Tytuł artykułu

Single Vector Hydrophone DOA Estimation: Leveraging Deep Learning with CNN-CBAM

Tytuł czasopisma

Archives of Acoustics

Rocznik

2025

Wolumin

vol. 50

Numer

No 2

Autorzy

Zeng, Fanyu ; Han, Yaning ; Yang, Hongyuan ; Yang, Dapeng ; Zheng, Fan

Afiliacje

Zeng, Fanyu : Key Laboratory of Geophysical Exploration Equipment, Ministry of Education,College of Instrumentation and Electrical Engineering, Jilin UniversityChangchun, China ; Han, Yaning : Key Laboratory of Geophysical Exploration Equipment, Ministry of Education,College of Instrumentation and Electrical Engineering, Jilin UniversityChangchun, China ; Yang, Hongyuan : Key Laboratory of Geophysical Exploration Equipment, Ministry of Education,College of Instrumentation and Electrical Engineering, Jilin UniversityChangchun, China ; Yang, Dapeng : Key Laboratory of Geophysical Exploration Equipment, Ministry of Education,College of Instrumentation and Electrical Engineering, Jilin UniversityChangchun, China ; Zheng, Fan : Key Laboratory of Geophysical Exploration Equipment, Ministry of Education,College of Instrumentation and Electrical Engineering, Jilin UniversityChangchun, China

Słowa kluczowe

single vector hydrophone ; direction of arrival (DOA) ; convolutional neural network (CNN) ; convolutionalblock attention module (CBAM) ; noise resistance

Wydział PAN

Nauki Techniczne

Wydawca

Polish Academy of Sciences, Institute of Fundamental Technological Research, Committee on Acoustics

Data

5.05.2025

Typ

Article

Identyfikator

DOI: 10.24425/aoa.2025.153659 ; ISSN 0137-5075 ; eISSN 2300-262X