声传感器网络中的节点效用盲评估算法
doi: 10.3724/SP.J.1146.2012.01715
Blind Assessment of Microphone Utility in a Wireless Acoustic Sensor Network
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摘要: 在麦克风节点分散布置的无线声传感器网络中,麦克风节点子集的选择通常是依据节点接收信号的质量好坏。然而在节点和声源位置、源信号、噪声信号都未知的情况下很难对其进行评估。对此,该文提出一种只依赖麦克风接收数据的节点效用盲评估算法。该算法基于频域信号的高阶统计信息(峭度)与信噪比间的关系,将接收信号各频点峭度值的加权和作为节点的效用值。仿真实验结果表明,该盲评估算法能有效地评估节点接收信号质量的好坏,评估结果与理论信噪比基本一致。Abstract: In a wireless acoustic sensor network where microphones are distributedly scattered, the microphone subset selection is usually based on the quality of the received signals on the microphones. However, it is difficult to evaluate it without knowing about the nodes and the sound sources position, the source signal and the noise signals. In this paper, a novel algorithm is proposed depending only on the received data for assessing microphone utility blindly. The algorithm exploits the relationship between the SNR and the signals higher-order statistical information (kurtosis) in frequency domain and the microphone utility is a weighted sum of the kurtosis of each frequency bin. The experimental results show that the proposed algorithm can effectively evaluate the quality of the received signals and get the comparable performance with the true SNR.
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