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

中文翻译：

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无线二进制传感器网络中基于均值漂移的多源定位方法

源定位是无线传感器网络定位研究的主要研究内容之一，长期以来引起了人们的广泛关注。近年来，由于其高能量效率，无线二进制传感器网络（WBSN）已被广泛用于源定位。提出了一种基于WBSN的多源定位新方法。首先，考虑错误警报的基于Neyman-Pearson准则的传感模型被用来识别被警告的节点。其次，对报警节点进行均值平移和分层聚类，得到聚类中心作为信号源的初始位置。最后，构建一些可以提高定位精度的投票矩阵来决定每个声源的位置。仿真结果表明，所提方法在准确性和效率上都可以提供优于传统方法的理想性能。