# RadHARSimulator V1: Model-Based FMCW Radar Human Activity Recognition Simulator

arXiv: https://arxiv.org/abs/2509.06751 · HTML: https://mlsanity.com/paper/2509.06751/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Sep 2025.

## Built on by (most cited first, 3 of 3)

- [RadHARSimulator V2: Video to Doppler Generator](https://mlsanity.com/paper/2511.09022/) (2025)
- [Represent Micro-Doppler Signature in Orders](https://mlsanity.com/paper/2602.12985/) (2026)
- [Generalization Theory for Through-the-Wall Radar Human Activity Recognition](https://mlsanity.com/paper/2607.08144/) (2026)

## Abstract (arXiv)

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.