构建可校准的毫米波雷达信号级数字孪生平台，实现真实测量与仿真数据对齐。
mmRadarTwin: A Measurement-Calibrated Signal-Level Digital Twin Platform for Indoor mmWave Radar
- 基于物理路径建模，将雷达实测与Unreal Engine场景仿真通过接收通道对齐。
- 在154个姿态下复现70.8%的有效响应区域，暴露弱路径缺失等误差来源。
- 适合雷达系统开发、仿真验证与故障诊断，尤其适用于室内感知研究。
室内毫米波雷达感知难以复现，因其测得的范围-角度响应受场景几何、材料特性、多径效应、硬件规范及信号处理影响。现有射线追踪与数字孪生工具多输出渲染、信道或路径级数据，而雷达感知需能与真实FMCW测量在同一域中处理的复杂信号产物。本文提出mmRadarTwin，一个面向室内毫米波雷达的信号级、路径标注型数字孪生平台。该平台通过共享接收信道与范围-角度处理接口，将真实雷达测量分支与Unreal Engine场景仿真分支相连。仿真器生成复数多通道接收网格，并导出每条路径的贡献记录，包含目标体、材料标签、传播事件及输出区间支持信息。我们在办公室部署中使用商用单站毫米波雷达与移动场景采集设备进行评估。在22个雷达位置、154个测量姿态下，当前仅基于物理路径的模拟器在中心可用视场内复现了70.8%的测量有效响应区域，同时揭示了弱路径缺失、响应偏移、不支持锚点及物理机制缺失等残差来源。mmRadarTwin不追求完整雷达图重建或跨房间泛化，而是建立了一套实用的系统工作流，用于构建、对比与诊断室内雷达数字孪生。
原文摘要 · Abstract (English)
Indoor mmWave radar perception is difficult to reproduce because measured range-angle responses depend on scene geometry, material response, multipath, hardware conventions, and signal processing. Existing ray-tracing and digital-twin tools often expose rendering, channel, or path-level quantities, while radar sensing requires complex signal products that can be processed and compared in the same domain as real FMCW measurements. We present mmRadarTwin, a signal-level and path-attributed digital-twin platform for indoor mmWave radar. mmRadarTwin links a real radar measurement branch with an Unreal Engine scene-simulation branch through a shared receive-channel and range-angle processing interface. The simulator writes complex multi-channel receive grids and exports per-path contribution records that identify the actor, material tag, propagation event, and output-bin support of each simulated return. We evaluate mmRadarTwin in an office deployment using a commodity monostatic mmWave radar and mobile scene-capture hardware. Across 154 measured poses spanning 22 radar locations, the current physics-only path-basis simulator recalls 70.8% of measurement-active geometry-supported response regions in the central usable field of view while exposing residuals caused by weak or missing path support, shifted responses, unsupported anchors, and missing physical mechanisms. Rather than claiming complete radar-map reconstruction or cross-room generalization, mmRadarTwin establishes a practical systems workflow for constructing, comparing, and diagnosing indoor radar digital twins.
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