Hilbert–Huang transform analysis of human activities using through-wall noise and noise-like radar

Various parts of the human body have different movements when a person is performing different physical activities. There is a need to remotely detect and recognise specific human activities for applications involving anti-terrorism, hostage liberation and search-and-rescue. An ultrawideband noise radar system has been built to detect signatures of human activities. The Hilbert–Huang transform, which is used to extract the human-induced Doppler frequency shift from the received signal, facilitates the identification and recognition of various human activities. A non-stationary Doppler model is developed to describe various aspects of human motion, which compares well with measured data. The theoretical analysis and experimental results are discussed.