Author

Pu Wang

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Preprint Jul 2026

HybridSim: A Physics-Learning Hybrid Digital Twin for mmWave Human Sensing

High-fidelity simulation of mmWave radar signals for dynamic human motion is valuable for developing radar-based human sensing models; yet collecting accurately labeled measurements for a specific deployment site remains expensive. We present HybridSim, a physics-learning hybrid simulator that synthesizes mmWave radar...

Weitao Xiong, Tianyu Liu, Peng Li et al. · 0 citations

Jul 2026

mmSimPrior: Learning Simulation Priors for Data-Efficient Real-World Generalizable Radar-Based Human Motion Reconstruction

Millimeter-wave (mmWave) radar enables privacy-preserving and illumination-robust human motion reconstruction, but training generalizable models typically requires costly paired radar-motion recordings. Simulation can scale such supervision, yet even physics-based simulators cannot fully reproduce real-world multipath,...

Cheng Guo, Qiming Cao, Sheng-Kai Xu et al. · arXiv.org · 0 citations