A method for extracting the characteristic spectral line from the ship-radiated noises

Wang, Panpan; Zhang, Guojun; Guan, Linggang

doi:10.1109/icsps.2010.5555696

Cited by 3 publications

(4 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The line spectrum is an important feature for judging whether the original signal contains ship radiation noise [3]. Here, we refer to [4] to illustrate the CMS method on extracting line spectrum features.…”

Section: A Cyclic Modulation Spectrum Featurementioning

confidence: 99%

See 1 more Smart Citation

Unsupervised Classification of Hydrophone Signals With an Improved Mel-Frequency Cepstral Coefficient Based on Measured Data Analysis

Yang

Zhou

2019

IEEE Access

View full text Add to dashboard Cite

Recently, passive detection technology has developed the ability to detect surface ships based on the noise emissions recorded by hydrophones, making it possible in some cases to classify surface ships. One of the most concerning issues with ships and underwater targets is the current lack of reliable features for unsupervised classification. To solve this problem, this paper proposes an improved Melfrequency cepstral coefficients (IMFCC) feature for unsupervised clustering of marine targets. As the feature extraction of hydrophone signals rely on preprocessing, the IMFCC adds cyclic modulation spectrum (CMS) and cross-correlation bispectrum (CCB) in the preprocessing module before traditional the Mel-frequency cepstral coefficient process, and the principal component analysis (PCA) is added as the backend processing module. There are four contributions as follows: First, for IMFCC extraction, it combines the advantages of the CMS, CCB, MFCC, and PCA. Second, the two common unsupervised clusters, Gaussian mixture model (GMM) and fuzzy C-means are used to evaluate the CMS, CCB, and several MFCCs-MFCC-vector quantization (MFCC-VQ), MFCC-Gaussian mixture model (MFCC-GMM), TEO-MFCC (Teager Energy Operator based MFCC), and IMFCC. Third, the performances of traditional MFCC, Teager-energy operator (TEO)-MFCC, IMFCC, MFCC-VQ, and MFCC-GMM are discussed under different dimensions, signalto-noise ratios, distances, and depths. Finally, the experimental results prove that the IMFCC method has a strong anti-interference ability and is robust and has a high-success rate for clustering multitarget or different depth targets, which enables the IMFCC to be a reliable feature for unsupervised classification.

show abstract

Section: A Cyclic Modulation Spectrum Featurementioning

confidence: 99%

“…The line spectrum features have been studied extensively and are widely used as a basis for classification due to their periodicity [1]- [3]. These features are usually detected by Detection of Envelope Modulation on Noise…”

Section: Introductionmentioning

confidence: 99%

Unsupervised Classification of Hydrophone Signals With an Improved Mel-Frequency Cepstral Coefficient Based on Measured Data Analysis

Yang

Zhou

2019

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The ship start to make a circular motion around the vector hydrophone at 0°.We take the time from 20s to 50s and estimate the position of the ship by using MUSIC algorithm,it is shown in Figure 8. Date the Figure 8(a) used is the raw data that the target ship collected.Figure8(b) use the date which is filtered by narrow-band.Line spectral analysis method [8] is used by filtering and we pick up the feature line spectrum of the ship then to filter.By comparing Figure 8 (a) (b),it can be known that the vector array can track the ship's track effectively and the tracking will be clearer and the accuracy of the DOA estimation will be higher after filtering.…”

Section: Tracking the Track Of The Targetmentioning

confidence: 99%

Experiment Research on Array Grouped by MEMS Vector Hydrophone

Liu

Jian

Liu

et al. 2014

KEM

View full text Add to dashboard Cite

As a new type of underwater acoustic sensors,the principle of the MEMS hydrophone is introduced in this paper.MUSIC is a algorithm for estimating the parameter of the signal and it has a high resolution.In order to verify DOA estimation performance of MEMS vector array,experiment has been done.the experiments results showed that the MEMS vector array can achieve DOA estimation and track the underwater moving target.thus,it is concluded the feasibility of the MEMS vector array.

show abstract

“…These structural patterns are important for periodic signal detection. The power spectrum of ship radiated noise consists of wide band continuous spectrum and discrete narrow band line spectrum [1]. The former represents random noise' power distribution, while line spectrum contains important signature information related to ship's inherent vibration characteristics.…”

Section: Introductionmentioning

confidence: 99%

Periodic Signal Detection in Ship Radiated Noise

Zheng

Zhao

2014

AMR

View full text Add to dashboard Cite

Periodic signal is abundant in ship radiated noise. Its detection is an important step towards active control of ship’s acoustic signature. Based on power spectrum analysis and DEMON analysis, an approach to detect line spectrum and modulation spectrum of ship radiated noise is proposed. Periodogram method is used for power spectrum estimation. The separation of line and continuous spectrum, false positive removal, and line spectrum merging are conducted to improve the quality of detected characteristic line spectrum. Via DEMON analysis, steady physical characteristics including propeller’s rotational speed and number of blades are obtained. Finally, the effectiveness of the approach is demonstrated by simulation results.

show abstract

A method for extracting the characteristic spectral line from the ship-radiated noises

Cited by 3 publications

References 2 publications

Unsupervised Classification of Hydrophone Signals With an Improved Mel-Frequency Cepstral Coefficient Based on Measured Data Analysis

Unsupervised Classification of Hydrophone Signals With an Improved Mel-Frequency Cepstral Coefficient Based on Measured Data Analysis

Experiment Research on Array Grouped by MEMS Vector Hydrophone

Periodic Signal Detection in Ship Radiated Noise

Contact Info

Product

Resources

About