Human Movement Tracking and Fall Detection Using UWB Impulse Radar

Non-contact medical monitoring is an emerging challenging field. In this paper, based on the single chip radar development kit of XeThru X4 ultra wideband (UWB) modules, a small radar system is systematically designed for indoor human body tracking, and fall detection. The algorithms are compared, optimized, and integrated in the system. In signal processing, moving target indication (MTI) and clutter map methods are employed to cancel strong fixed clutter; wavelet analysis is used to denoise and reconstruct the echoes of human breathing and heart-movement; center-of-gravity ranging method is used to detect the presence of human targets and to measure the human range. In data processing, using only the range dimensional measurement, the algorithms for single human target track initialization, track filtering, data association, and track management are designed in a systematic way. Since a normal human body is usually stationary or moving uniformly, a constant-velocity (CV) model is adequately to estimate the human state, and the normalized innovation squared (NIS) is sliding averaged to implement fall judgment. The field data show that the system can effectively detect and track a human body, make timely judgments of human falling and drastic moving changes of state, and extract other vital features.