Application of robust principal component analysis for time domain source separation

Time domain source separation of microphone array signals with non-stationary, impulsive sources using robust principal component analysis (RPCA) is presented. Time domain source separation with RPCA is applied to microphone array signals observing the aeroacoustic emission of a vortex ring interacting with the edge of a semi-infinite half-plane (V/E interaction). An impulsive spherical pressure wave is produced as a by-product of the generation of vortex rings and is observed by all microphones. With non-stationary, impulsive signal features, frequency domain source separation techniques may not sufficiently separate the sources, requiring a time domain approach. Source separation is achieved with RPCA, enabling accurate estimation of V/E source parameters, with theoretical predictions in good agreement. RPCA, in this application, shows improved performance when compared to other time domain source separation methods involving principal component analysis (PCA). RPCA provides a data-driven approach for impulsive source separation, requiring less user intervention than PCA. Furthermore, RPCA source separation enables improved V/E source waveform time series when compared to prior efforts, which utilized signal windows that excluded the impulsive pressure wave signal feature.