安徽大学学报（自然科学版）2025，Vol.49Issue(5)：65-74,10.DOI:10.3969/j.issn.1000-2162.2025.05.008
基于EMBFLN的移动声源定位方法
Mobile sound source localization method based on EMBFLN
摘要
Abstract
Aiming at the problem that the accuracy of sound source localization drops sharply when the noise and reverberation are large in the traditional sound source localization method,a method of using eicosahedral multilayer branching feature learning network(EMBLFN)structure is proposed for sound source localization.Firstly,the maximum and minimization operation is introduced on the traditional signal processing method steered response power with phase transform(SRP-PHAT)to obtain the noise and reverberation influence,maximize the response power spectrum after the real transmission path signal,and feed it into the EMBLFN structure as the input of the network.Then,the Mish activation function is applied to the deep learning neural network of sound source localization to smooth the output of the network and improve the generalization ability of the model.Finally,the effectiveness of the proposed method is verified by simulation experiments.In addition,in order to verify the scalability of the proposed model,the model is tested by using the close-range UAV audio data and making a semi-synthetic mobile UAV acoustic scene.关键词
阵列信号处理/声源定位/深度学习/二十面体卷积神经网络Key words
array signal processing/sound source localization/deep learning/icosahedral convolutional neural network分类
数理科学引用本文复制引用
蒋芳,王凯,管灵,董纯柱,陈志菲,许耀华,胡艳军..基于EMBFLN的移动声源定位方法[J].安徽大学学报（自然科学版）,2025,49(5):65-74,10.基金项目
安徽省高校自然科学研究重点项目(2022AH050109) （2022AH050109）
安徽省质量基础设施标准化专项项目(2023MKS10) （2023MKS10）
