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Acoustic Sensor Networks for Woodpecker Localization

机译:用于啄木鸟定位的声学传感器网络

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Sensor network technology can revolutionize the study of animal ecology by providing a means of non-intrusive, simultaneous monitoring of interaction among multiple animals. In this paper, we investigate design, analysis, and testing of acoustic arrays for localizing acorn woodpeckers using their vocalizations. Each acoustic array consists of four microphones arranged in a square. All four audio channels within the same acoustic array are finely synchronized within a few micro seconds. We apply the approximate maximum likelihood (AML) method to synchronized audio channels of each acoustic array for estimating the direction-of-arrival (DOA) of woodpecker vocalizations. The woodpecker location is estimated by applying least square (LS) methods to DOA bearing crossings of multiple acoustic arrays. We have revealed the critical relation between microphone spacing of acoustic arrays and robustness of beamforming of woodpecker vocalizations. Woodpecker localization experiments using robust array element spacing in different types of environments are conducted and compared. Practical issues about calibration of acoustic array orientation are also discussed.
机译:传感器网络技术可以通过提供一种非侵入性的,同时监视多种动物之间相互作用的方式,彻底改变动物生态学研究。在本文中,我们研究了使用声学阵列对橡果啄木鸟进行定位的声学阵列的设计,分析和测试。每个声学阵列均由四个以正方形排列的麦克风组成。同一声学阵列中的所有四个音频通道都可以在几微秒内精确同步。我们将近似最大似然(AML)方法应用于每个声学阵列的同步音频通道,以估计啄木鸟发声的到达方向(DOA)。通过将最小二乘(LS)方法应用于多个声学阵列的DOA轴承交叉点,可以估计啄木鸟的位置。我们已经揭示了声学阵列的麦克风间距和啄木鸟发声的波束形成的鲁棒性之间的关键关系。进行并比较了在不同类型的环境中使用鲁棒的阵列元素间距进行的啄木鸟定位实验。还讨论了有关声学阵列方向校准的实际问题。

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