帧地图，2.85帧里程计，跨空水域连续建模。
- 适合水下探测、无人船测绘等需高鲁棒性环境感知的场景。
关键海事基础设施日益需要对水面以上与以下环境的态势感知，但现有「从海底到天空」的建图流程要么依赖易受遮挡或欺骗的GNSS，要么依赖昂贵的测深声呐。本文提出一种统一的、不依赖GNSS的建图系统，通过将激光雷达-惯性测量单元（LiDAR-IMU）与一对正交安装的前视声呐（FLS）融合，从自主水面航行器生成一致的海床至天空地图。在声学侧，我们拓展了正交宽孔径融合方法，以处理任意声呐间平移（支持异构、非共位模型），并从每个FLS提取前沿形成线扫描；在建图侧，修改LIO-SAM，通过运动插值姿态，在关键帧及之间注入立体衍生的3D声呐点和前沿线扫描，使稀疏声学更新持续贡献于单一因子图地图。我们在哥本哈根贝尔韦德雷运河的真实数据上验证该系统，实现约2.65 Hz的地图更新与约2.85 Hz的里程计，生成跨越空气-水体域的统一3D模型。
原文摘要 · Abstract (English)
Critical maritime infrastructure increasingly demands situational awareness both above and below the surface, yet existing ''seabed-to-sky'' mapping pipelines either rely on GNSS (vulnerable to shadowing/spoofing) or expensive bathymetric sonars. We present a unified, GNSS-independent mapping system that fuses LiDAR-IMU with a dual, orthogonally mounted Forward Looking Sonars (FLS) to generate consistent seabed-to-sky maps from an Autonomous Surface Vehicle. On the acoustic side, we extend orthogonal wide-aperture fusion to handle arbitrary inter-sonar translations (enabling heterogeneous, non-co-located models) and extract a leading edge from each FLS to form line-scans. On the mapping side, we modify LIO-SAM to ingest both stereo-derived 3D sonar points and leading-edge line-scans at and between keyframes via motion-interpolated poses, allowing sparse acoustic updates to contribute continuously to a single factor-graph map. We validate the system on real-world data from Belvederekanalen (Copenhagen), demonstrating real-time operation with approx. 2.65 Hz map updates and approx. 2.85 Hz odometry while producing a unified 3D model that spans air-water domains.
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