2021/03/02 by Shelly Vishwakarma, Vishwakarma, Shelly, Wenda Li +9
Engineering · #Advanced SAR Imaging Techniques #FOS: Electrical engineering #Microwave Imaging and Scattering Analysis #Radar Systems and Signal Processing #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2103.01677
openalex publication_date 2021/03/02 · openalex created_date 2021/03/15 · openalex updated_date 2026/07/28
This work presents a simulation framework to generate human micro-Dopplers in WiFi based passive radar scenarios, wherein we simulate IEEE 802.11g complaint WiFi transmissions using MATLAB's WLAN toolbox and human animation models derived from a marker-based motion capture system. We integrate WiFi transmission signals with the human animation data to generate the micro-Doppler features that incorporate the diversity of human motion characteristics, and the sensor parameters. In this paper, we consider five human activities. We uniformly benchmark the classification performance of multiple machine learning and deep learning models against a common dataset. Further, we validate the classification performance using the real radar data captured simultaneously with the motion capture system. We present experimental results using simulations and measurements demonstrating good classification accuracy of ≥ 95% and ≈ 90%, respectively.