Research on feature extraction of ship-radiated noise based on multi-scale reverse dispersion entropy

Li, Yuxing; Jiao, Shangbin; Geng, Bo; Zhou, Yuan

doi:10.1016/j.apacoust.2020.107737

Cited by 31 publications

(10 citation statements)

References 24 publications

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“…The SlEn algorithm has only five symbol patterns, which makes it easy to implement. The calculation process of SlEn is as follows [ 35 ]:…”

Section: Slope Entropymentioning

confidence: 99%

“…In 2016, DE was proposed for the first time; this can quantify the uncertainty of time series, detect the noise bandwidth and simultaneous frequency and amplitude change [ 33 ]. In the next three years, some improved algorithms (MDE, FDE, and RDE) of DE were proposed, and their performances for SNS feature extraction have proved better than DE [ 34 , 35 ].…”

Section: Introductionmentioning

confidence: 99%

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Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy

Gao

Tang

et al. 2021

Entropy

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In order to accurately identify various types of ships and develop coastal defenses, a single feature extraction method based on slope entropy (SlEn) and a double feature extraction method based on SlEn combined with permutation entropy (SlEn&PE) are proposed. Firstly, SlEn is used for the feature extraction of ship-radiated noise signal (SNS) compared with permutation entropy (PE), dispersion entropy (DE), fluctuation dispersion entropy (FDE), and reverse dispersion entropy (RDE), so that the effectiveness of SlEn is verified, and SlEn has the highest recognition rate calculated by the k-Nearest Neighbor (KNN) algorithm. Secondly, SlEn is combined with PE, DE, FDE, and RDE, respectively, to extract the feature of SNS for a higher recognition rate, and SlEn&PE has the highest recognition rate after the calculation of the KNN algorithm. Lastly, the recognition rates of SlEn and SlEn&PE are compared, and the recognition rates of SlEn&PE are higher than SlEn by 4.22%. Therefore, the double feature extraction method proposed in this paper is more effective in the application of ship type recognition.

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“…The SlEn algorithm has only five symbol patterns, which makes it easy to implement. The calculation process of SlEn is as follows [ 35 ]:…”

Section: Slope Entropymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy

Gao

Tang

et al. 2021

Entropy

Self Cite

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“…Thus, it is necessary to propose a new detection model for underwater acoustic detection. Especially, some weak signals are too weak in energy, and they cannot be effectively extracted from the line spectrum [ 23 , 24 , 25 , 26 , 27 ]. Based on the above potential problems in weak signal underwater acoustic detection, a new chaos system model that can be applied in the detection of the chaotic weak signal is proposed in this paper.…”

Section: Introductionmentioning

confidence: 99%

Detection Line Spectrum of Ship Radiated Noise Based on a New 3D Chaotic System

Wang

Liu

2021

Sensors

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This paper proposes a new detection model of a weak signal based on a third-order chaotic system. Using a dynamic analysis tool, such as the Lyapunov exponent and the bifurcation diagram, variations of dynamic behavior can be observed, and the weak signal underwater can be picked up. In order to improve the observability of detection signals in the time domain and frequency domain, the spectral entropy complexity algorithm (SE) and C0 complexity algorithms are used to analyze and extract the weak signal. The experimental results show that the spectrum extraction based on the complexity algorithm can accurately reflect the dynamic characteristics of the detected signal. It provides the theoretical direction and experimental data support for the application of the chaotic system in the field of acoustic detection.

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“…Entropy, as one of the parameters representing the state of matter in thermodynamics, is a powerful metric of the degree of chaos, complexity, or disorder in time series, such as permutation entropy (PE), approximate entropy (AE), sample entropy (SE), fuzzy entropy (FE), and their improved and multi-scale ones [ 11 , 12 , 13 , 14 , 15 , 16 ]. However, as a fast and powerful symbolization method, PE has attracted much attention from researchers due to the unique advantages of the advantages of high efficiency and simple calculation [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

“…Most of the traditional feature extraction methods for ship-radiated noise are based on frequency or energy, for example, the aforementioned feature extraction schemes based on CEEMDAN and VMD, their superior performance in the extraction of ship-radiated noise has been confirmed in [ 35 , 36 ]. However, compared with these traditional feature extraction methods, the entropy-based feature extraction method can extract the complexity of the ship-radiated noise, and has better performance at distinguishing between different ships [ 14 ], such as PE, RPE, and WPE. In this paper, we apply RCMRWPE to the artificial random signals and actual underwater acoustic signals, and propose an underwater acoustic signal feature extraction scheme based on RCMRWPE.…”

Section: Introductionmentioning

confidence: 99%

Refined Composite Multi-Scale Reverse Weighted Permutation Entropy and Its Applications in Ship-Radiated Noise

Geng

Jiao

2021

Entropy

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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) has the advantages of high efficiency and simple calculation. However, PE has the problems of missing amplitude information and single scale. To address the two drawbacks, refined composite multi-scale reverse weighted PE (RCMRWPE), as a novel measurement technology of describing the signal complexity, is put forward based on refined composite multi-scale processing (RCMP) and reverse weighted PE (RWPE). RCMP is an improved method of coarse-graining, which not only solves the problem of single scale, but also improves the stability of traditional coarse-graining; RWPE has been proposed more recently, and has better inter-class separability and robustness performance to noise than PE, weighted PE (WPE), and reverse PE (RPE). Additionally, a feature extraction scheme of ship-radiated noise is proposed based on RCMRWPE, furthermore, RCMRWPE is combined with discriminant analysis classifier (DAC) to form a new classification method. After that, a large number of comparative experiments of feature extraction schemes and classification methods with two artificial random signals and six ship-radiated noise are carried out, which show that the proposed feature extraction scheme has better performance in distinguishing ability and stability than the other three similar feature extraction schemes based on multi-scale PE (MPE), multi-scale WPE (MWPE), and multi-scale RPE (MRPE), and the proposed classification method also has the highest recognition rate.

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Research on feature extraction of ship-radiated noise based on multi-scale reverse dispersion entropy

Cited by 31 publications

References 24 publications

Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy

Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy

Detection Line Spectrum of Ship Radiated Noise Based on a New 3D Chaotic System

Refined Composite Multi-Scale Reverse Weighted Permutation Entropy and Its Applications in Ship-Radiated Noise

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