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Lung sound localization using array of acoustic sensors

机译:使用声学传感器阵列的肺部声音定位

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This paper presents a localization algorithm to detect lung sounds using a circular array of microphones. We use the natural basis functions of propagation waves in height invariant wavefields to form a spatial minimum variance (MV) problem in eigen space. We also derive a Nyquist criteria for localizing sources within a circular region. This Nyquist criteria shows that the radius of the region where sources can be localized is inversely proportional to the frequency of sound. The modified Nyquist criteria can be used for determining the number of sensors required for a given frequency range and radius of region for which sources need to be localized. The results are corroborated by computer simulations.
机译:本文介绍了使用圆形麦克风检测肺部声音的本地化算法。我们使用高度不变波场的传播波的自然基函数在特征空间中形成空间最小方差(MV)问题。我们还导出奈奎斯特标准,用于本地化圆形区域内的源。这个奈奎斯特标准表明,该区域的半径可以定位的区域的半径与声音的频率成反比。修改的奈奎斯特标准可用于确定所需频率范围和所需的区域的传感器的数量来确定所需的区域。结果通过计算机模拟得到证实。

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