Abstract
Gaussian/non-Gaussian impulsive noises in underwater acoustic (UWA) channel seriously impact the quality of underwater acoustic communication. The common denoising algorithms are based on Gaussian noise model and are difficult to apply to the coexistence of Gaussian/non-Gaussian impulsive noises. Therefore, a new UWA noise model is described in this paper by combining the symmetric $\alpha$ -stable (S $\alpha$ S) distribution and normal distribution. Furthermore, a novel underwater acoustic signal denoising algorithm called AWMF+GDES is proposed. First, the non-Gaussian impulsive noise is adaptively suppressed by the adaptive window median filter (AWMF). Second, an enhanced wavelet threshold optimization algorithm with a new threshold function is proposed to suppress the Gaussian noise. The optimal threshold parameters are obtained based on good point set and dynamic elite group guidance combined simulated annealing selection artificial bee colony (GDES-ABC) algorithm. The numerical simulations demonstrate that the convergence speed and the convergence precision of the proposed GDES-ABC algorithm can be increased by 25% $\sim$ 66% and 21% $\sim$ 73%, respectively, compared with the existing algorithms. Finally, the experimental results verify the effectiveness of the proposed underwater acoustic signal denoising algorithm and demonstrate that both the proposed wavelet threshold optimization method based on GDES-ABC and the AWMF+GDES algorithm can obtain higher output signal-to-noise ratio (SNR), noise suppression ratio (NSR), and smaller root mean square error (RMSE) compared with the other algorithms.
Highlights
T HE acoustic wave is widely used in the field of underwater communication because it is the only carrier thatManuscript received June 11, 2020; revised October 9, 2020; accepted December 7, 2020
This paper proposes a novel underwater acoustic signal denoising algorithm named AWMF+GDES, which is based on adaptive window median filter combined with wavelet threshold optimization
TrhBe ycocnotmribbuintiionngsthoefSthαiSs paper are as follows: distribution and the normal distribution, a new underwater acoustic (UWA) noise model is described and the energies of Gaussian noise and non-Gaussian impulsive noise are defined by signal-to-noise ratio (SNR) and mixed signal-to-noise ratio (MSNR), respectively
Summary
T HE acoustic wave is widely used in the field of underwater communication because it is the only carrier that. Based on three dynamic adjustment strategies to improve the optimization performance of PSO algorithm, Zhang et al [40] proposed a parameter wavelet threshold signal denoising method (MPSO) to optimize the wavelet threshold parameters. This paper proposes a novel underwater acoustic signal denoising algorithm named AWMF+GDES, which is based on adaptive window median filter combined with wavelet threshold optimization. WANG et al.: A NOVEL UNDERWATER ACOUSTIC SIGNAL DENOISING ALGORITHM FOR GAUSSIAN/NON-GAUSSIAN IMPULSIVE NOISE noise is suppressed. TrhBe ycocnotmribbuintiionngsthoefSthαiSs paper are as follows: distribution and the normal distribution, a new UWA noise model is described and the energies of Gaussian noise and non-Gaussian impulsive noise are defined by SNR and MSNR, respectively. The numerical simulations and the experimental results demonstrate and validate that the proposed AWMF+GDES method can effectively improve the reception performance of underwater acoustic signals.
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