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首页> 外文期刊>IEEE Transactions on Signal Processing >Simultaneous Ranging and Self-Positioning in Unsynchronized Wireless Acoustic Sensor Networks
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Simultaneous Ranging and Self-Positioning in Unsynchronized Wireless Acoustic Sensor Networks

机译:非同步无线声传感器网络中的同时测距和自定位

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摘要

Automatic ranging and self-positioning is a very desirable property in wireless acoustic sensor networks, where nodes have at least one microphone and one loudspeaker. However, due to environmental noise, interference, and multipath effects, audio-based ranging is a challenging task. This paper presents a fast ranging and positioning strategy that makes use of the correlation properties of pseudonoise sequences for estimating simultaneously relative time-of-arrivals from multiple acoustic nodes. To this end, a proper test signal design adapted to the acoustic node transducers is proposed. In addition, a novel self-interference reduction method and a peak matching algorithm are introduced, allowing for increased accuracy in indoor environments. Synchronization issues are removed by following a BeepBeep strategy, providing range estimates that are converted to absolute node positions by means of multidimensional scaling. The proposed approach is evaluated both with simulated and real experiments under different acoustical conditions. The results using a real network of smartphones and laptops confirm the validity of the proposed approach, reaching an average ranging accuracy below 1 cm.
机译:在无线声传感器网络中,节点具有至少一个麦克风和一个扬声器的情况下,自动测距和自动定位是非常理想的属性。但是,由于环境噪声,干扰和多径效应,基于音频的测距是一项艰巨的任务。本文提出了一种快速测距和定位策略,该策略利用伪噪声序列的相关属性来同时估计多个声学节点的相对到达时间。为此,提出了适合于声节点换能器的适当测试信号设计。此外,还介绍了一种新颖的自干扰减少方法和峰值匹配算法,可提高室内环境的准确性。遵循BeepBeep策略可消除同步问题,该范围可提供范围估计值,并通过多维缩放将其转换为绝对节点位置。在不同的声学条件下,通过模拟和真实实验对提出的方法进行了评估。使用智能手机和笔记本电脑的真实网络进行的结果证实了该方法的有效性,其平均测距精度低于1厘米。

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