2025/09/08 by Gao, Weicheng · 1 citation
Engineering · Health Professions · #68T45 #Advanced SAR Imaging Techniques #FOS: Electrical engineering #I.5.4 #Non-Invasive Vital Sign Monitoring #Occupational Health and Performance #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2509.06751
openalex publication_date 2025/09/08 · openalex created_date 2025/10/11 · openalex updated_date 2026/07/28
Radar-based human activity recognition (HAR) is a pivotal research area for applications requiring non-invasive monitoring. However, the acquisition of diverse and high-fidelity radar datasets for robust algorithm development remains a significant challenge. To overcome this bottleneck, a model-based frequency-modulated continuous wave (FMCW) radar HAR simulator is developed. The simulator integrates an anthropometrically scaled 13-scatterer kinematic model to simulate 12 distinct activities. The FMCW radar echo model is employed, which incorporates dynamic radar cross-section (RCS), free-space or through-the-wall propagation, and a calibrated noise floor to ensure signal fidelity. The simulated raw data is then processed through a complete pipeline, including moving target indication (MTI), bulk Doppler compensation, and Savitzky-Golay denoising, culminating in the generation of high-resolution range-time map (RTM) and Doppler-time maps (DTMs) via both short-time Fourier transform (STFT) and Fourier synchrosqueezed transform (FSST). Finally, a novel neural network method is proposed to validate the effectiveness of the radar HAR. Numerical experiments demonstrate that the simulator successfully generates high-fidelity and distinct micro-Doppler signature, which provides a valuable tool for radar HAR algorithm design and validation. The installer of this simulator is released at: https://github.com/JoeyBGOfficial/RadHARSimulatorV1-Model-Based-FMCW-Radar-Human-Activity-Recognition-Simulator.