A self-noise cancellation method for unmanned underwater vehicle based on sparse shrinkage algorithm

Unmanned underwater vehicles (UUV) is affected by various types of noise during the passive detection process. One of main components of noise are UUV's self-noise. In this paper, we proposes a sparse shrinkage interference cancellation method combining UUV self-noise distribution characteristi...

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Bibliographic Details
Published inOCEANS 2019 - Marseille pp. 1 - 4
Main Authors Ju, Donghao, Li, Yu, Huang, Haining
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2019
Subjects
Data models
Estimation
Interference
Matching pursuit algorithms
Noise reduction
Signal processing
Signal to noise ratio
sparse shrinkage
threshold function
Transforms
underwater unmanned vehicle
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Summary:Unmanned underwater vehicles (UUV) is affected by various types of noise during the passive detection process. One of main components of noise are UUV's self-noise. In this paper, we proposes a sparse shrinkage interference cancellation method combining UUV self-noise distribution characteristics. The method uses an adaptive contraction function combined with the SURE threshold. The experimental results show that the proposed method has better denoising effect than the other existing methods. In addition, the algorithm we proposed in this papper is also applied to actual data processing, which improves the signal-to-noise ratio of the signal while preserving the singularity of the signal.
DOI:10.1109/OCEANSE.2019.8867506