Source localization is one of the major research contents in the localization research of wireless sensor networks, which has\nattracted considerable attention for a long period. In recent years, the wireless binary sensor network (WBSN) has been widely\nused for source localization due to its high energy efficiency. A novel method which is based on WBSN for multiple source\nlocalization is presented in this paper. Firstly, the Neyman-Pearson criterion-based sensing model which takes into account the\nfalse alarms is utilized to identify the alarmed nodes. Secondly, the mean shift and hierarchical clustering method are performed\non the alarmed nodes to obtain the cluster centers as the initial locations of signal sources. Finally, some voting matrices which\ncan improve the localization accuracy are constructed to decide the location of each acoustic source. The simulation results\ndemonstrate that the proposed method can provide a desirable performance superior to some traditional methods in accuracy\nand efficiency.
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