AI 中文总结
本文提出分布式ISAC框架，利用60GHz波束训练测量辅助恢复二维LiDAR缺失区域，通过RF与LiDAR融合，在80度缺失时MAE降低72.8%。
AI 中文摘要
恢复二维LiDAR扫描中的缺失区域对于在环境感知中保持几何意识至关重要。仅依赖LiDAR的重建依赖于缺失区域周围的测量值，并且随着未观测扇区增大或表面几何形状变得更加复杂，重建质量会下降。本文提出了一种分布式集成感知与通信（ISAC）框架，利用来自多个接收器的定向60-GHz波束训练测量来辅助恢复二维LiDAR扫描中的缺失区域。发射器和接收器位置、波束方向以及相对波束功率阈值被用于构建射频导出的表面先验，而无需射频飞行时间测量。随后，将由此得到的射频导出距离估计与LiDAR测量融合，以估计缺失的几何形状。所提出的框架在室内环境中使用LiDAR和60-GHz相控阵测量进行评估，这些测量来自55个接收器视点，包含37,620个波束对功率测量，覆盖72个受控的缺失扇区案例。结果表明，随着缺失扇区宽度的增加，射频辅助重建提供了更大的精度提升。对于本文研究的80度缺失扇区案例，射频+极坐标融合将平均绝对误差（MAE）从极坐标LiDAR插值的2.271米降低到0.617米，相当于减少了72.8%。结果还表明，即使在有限的波束训练下使用更少的波束对测量，也能保持有用的射频辅助恢复。这些发现表明，定向通信测量可以通过为缺失的LiDAR区域提供互补的几何信息来支持环境感知。
英文摘要
Recovering missing regions in 2-D LiDAR scans is crucial for maintaining geometric awareness in environmental sensing. LiDAR-only reconstruction relies on measurements surrounding the missing region and can degrade as the unobserved sector grows or the surface geometry becomes more complex. This paper presents a distributed integrated sensing and communication (ISAC) framework that uses directional 60-GHz beam-training measurements from multiple receivers to assist in the recovery of missing regions in 2-D LiDAR scans. Transmitter and receiver positions, beam directions, and relative beam-power thresholding are used to construct an RF-derived surface prior without requiring RF time-of-flight measurements. The resulting RF-derived range estimates are then fused with LiDAR measurements to estimate the missing geometry. The proposed framework is evaluated in an indoor environment using LiDAR and 60-GHz phased-array measurements from 55 receiver viewpoints comprising 37,620 beam-pair power measurements across 72 controlled missing-sector cases. The results show that RF-assisted reconstruction provides larger accuracy gains as the missing-sector width increases. For the 80-degree missing-sector case investigated in this paper, RF+polar fusion is shown to reduce the mean absolute error (MAE) from 2.271 m for polar LiDAR interpolation to 0.617 m, corresponding to a 72.8% reduction. The results further show that useful RF-assisted recovery can be maintained even with fewer beam-pair measurements under limited beam training. These findings demonstrate that directional communication measurements can support environmental sensing by providing complementary geometric information for missing LiDAR regions.
