Multi-source localization by using offset residual weight

EURASIP Journal on Audio, Speech, and Music Processing

Changchun Bao¹  Shang Gao¹  Maoshen Jia¹ 

[1] School of Information and Communication Engineering, Faculty of Information Technology, Beijing University of Technology, 100124, Beijing, China;

关键词: Multiple sound sources localization;    Direction of arrival estimation;    Reverberation;    Soundfield microphone;   

DOI  :  10.1186/s13636-021-00211-w

来源: Springer

【 摘 要 】

Multiple sound source localization is a hot issue of concern in recent years. The Single Source Zone (SSZ) based localization methods achieve good performance due to the detection and utilization of the Time-Frequency (T-F) zone where only one source is dominant. However, some T-F points consisting of components from multiple sources are also included in the detected SSZ sometimes. Once a T-F point in SSZ is contributed by multiple components, this point is defined as an outlier. The existence of outliers within the detected SSZ is usually an unavoidable problem for SSZ-based methods. To solve this problem, a multi-source localization by using offset residual weight is proposed in this paper. In this method, an assumption is developed: the direction estimated by all the T-F points within the detected SSZ has a difference along with the actual direction of sources. But this difference is much smaller than the difference between the directions estimated by the outliers along with the actual source localization. After verifying this assumption experimentally, Point Offset Residual Weight (PORW) and Source Offset Residual Weight (SORW) are proposed to reduce the influence of outliers on the localization results. Then, a composite weight is formed by combining PORW and SORW, which can effectively distinguish the outliers and desired points. After that, the outliers are removed by composite weight. Finally, a statistical histogram of DOA estimation with outliers removed is used for multi-source localization. The objective evaluation of the proposed method is conducted in various simulated environments. The results show that the proposed method achieves a better performance compared with the reference methods in sources localization.

【 授权许可】

CC BY