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Acoustic Source Localization via Time Difference of Arrival Estimation for Distributed Sensor Networks Using Tera-Scale Optical Core Devices

机译:使用万亿级光核心设备的分布式传感器网络通过到达时间估计的时差进行声源定位

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摘要

For real-time acoustic source localization applications, one of the primary challenges is the considerablegrowth in computational complexity associated with the emergence of ever larger, activeor passive, distributed sensor networks. These sensors rely heavily on battery-operated systemcomponents to achieve highly functional automation in signal and information processing. In orderto keep communication requirements minimal, it is desirable to perform as much processing onthe receiver platforms as possible. However, the complexity of the calculations needed to achieveaccurate source localization increases dramatically with the size of sensor arrays, resulting in substantial growth of computational requirements that cannot be readily met with standard hardware. One option to meet this challenge builds upon the emergence of digital optical-core devices. Theobjective of this work was to explore the implementation of key building block algorithms used inunderwater source localization on the optical-core digital processing platform recently introducedby Lenslet Inc. This demonstration of considerably faster signal processing capability should beof substantial significance to the design and innovation of future generations of distributed sensornetworks.
机译:对于实时声源定位应用,主要挑战之一是与越来越大的有源或无源分布式传感器网络的出现相关的计算复杂性的显着增长。这些传感器严重依赖电池供电的系统组件,以实现信号和信息处理中的高性能自动化。为了使通信需求最小化,期望在接收器平台上执行尽可能多的处理。但是,实现精确的源定位所需的计算复杂度会随着传感器阵列的大小而急剧增加,从而导致计算需求的大幅增长,而标准硬件无法轻松满足这些需求。应对这一挑战的一种选择是基于数字光核设备的出现。这项工作的目的是在Lenslet Inc.近期推出的光核数字处理平台上探索用于水下源定位的关键构件算法的实现。这种相当快的信号处理能力的证明对未来的设计和创新具有重大意义。几代分布式传感器网络。

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