Noise assisted multivariate empirical mode decomposition applied to Doppler radar data

The operation of the noise-assisted multivariate empirical mode decomposition (NA-MEMD) algorithm, which represents a breakthrough in data-adaptive analysis, is illustrated for the time-frequency analysis of Doppler radar signals. The performance of the NA-MEMD is here compared to the continuous wavelet transform, for both synthetic and real-world data applications, showing the advantage of the noise-assisted concept in terms of sparse time-frequency localization. For the considered application, we show how the approach gives a clear and natural interpretation of Doppler radar phenomena and enables the accurate tracking of object speeds.