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Collection and Processing of Acoustic and Seismic Array Data for Source Localizaton

机译:收集和处理声震阵列数据以进行源定位

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Distributed sensor networks have been proposed for a wide range of applications. In this paper, our goal is to locate a wideband source, generating both acoustic and seismic signals, using both seismic and acoustic sensors. For a far-field acoustic source, only the direction-of-arrival (DOA) in the coordinate system of the sensors is observable. We use the approximate Maximum-Likelihood (AML) method for DOA estimations from several acoustic arrays. For a seismic source, we use data collected at a single tri-axial accelerometer to perform DOA estimation. Two seismic DOA estimation methods, the eigen-decomposition of the sample covariance matrix method and the surface wave method are used. Field measurements of acoustic and seismic signals generated by vertically striking a heavy metal plate placed on the ground in an open field are collected. Each acoustic array uses four low-cost microphones placed in a square configuration and separated by one meter. The microphone outputs of each array are collected by a synchronized A/D recording system and processed locally based on the AML algorithm for DOA estimation. An array of six tri-axial accelerometers arranged in two rows whose outputs are fed into an ultra low power and high resolution network-aware seismic recording system. Field measured data from the acoustic and seismic arrays show the estimated DOAs and consequent localizations of the source are quite accurate and useful.
机译:已经提出了分布式传感器网络用于广泛的应用。在本文中,我们的目标是使用地震和声学传感器定位宽带源,同时产生声音和地震信号。对于远场声源,只能观察到传感器坐标系中的到达方向(DOA)。我们使用近似最大似然(AML)方法从几个声学阵列进行DOA估计。对于地震源,我们使用在单个三轴加速度计上收集的数据来进行DOA估计。使用了两种地震DOA估计方法:样本协方差矩阵的特征分解法和表面波方法。收集通过在空旷地区垂直撞击放置在地面上的重金属板而产生的声音和地震信号的现场测量结果。每个声学阵列都使用四个低成本麦克风,这些麦克风呈正方形放置,相隔一米。每个阵列的麦克风输出由同步的A / D记录系统收集,并根据用于DOA估计的AML算法在本地进行处理。六个六轴三轴加速度计的阵列,分为两行,其输出馈入超低功耗和高分辨率的网络感知地震记录系统。来自声波阵列和地震阵列的现场测量数据表明,估计的DOA以及源的后续定位非常准确和有用。

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