Improved signal de-noising in underwater acoustic noise using S-transform: A performance evaluation and comparison with the wavelet transform
Sound waves propagate well underwater making it useful for target locating and communication. Underwater acoustic noise (UWAN) affects the reliability in applications where the noise comes from multiple sources. In this paper, a novel signal de-noising technique is proposed using S-transform. From t...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2017-09-01
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| Series: | Journal of Ocean Engineering and Science |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468013317300049 |
| _version_ | 1818254768846405632 |
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| author | Yasin Yousif Al-Aboosi Ahmad Zuri Sha'ameri |
| author_facet | Yasin Yousif Al-Aboosi Ahmad Zuri Sha'ameri |
| author_sort | Yasin Yousif Al-Aboosi |
| collection | DOAJ |
| description | Sound waves propagate well underwater making it useful for target locating and communication. Underwater acoustic noise (UWAN) affects the reliability in applications where the noise comes from multiple sources. In this paper, a novel signal de-noising technique is proposed using S-transform. From the time–frequency representation, de-noising is performed using soft thresholding with universal threshold estimation which is then reconstructed. The UWAN used for the validation is sea truth data collected at Desaru beach on the eastern shore of Johor in Malaysia with the use of broadband hydrophones. The comparison is made with the more conventionally used wavelet transform de-noising method. Two types of signals are evaluated: fixed frequency signals and time-varying signals. The results demonstrate that the proposed method shows better signal to noise ratio (SNR) by 4 dB and lower root mean square error (RMSE) by 3 dB achieved at the Nyquist sampling frequency compared to the previously proposed de-noising method like wavelet transform. |
| first_indexed | 2024-12-12T17:01:13Z |
| format | Article |
| id | doaj.art-e9a66496c63e4be284b92e68c373333b |
| institution | Directory Open Access Journal |
| issn | 2468-0133 |
| language | English |
| last_indexed | 2024-12-12T17:01:13Z |
| publishDate | 2017-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Ocean Engineering and Science |
| spelling | doaj.art-e9a66496c63e4be284b92e68c373333b2022-12-22T00:18:08ZengElsevierJournal of Ocean Engineering and Science2468-01332017-09-012317218510.1016/j.joes.2017.08.003Improved signal de-noising in underwater acoustic noise using S-transform: A performance evaluation and comparison with the wavelet transformYasin Yousif Al-Aboosi0Ahmad Zuri Sha'ameri1Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai 81300, Johor, MalaysiaFaculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai 81300, Johor, MalaysiaSound waves propagate well underwater making it useful for target locating and communication. Underwater acoustic noise (UWAN) affects the reliability in applications where the noise comes from multiple sources. In this paper, a novel signal de-noising technique is proposed using S-transform. From the time–frequency representation, de-noising is performed using soft thresholding with universal threshold estimation which is then reconstructed. The UWAN used for the validation is sea truth data collected at Desaru beach on the eastern shore of Johor in Malaysia with the use of broadband hydrophones. The comparison is made with the more conventionally used wavelet transform de-noising method. Two types of signals are evaluated: fixed frequency signals and time-varying signals. The results demonstrate that the proposed method shows better signal to noise ratio (SNR) by 4 dB and lower root mean square error (RMSE) by 3 dB achieved at the Nyquist sampling frequency compared to the previously proposed de-noising method like wavelet transform.http://www.sciencedirect.com/science/article/pii/S2468013317300049Underwater acoustic noiseTime–frequency analysisWavelet transformsS-transformsSignal de-noising |
| spellingShingle | Yasin Yousif Al-Aboosi Ahmad Zuri Sha'ameri Improved signal de-noising in underwater acoustic noise using S-transform: A performance evaluation and comparison with the wavelet transform Journal of Ocean Engineering and Science Underwater acoustic noise Time–frequency analysis Wavelet transforms S-transforms Signal de-noising |
| title | Improved signal de-noising in underwater acoustic noise using S-transform: A performance evaluation and comparison with the wavelet transform |
| title_full | Improved signal de-noising in underwater acoustic noise using S-transform: A performance evaluation and comparison with the wavelet transform |
| title_fullStr | Improved signal de-noising in underwater acoustic noise using S-transform: A performance evaluation and comparison with the wavelet transform |
| title_full_unstemmed | Improved signal de-noising in underwater acoustic noise using S-transform: A performance evaluation and comparison with the wavelet transform |
| title_short | Improved signal de-noising in underwater acoustic noise using S-transform: A performance evaluation and comparison with the wavelet transform |
| title_sort | improved signal de noising in underwater acoustic noise using s transform a performance evaluation and comparison with the wavelet transform |
| topic | Underwater acoustic noise Time–frequency analysis Wavelet transforms S-transforms Signal de-noising |
| url | http://www.sciencedirect.com/science/article/pii/S2468013317300049 |
| work_keys_str_mv | AT yasinyousifalaboosi improvedsignaldenoisinginunderwateracousticnoiseusingstransformaperformanceevaluationandcomparisonwiththewavelettransform AT ahmadzurishaameri improvedsignaldenoisinginunderwateracousticnoiseusingstransformaperformanceevaluationandcomparisonwiththewavelettransform |