The complexities of the marine environment and the unique characteristics of underwater channels pose challenges in obtaining reliable signals underwater,necessitating the filtration of underwater acoustic noise.Herei...The complexities of the marine environment and the unique characteristics of underwater channels pose challenges in obtaining reliable signals underwater,necessitating the filtration of underwater acoustic noise.Herein,an underwater acoustic signal denoising method based on ensemble empirical mode decomposition(EEMD),correlation coefficient(CC),permutation entropy(PE),and wavelet threshold denoising(WTD)is proposed.Furthermore,simulation experiments are conducted using simulated and real underwater acoustic data.The experimental results reveal that the proposed denoising method outperforms other previous methods in terms of signal-to-noise ratio,root mean square error,and CC.The proposed method eliminates noise and retains valuable information in the signal.展开更多
基金Supported by the National Natural Science Foundation of China(No.62033011)Science and Technology Project of Hebei Province(No.216Z1704G,No.20310401D)。
文摘The complexities of the marine environment and the unique characteristics of underwater channels pose challenges in obtaining reliable signals underwater,necessitating the filtration of underwater acoustic noise.Herein,an underwater acoustic signal denoising method based on ensemble empirical mode decomposition(EEMD),correlation coefficient(CC),permutation entropy(PE),and wavelet threshold denoising(WTD)is proposed.Furthermore,simulation experiments are conducted using simulated and real underwater acoustic data.The experimental results reveal that the proposed denoising method outperforms other previous methods in terms of signal-to-noise ratio,root mean square error,and CC.The proposed method eliminates noise and retains valuable information in the signal.
基金This research is supported by the Key Project of the National Natural Science Foundation of China under Grant No. 10631070, the National Natural Science Foundation of China under Grant Nos. 10801112, 10971223, 11071252, and the Ph.D Graduate Start Research Foundation of Xinjiang University Funded Project under Grant No. BS080101. Thank Dr. Yong Wang from Institute of Systems Science, Academy of Mathematics and Systems Science for kind discussion and good suggestions.