IMT Atlantique Bretagne-Pays de la Loire, Plouzane 29280, France.
Acoustics Research Centre, Department of Mechanical Engineering, The University of Auckland, Auckland 1010, New Zealand.
J Acoust Soc Am. 2019 Dec;146(6):4650. doi: 10.1121/1.5138593.
Bird localisation using passive acoustic methods is a non-intrusive solution for taking a census of bird species. Through the recordings from a microphone array, the generalised cross-correlation with phase transform (GCC-PHAT) has been adopted widely in the estimation of the direction-of-arrival (DOA) of audio signals especially speech in indoor environments, as it performs very well in a reverberant environment. However, the performance is degraded when the signal to noise ratio is low. This study investigates the performance of DOA estimation when the GCC-PHAT is applied in the wavelet domain. Three configurations are considered in this study and the performance of these configurations is assessed by numerical simulation under ideal setup and practical experiments using audio signals recorded in a typical native forest in New Zealand. The results suggest the configuration which applies GCC-PHAT and denoising in the wavelet domain and estimates DOA from the reconstructed cross-correlation can give more accurate estimation compared to the conventional GCC-PHAT.
使用被动声学方法进行鸟类定位是对鸟类物种进行普查的一种非侵入性解决方案。通过麦克风阵列的录音，广义互相关相位变换（GCC-PHAT）已广泛应用于音频信号，特别是在室内环境中的语音到达方向（DOA）估计中，因为它在混响环境中表现非常出色。然而，当信噪比较低时，性能会下降。本研究探讨了将 GCC-PHAT 应用于小波域时 DOA 估计的性能。本研究考虑了三种配置，并通过数值模拟和在新西兰典型原生林记录的音频信号进行的实际实验评估了这些配置的性能。结果表明，与传统的 GCC-PHAT 相比，将 GCC-PHAT 和小波域去噪应用于估计 DOA 的重建互相关的配置可以提供更准确的估计。
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