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Decentralized acoustic source localization in a distributed sensor network

机译:分布式传感器网络中的分散声源定位

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The purpose of this work is to investigate acoustic source localization algorithms suitable for use with distributed sensor networks. Traditional sensor networks employ a central controller; however centralized data processing in large-scale sensor networks is not always desirable because of the excessive communication and computational complexity it requires. Therefore, fully distributed localization algorithms are considered. The most important aspect of these algorithms is that they be scalable for use in large sensor networks. The scalability is achieved by forming sensor nodes into groups which collaborate to locate sources. Source locations are determined from time of arrival (TOA) information of the acoustic wave front. Two source location solution methods are used: least squares (LS) and Tikhonov regularized inversion (RI). Experimental results validate the accuracy of a distributed localization approach, and the effectiveness of the LS and RI methods are compared. Additionally, important parameters of the distributed localization algorithm are considered.
机译:这项工作的目的是研究适用于分布式传感器网络的声源定位算法。传统的传感器网络采用中央控制器。然而,由于需要过多的通信和计算复杂性,因此并不总是希望在大型传感器网络中进行集中式数据处理。因此,考虑了完全分布式的定位算法。这些算法最重要的方面是它们可扩展以用于大型传感器网络。可伸缩性是通过将传感器节点形成可协作定位源的组来实现的。源位置根据声波前的到达时间(TOA)信息确定。使用两种源定位解决方法:最小二乘法(LS)和Tikhonov正则化反演(RI)。实验结果验证了分布式定位方法的准确性,并比较了LS和RI方法的有效性。另外,考虑了分布式定位算法的重要参数。

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