论文/arXiv 2609.22742·1 个月前

分布式ISAC赋能的缺失二维LiDAR测量多模态恢复

针对二维LiDAR扫描缺失区域恢复，提出分布式ISAC框架融合60-GHz波束训练与LiDAR，并在室内测量中验证。

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原文链接：Distributed ISAC-Enabled Multimodal Recovery of Missing 2-D LiDAR Measurements（arXiv 2609.22742 · 发布日期：2026-09-19）

Distributed ISAC-Enabled Multimodal Recovery of Missing 2-D LiDAR Measurements

针对二维LiDAR扫描缺失区域恢复，提出分布式ISAC框架融合60-GHz波束训练与LiDAR，并在室内测量中验证。

核心要点

• LiDAR单独重建依赖缺失区周边测量，扇区增大或几何复杂时会退化。
• 方法利用多接收器60-GHz定向波束训练，构建RF表面先验并与LiDAR融合。
• 室内实验含55个接收视点、37,620个波束对功率测量和72个缺失案例。
• 80度缺失扇区中，RF+polar融合将MAE由2.271 m降至0.617 m；少量波束对下仍可恢复。

验证范围与局限：仅在室内环境、55个接收视点和72个受控缺失扇区案例上评估。

英文摘要 (Abstract)

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.

作者：Mohammed E. Eltayeb

来源

本页事实对应的公开页面，以原文为准。

1. arXiv 2609.22742：Distributed ISAC-Enabled Multimodal Recovery of Missing 2-D LiDAR Measurements访问 2026-10-21