Weighted average frequency algorithm for Hilbert–Huang spectrum and its application to micro-Doppler estimation

For micro-Doppler estimation, an innovative Hilbert–Huang transform (HHT)-based instantaneous frequencies estimator approach designated as weighted average frequency algorithm (WAFA) is proposed in this study. The algorithm is a smoothing of adjacent instantaneous frequencies with a normal rectangular window. After achieving Hilbert–Huang spectrum of the signal, weighted average frequencies and amplitudes are then computed to determine the corresponding point on the time–frequency space, based on which micro-Doppler can be finally estimated. This proposed algorithm of micro-Doppler estimation has been successfully applied to experimental cone and human data.