Open AccessUnderwater magnetic target signal denoising based on modified wavelet decomposition and reconstruction algorithm
Author(s) -
Tao Qin,
pingjun Cao,
yuzhu Zhang,
zhanxin Liu,
Zhengxiang Chen,
xuebin Zhang,
Kai Dou,
Dong Hu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1738/1/012019
Subject(s) - signal (programming language) , algorithm , noise (video) , noise reduction , wavelet , signal to noise ratio (imaging) , signal reconstruction , computer science , underwater , mathematics , artificial intelligence , signal processing , digital signal processing , telecommunications , oceanography , computer hardware , image (mathematics) , programming language , geology
Noise reduction is crucial for magnetic anomaly signal detection of underwater ferromagnetic target. Modified wavelet decomposition and reconstruction algorithm is proposed to suppress the colored noise and improve the signal to noise ratio. Hamming window is employed to make the preprocessed signal continuous. Evaluation index based on signal-to-noise ratio function is selected, wavelet decomposition and reconstruction algorithm iterates adaptively to select the optimal order of decomposition and reconstruction. The experiment result emphasizes that the signal-to-noise ratio of novel algorithm is 71.6dB. In this particle, we provide a new method to improve signal-to-noise ratio and enhance real-time signal processing for underwater target magnetic anomaly signal detection.