Abstract

Doppler spectrogram analysis of the human gait is a useful tool for discriminating various microDoppler tracks due to the movements of different body parts. A data-dependent algorithm, namely the short-time iterative adaptive approach, is used to obtain a more accurate spectrogram than the one provided by the conventional short-time Fourier transform-based approaches. The performance of the approaches is demonstrated and contrasted using both simulated and measured human gait data.

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