Indoor non‐rhythmic human motion classification using a frequency‐modulated continuous‐wave radar

Human motion classification is widely used in intelligent house, surveillance, search and rescue operation, intelligent house, and elder monitoring. In this study, a frequency‐modulated continuous‐wave radar is utilised to classify non‐rhythmic human motion in an indoor scenario. Both the range and Doppler features are extracted from echo signals for a machine learning classifier subspace K ‐nearest neighbour. Extensive experiments demonstrate its feasibility, and an accuracy rate of 94.2% was achieved in recognition of eight typical non‐rhythmic motions.