Abstract

Direction-of-arrival (DOA) estimation method based on single-source zone (SSZ) detection, using the sparsity of speech signal, which transforms the multiple sources localization into single source localization. However, there are many time-frequency (TF) points whose direction information are far away from the true DOA in the detected SSZ, these points may disturb the localization performance. Aiming this issue, a DOA estimation of multiple sources based on the angle distribution of TF points is proposed in this paper. Firstly, the SSZs are detected through the recorded signal of sound field microphone. Secondly, the optimized single-source zone (OSSZ) can be acquired by removing the outliers based on the angle distribution of the TF points in the detected SSZ. Thirdly, DOA histogram can be obtained using the TF points in OSSZ, then the envelop of the DOA histogram is gained by kernel density estimation. Finally, peak search is adopted to obtain the DOA estimates and number of sources. The experiment results show that the proposed method can achieve better localization performance than SSZ-based method under medium and high reverberation conditions.

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