测试技术学报2025，Vol.39Issue(4)：475-482,490,9.DOI:10.62756/csjs.1671-7449.2025058
基于复值卷积降噪自编码器去噪的矢量水听器DOA估计方法
Vector Hydrophone DOA Estimation Method Based on Complex-Valued Convolutional Denoising Autoencoder Denoising
摘要
Abstract
To address the existing shortcomings of the real valued convolutional neural network based esti-mation of vector hydrophone direction of arrival(DOA)that does not adequately extract the phase features of the signals received by the array,a vector hydrophone DOA estimation method(CV-CDAE-CNN)based on combination of complex-valued convolutional denoising autoencoder(CV-CDAE)and complex-valued convolutional neural network(CV-CNN)is proposed.The complex-valued covariance matrix of the received signals from the vector hydrophone are firstly input into the CV-CDAE module to remove the noise,and then the denoised samples are input into the CV-CNN for classification.The double-scale dila-tion convolution is used to increase the receptive field of the feature map of CV-CNN before down-sampling and to mitigate the information loss caused by down-sampling.Angle classification is realized by CV-CDAE denoising and CV-CNN's unique way of dealing with complex values,and then DOA esti-mates are obtained.Simulation results show that the proposed method in this paper has stronger general-ization ability,higher DOA estimation accuracy and higher estimation accuracy compared with the existing CV-CNN at low signal-to-noise ratio or limited number of snapshots.关键词
波达方向估计/复值卷积降噪自编码器/复值卷积神经网络/双尺度膨胀卷积/矢量水听器Key words
direction-of-arrival estimation/complex-valued convolutional denoising autoencoder/convolu-tional neural network/double-scale dilation convolution/vector hydrophone分类
信息技术与安全科学引用本文复制引用
任晶,谭秀辉,白艳萍,王宏妍,续婷,程蓉..基于复值卷积降噪自编码器去噪的矢量水听器DOA估计方法[J].测试技术学报,2025,39(4):475-482,490,9.基金项目
国家自然科学基金资助项目(61774137) （61774137）
山西省基础研究计划资助项目(202103021224195,202103021224212,202103021223189,20210302123019) （202103021224195,202103021224212,202103021223189,20210302123019）
山西省回国留学人员科研资助项目(2020-104,2021-108) （2020-104,2021-108）
