In the development of hand gesture based Human to Machine Interface, the Doppler response feature extraction method plays an important role in translating hand gesture of certain information. The Doppler response feature extraction method from hand gesture sign was proposed and designed by combining time and frequency domain analysis. The extraction of the Doppler response features at the time domain is developed by using cross correlation, and the time domain feature is represented by using peak value of cross correlation result and its time shift. The Doppler response feature of frequency domain is extracted by employing a discriminator filter determined by the frequency spectrum observation of Doppler response. The proposed method was employed as a pre-processing for Continuous Wave (CW) radar output signals, which is able to relieve the pattern classification of Doppler response associated with each hand gesture. The simulation and laboratory experiment using HB 100 Doppler radar were performed to investigate the proposed method. The results show that the combination of all three features was capable of differentiating every type of hand gestures movement.
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