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EURASIP Journal on Advances in Signal ProcessingTarget identification of ship-radiated noise is a crucial area in underwater target recognition. However, there is currently a lack of multi-target ship datasets that accurately represent real-world underwater acoustic conditions.
Xiaoyang Du, Feng Hong
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Entropy, 2021 Ship-radiated noise is one of the important signal types under the complex ocean background, which can well reflect physical properties of ships. As one of the valid measures to characterize the complexity of ship-radiated noise, permutation entropy (PE)
Yuxing Li, Bo Geng, Shangbin Jiao
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A survey on machine learning in ship radiated noise
Ocean EngineeringThe utilization of machine learning in analyzing ship radiated noise (SR-N) is undergoing rapid evolution. Because the omnipresent background noise strongly depends on the highly variable environment, the application of such techniques poses challenges. Furthermore, publicly available labeled datasets are scarce.
Sandjai Bhulai
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Ship-Radiated Noise Separation in Underwater Acoustic Environments Using a Deep Time-Domain Network
Journal of Marine Science and EngineeringShip-radiated noise separation is critical in both military and economic domains. However, due to the complex underwater environments with multiple noise sources and reverberation, separating ship-radiated noise poses a significant challenge ...
Qunyi He +3 more
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Ship Radiated Noise Recognition Using Resonance-Based Sparse Signal Decomposition [PDF]
Shock and Vibration, 2017 Under the complex oceanic environment, robust and effective feature extraction is the key issue of ship radiated noise recognition. Since traditional feature extraction methods are susceptible to the inevitable environmental noise, the type of vessels ...
Jiaquan Yan +4 more
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Research on Feature Extraction of Ship-Radiated Noise Based on Multiscale Fuzzy Dispersion Entropy
Journal of Marine Science and Engineering, 2023 In recent years, fuzzy dispersion entropy (FDE) has been proposed and used in the feature extraction of various types of signals. However, FDE can only analyze a signal from a single time scale during practical application and ignores some important ...
Yuxing Li +3 more
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Entropy, 2019 Sea environment complexity and underwater acoustic channels make it hard to extract features of ship-radiated noise signals. This paper presents a novel feature extraction method using the advantages of variational mode decomposition (VMD), fluctuation ...
Hong Yang, Ke Zhao, Guohui Li
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Entropy, 2016 In order to solve the problem of feature extraction of underwater acoustic signals in complex ocean environment, a new method for feature extraction from ship-radiated noise is presented based on empirical mode decomposition theory and permutation ...
Yu-Xing Li +3 more
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Resonance-Based Time-Frequency Manifold for Feature Extraction of Ship-Radiated Noise
Sensors, 2018 In this paper, a novel time-frequency signature using resonance-based sparse signal decomposition (RSSD), phase space reconstruction (PSR), time-frequency distribution (TFD) and manifold learning is proposed for feature extraction of ship-radiated noise,
Jiaquan Yan +4 more
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An Underwater Acoustic Target Recognition Method Based on Spectrograms with Different Resolutions
Journal of Marine Science and Engineering, 2021 This paper focuses on the automatic target recognition (ATR) method based on ship-radiated noise and proposes an underwater acoustic target recognition (UATR) method based on ResNet.
Xinwei Luo +4 more
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