Accelerated steered response power method for sound source localization via clustering search  

作　　者：ZHAO XiaoYan TANG Jie ZHOU Lin WU ZhenYang 

机构地区：[1]Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education,Southeast University

出　　处：《Science China(Physics,Mechanics & Astronomy)》2013年第7期1329-1338,共10页中国科学：物理学、力学、天文学（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant Nos. 60971098 and 61201345);the Beijing Key Laboratory of Advanced Information Science and Network Technology(Grant No.XDXX1308)

摘　　要：The steered response power-phase transform (SRP-PHAT) sound source localization algorithm is robust in a real environment. However, the large computation complexity limits the practical application of SRP-PHAT. For a microphone array, each location corresponds to a set of time differences of arrival (TDOAs), and this paper collects them into a TDOA vector. Since the TDOA vectors in the adjacent regions are similar, we present a fast algorithm based on clustering search to reduce the computation complexity of SRP-PHAT. In the training stage, the K-means or Iterative Self-Organizing Data Analysis Technique (ISODATA) clustering algorithm is used to find the centroid in each cluster with similar TDOA vectors. In the procedure of sound localization, the optimal cluster is found by comparing the steered response powers (SRPs) of all centroids. The SRPs of all candidate locations in the optimal cluster are compared to localize the sound source. Experiments both in simulation environments and real environments have been performed to compare the localization accuracy and computational load of the proposed method with those of the conventional SRP-PHAT algorithm. The results show that the proposed method is able to reduce the computational load drastically and maintains almost the same localization accuracy and robustness as those of the conventional SRP-PHAT algorithm. The difference in localization performance brought by different clustering algorithms used in the training stage is trivial.The steered response power-phase transform （SRP-PHAT） sound source localization algorithm is robust in a real environment. However, the large computation complexity limits the practical application of SRP-PHAT. For a microphone array, each location corresponds to a set of time differences of arrival （TDOAs）, and this paper collects them into a TDOA vector. Since the TDOA vectors in the adjacent regions are similar, we present a fast algorithm based on clustering search to reduce the computation complexity of SRP-PHAT. In the training stage, the K-means or Iterative Self-Organizing Data Analysis Technique （ISODATA） clustering algorithm is used to find the centroid in each cluster with similar TDOA vectors. In the procedure of sound localization, the optimal cluster is found by comparing the steered response powers （SRPs） of all centroids. The SRPs of all candidate locations in the optimal cluster are compared to localize the sound source. Experiments both in simulation environments and real environments have been performed to compare the localization accuracy and computational load of the proposed method with those of the conventional SRP-PHAT algorithm. The results show that the proposed method is able to reduce the computational load drastically and maintains almost the same localization accuracy and robustness as those of the conventional SRP-PHAT algorithm. The difference in localization performance brought by different clustering algorithms used in the training stage is trivial.

关 键 词：sound source localization microphone array steered response power clustering search 

分 类 号：TN912.3[电子电信—通信与信息系统]