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23 September 2019 Intelligent Noise Elimination Algorithm for Marine Communication Based on Cluster Collaboration
Xuhua Wang, Dong Fang, Shichang Wan, Yuanhao Cheng
Author Affiliations +
Abstract

Wang, X.; Fang, D.; Wan, S., and Cheng, Y., 2019. Intelligent noise elimination algorithm for marine communication based on cluster collaboration In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 753–761. Coconut Creek (Florida), ISSN 0749-0208.

In order to overcome the large amount of noise in marine communication and further improve the quality of communication under low SNR, an intelligent noise elimination algorithm based on cluster cooperation is proposed. Firstly, a finite perception congestion model is established, and a noise control strategy based on denoising operator for consistency algorithm is proposed. It is pointed out that when ε (t) is a high order infinite, the consistency algorithm after denoising can control the noise, make the Agent to converge to the original convergence state, and make the center to distribute normally. By frequency modulation, the noisy signal in communication is modulated into the instantaneous frequency of the analytic signal. In view of the non-linear characteristics of the marine communication signal, the cluster collaboration algorithm is realized by using the windowed Wigner-Ville distribution. For the high noise situation, the iterative algorithm can be used until the noise is completely eliminated. Experiments show that the algorithm can effectively eliminate communication noise and has high real-time performance.

©Coastal Education and Research Foundation, Inc. 2019
Xuhua Wang, Dong Fang, Shichang Wan, and Yuanhao Cheng "Intelligent Noise Elimination Algorithm for Marine Communication Based on Cluster Collaboration," Journal of Coastal Research 93(sp1), 753-761, (23 September 2019). https://doi.org/10.2112/SI93-105.1
Received: 29 September 2018; Accepted: 30 April 2019; Published: 23 September 2019
KEYWORDS
cluster collaboration
Crowd cluster model
instantaneous frequency
noise suppression operator
nonlinear characteristics
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