Minimum Entropy-Based Acoustic Source Localization with Laplace Distribution

摘要：

Accurate and fast localization of acoustic sources is a problem that is of significant interest in applications such as conference systems, gunshot localization systems. Recently, approaches that based on the time difference of arrival(TDOA) are becoming popular, despite the computational expenses. The TDOA localization algorithms contain two parts: the time delay estimation(TDE) algorithms and space search algorithms. The most important TDE algorithms are based on the generalized cross-correlation(GCC) method. These algorithms perform reasonably well when reverberation or noise is not too high. Lots of improved algorithms are proposed, such as SRP-PHAT. In this article, we show that acoustic source localization with Laplace Distribution can be developed on a basis of minimum entropy (ME). For traditional grid search is too expensive for a real-time system, we propose using stochastic region contraction(SRC) to make computing the ME practical. Results from simulation experiences show excellent accuracy of the ME-SRC algorithm.

关键词： acoustic source localization minimum entropy stochastic region contraction Laplace Distribution

作者: Liu Ying Liu Jianping Zhang Yiwen

作者单位: Department of communication engineering, Engineering College of CAPF, Xi’an, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 498-501

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）