Direction of Arrival Estimation Based on Subband Weighting for Noisy Conditions

In this paper, we present a novel DOA estimation method for human speech using subband weighting. Existing DOA estimation methods still can not perform quite reliably in low SNR condition. To improve the robustness of DOA estimator in noisy environment, we propose a novel DOA estimation approach. Firstly, the speech signal of each channel is passed through a Gammatone filterbank to obtain a set of time-domain subband signals. Secondly, we achieve TDOA estimation based on a new cost function in each subband. Subband weight is calculated to emphasis the estimation results of subbands with high probability containing speech signals. Finally, DOA is determined by the estimated TDOA and geometry of microphone array. Experimental results show that the proposed subband weighting based method outperforms SRP-PHAT and broadband MUSIC algorithm in highly noisy environment.