Convolutive source separation and selective null beamforming using a pilot-based channel estimation technique

In this paper, we propose new convolutive source separation and selective null beamforming methods using a pilot-based channel estimation technique in reverberation environments. First, we show convolutive sound source separation methods in determined and overdetermined cases. For the acoustic channel estimation, we propose a new channel estimation method using pilot sequence conceptually similar to a pilot code in wireless communication. Pilot sequence is composed of sum of sinusoidal sequences at frequencies matching STFT (Short-Time Fourier Transform) frequencies. Proposed channel estimation method considered the effect of spectral sampling with frequencies matching STFT frequencies provides precise channel information we want to know and has less computational loads than other competitive methods. After acoustic channel estimation, we can separate the signals from observations using inverse(or pseudo-inverse) operator of estimated channel matrix at each frequency bins. We show the proposed method has better performance than other competitive methods in various measures. Second, we propose selective null beamforming using a pilot-based channel technique. If we use same pilot sequence at each transmitter, we can obtain relative difference of acoustic channel between transmitters as well as between microphone array. From estimated channel information, we can calculate beamforming weight vectors to null the signals at target location and to transmit the signals to desired location without distortion using singular value decomposition at each frequency bins. We evaluate the performance of proposed methods through experiments as well as the computer simulations.