(3) Improved signal de-noising in underwater acoustic noise using S-transform: A performance evaluation and comparison with the wavelet transform

Yasin Yousif Al-Aboosi ^{a , b , ∗} , Ahmad Zuri Sha’ameri ^a
a Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai 81300, Johor, Malaysia

b Faculty of Engineering, University of Mustansiriyah, Baghdad, Iraq

Received 15 March 2017; accepted 8 August 2017
Available online 13 August 2017

Abstract
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.
© 2017 Shanghai Jiaotong University. Published by Elsevier B.V.
This is an open access article under the CC BY-NC-ND license. ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )
Keywords: Underwater acoustic noise; Time–frequency analysis; Wavelet transforms; S-transforms; Signal de-noising.