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Distributed Source Localization in Acoustic Sensor Networks Using the Coherent-to-Diffuse Power Ratio

机译:使用相干扩散功率比的声传感器网络中的分布式源定位

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摘要

In this paper, acoustic source localization in an acoustic sensor network (ASN) based on estimates of the coherent-to-diffuse power ratio (CDR) is investigated. It is shown that the CDR reflects the distance between an acoustic source and an observing microphone pair in real-world acoustic enclosures. As this relation is dependent on various physical parameters of the given acoustic environment which are unknown in practice, we estimate it by Gaussian process regression. Subsequently, the obtained distance estimates are used by an ASN with known relative node positions for estimating the position of the acoustic source. The algorithm is designed in a completely distributed fashion, i.e., no fusion center is needed. The computational complexity of the proposed algorithm is low and the amount of data to be shared between the sensor nodes is small and can be adjusted to the constraints imposed on the network by using a sparse Gaussian process regression method. A simulation study confirms, employing also real measurement data in a low-reverberant room, the efficacy of the proposed algorithm for a multitude of scenarios.
机译:本文研究了基于相干扩散功率比(CDR)估计的声传感器网络(ASN)中的声源定位。结果表明,CDR反映了真实声学外壳中声源与观察麦克风对之间的距离。由于这种关系取决于实际中未知的给定声学环境的各种物理参数,因此我们通过高斯过程回归对其进行估计。随后,获得的距离估计值将由具有已知相对节点位置的ASN使用,以估计声源的位置。该算法以完全分布式的方式设计,即不需要融合中心。所提出算法的计算复杂度低,并且传感器节点之间共享的数据量很小,并且可以使用稀疏的高斯过程回归方法来调整以适应网络上的约束。仿真研究证实,在低混响室内也采用真实的测量数据,该算法在多种情况下的功效。

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