Target depth estimation by deep neural network based on acoustic interference structure in deep water-Reference-Cited by-同舟云学术

Target depth estimation by deep neural network based on acoustic interference structure in deep water

Published:2022-03-24 Issue:7 Volume:16 Page:1131-1143
ISSN:1751-8784
Container-title:IET Radar, Sonar & Navigation
language:en
Short-container-title:IET Radar Sonar & Navi

Author:

Guo Yue¹²^ORCID,Duan Rui¹²,Yang Kunde¹²³

Affiliation:

1. School of Marine Science and Technology Northwestern Polytechnical University Xi'an Shaanxi China

2. Key Laboratory of Ocean Acoustics and Sensing (Northwestern Polytechnical University) Ministry of Industry and Information Technology Xi'an Shaanxi China

3. National Key Laboratory of Underwater Information Processing and Control Xi'an Shaanxi China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/rsn2.12248

Reference34 articles.

1. Reliable acoustic path and convergence zone bottom interaction in the Philippine Sea 09 Experiment.

2. Ambient Noise Analysis of Deep-Ocean Measurements in the Northeast Pacific

3. Depth-based signal separation with vertical line arrays in the deep ocean

4. Detection in reverberation using space time adaptive prewhiteners

5. Estimating the delay-Doppler of target echo in a high clutter underwater environment using wideband linear chirp signals: Evaluation of performance with experimental data

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