基于相干态的非持续声活动无线声传感器网络的长期同步

Aleksej Chinaev, Niklas Knaepper, G. Enzner
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引用次数: 0

摘要

采样精确的节点同步是必要的,以使声学传感器网络的合作和增强信号采集的全部潜力。虽然传感器的时空效用度量是传感器节点成功聚集的关键,例如,执行声音定位或波束形成,但基于波形的采样率偏移(SRO)评估和补偿也是如此。因此,本文提出了一种声学相干状态(ACS)度量来支持SRO估计系统,以整合由于非持续声活动和几何多样性而产生的各种效用估计。具体来说,我们考虑了在开环和闭环结构中具有SRO估计和补偿的系统,并概述了嵌入基于acs的传感器实用程序的体系结构。在这两种情况下,声学相干度量在端到端同步性能方面比语音或声音活动检测器更合适。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Long-Term Synchronization of Wireless Acoustic Sensor Networks with Nonpersistent Acoustic Activity Using Coherence State
Sample-accurate synchronization of nodes is required to enable the full potential of acoustic sensor networks for cooperative and enhanced signal acquisition. While metrics of spatio-temporal sensor utility are key to successful aggregation of sensor nodes, for instance, to perform sound localization or beamforming, the same is true for waveform-based assessment and compensation of sampling-rate offset (SRO). This paper therefore proposes an acoustic coherence state (ACS) metric to support systems for SRO estimation to integrate estimations of various utility due to nonpersistent acoustic activity and geometrical diversity. Specifically, we consider systems with SRO estimation and compensation in open- and closed-loop structures and outline the architectures for embedding ACS-based sensor utility. It is demonstrated in both cases that the acoustic coherence metric is more appropriate in terms of end-to-end synchronization performance than voice or sound activity detectors.
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