Time-Synchronization for Coherent Digital Signal Processing in Wireless Acoustic Sensor Networks

无线声学传感器网络中相干数字信号处理的时间同步

• 批准号: 318597153
• 负责人: Professor Dr.-Ing. Gerald Enzner
• 金额: --
• 依托单位: Lehrstuhl für Multimediakommunikation und Signalverarbeitung
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/318597153?language=en
• 关键词: Time; Synchronization; Coherent; Digital; Signal

With the advent of smart home technology, acoustic sensor networks (ASN) have made a huge step from niche application to home appliance. Within an ASN, sensor nodes are not per se synchronized since individual oscillators in the nodes inevitably introduce a sampling-rate offset (SRO). Even small SROs in the order of parts per million may be detrimental to typical audio processing involving multiple nodes such as beamforming or source localization. Over a longer time period, small SROs will further accumulate substantial signal drifts that result in entirely asynchronous audio streams. Sampling rate synchronization is, hence, a crucial component for signal processing tasks in ASNs. In this project extension within the Research Unit (RU) "Acoustic Sensor Networks", we consider the dynamics that result from smart home settings as both challenge and opportunity for synchronization. In line with the overarching goals of the RU, we introduce the reliability of estimated SROs to reflect how well a particular acoustical scene lends itself to further signal processing. With several pairwise estimates obtained over time, we then fuse the information based on the reliability to obtain more stable synchronization in the long run. Furthermore, we extend the perspective from synchronizing two sensor nodes to an arbitrary number of nodes within a smart home by applying the fusion across the ASN. The 'Acoustic Map' foreseen in the RU acts as an interface to provide synchronization for other projects within the RU and allows high-level information to be exploited in order to facilitate synchronization efforts.

随着智能家居技术的出现，声传感器网络从小众应用向家用电器迈出了巨大的一步。在传感器网络中，传感器节点本身并不同步，因为节点中的各个振荡器不可避免地引入了采样率偏移（SRO）。即使是百万分之几量级的小SRO也可能对涉及多个节点的典型音频处理（诸如波束成形或源定位）有害。在较长的时间段内，小的SRO将进一步积累大量的信号漂移，导致完全异步的音频流。因此，采样率同步是ASN中信号处理任务的关键组成部分。在研究单位（RU）“声学传感器网络”的这个项目扩展中，我们认为智能家居设置产生的动态既是同步的挑战，也是同步的机会。根据RU的总体目标，我们引入了估计的SRO的可靠性，以反映一个特定的声学场景如何适合于进一步的信号处理。随着时间的推移，我们得到了几个成对的估计，然后融合的信息的基础上的可靠性，以获得更稳定的同步在长期运行。此外，我们扩展的角度从同步两个传感器节点到任意数量的节点在一个智能家居通过应用融合跨越的传感器。RU中预见的“声学地图”作为一个接口，为RU内的其他项目提供同步，并允许利用高级信息，以促进同步工作。