Covert Underwater Acoustic Channel-sensing Technique using Marine Mammal Whistles

The exposure of sound sources presents a major ob-stacle for active sonar and communication sonar systems. Herein, we introduce a unified framework that uses the linear sparse model for reconstructing marine mammal whistles, leveraging this signal for covertly sensing underwater acoustic channels. I...

Full description

Saved in:
Bibliographic Details
Published in2024 OES China Ocean Acoustics (COA) pp. 1 - 6
Main Authors Cang, Siyuan, Sheng, Xueli, Dong, Hang, Cui, Xiaoming, Li, Chao, Yang, Huayong
Format Conference Proceeding
LanguageEnglish
Published IEEE 29.05.2024
Subjects
Channel Sensing
Chirp
Data models
Estimation
Huber
M-estimate
Marine Mammal
Noise
Oceans
Sensors
Sonar
Underwater
Underwater acoustics
Whistle
Online AccessGet full text

Cover

More Information
Summary:The exposure of sound sources presents a major ob-stacle for active sonar and communication sonar systems. Herein, we introduce a unified framework that uses the linear sparse model for reconstructing marine mammal whistles, leveraging this signal for covertly sensing underwater acoustic channels. In addition, the linear sparse model can accurately reconstruct the channel. In dealing with non-Gaussian noise, a Huber loss penalty is used to optimize the sparse estimator. Using simulations and experimental data collected from the South China Sea, the effectiveness of the proposed algorithm is demonstrated.
DOI:10.1109/COA58979.2024.10723376