A Novel Underwater Acoustic Signal Denoising Algorithm for Gaussian/Non-Gaussian Impulsive Noise

Gaussian/non-Gaussian impulsive noises in underwater acoustic (UWA) channel seriously impact the quality of communication. The common denoising algorithms are based on Gaussian noise model and difficult to apply coexistence noises. Therefore, a new UWA is described this paper by combining symmetric ?-stable (S?S) distribution normal distribution. Furthermore, novel signal algorithm called AWMF+GDES proposed. First, non-Gaussian adaptively suppressed adaptive window median filter (AWMF). Second, an enhanced wavelet threshold optimization with function proposed suppress noise. optimal parameters obtained good point set dynamic elite group guidance combined simulated annealing selection artificial bee colony (GDES-ABC) algorithm. numerical simulations demonstrate that convergence speed precision GDES-ABC can be increased 25%~66% 21%~73%, respectively, compared existing algorithms. Finally, experimental results verify effectiveness both method obtain higher output signal-to-noise ratio (SNR), suppression (NSR), smaller root mean square error (RMSE) other