2023/04/12 by John Kobak, Bennett J. Richman, Kobak, John +5
Engineering · #Advanced SAR Imaging Techniques #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Non-Invasive Vital Sign Monitoring #Radar Systems and Signal Processing #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2304.06173
openalex publication_date 2023/04/12 · openalex created_date 2023/04/15 · openalex updated_date 2026/07/28
The prompt and accurate recognition of Continuous Human Activity (CHAR) is critical in identifying and responding to health events, particularly fall risk assessment. In this paper, we examine a multi-antenna radar system that can process radar data returns for multiple individuals in an indoor setting, enabling CHAR for multiple subjects. This requires combining spatial and temporal signal processing techniques through micro-Doppler (MD) analysis and high-resolution receive beamforming. We employ delay and sum beamforming to capture MD signatures at three different directions of observation. As MD images may contain multiple activities, we segment the three MD signatures using an STA/LTA algorithm. MD segmentation ensures that each MD segment represents a single human motion activity. Finally, the segmented MD image is resized and processed through a convolutional neural network (CNN) to classify motion against each MD segment.