Research On Complex Ocean Noise Suppression Method Based On Underwater Acoustic Array Beamforming Tehnology

Acoustic waves are currently the only information carriers that can travel long distances in the ocean,which are widely used in the field of underwater acoustic engineering.However,in the actual underwater acoustic channel,the acoustic waves generated by anthropogenic and natural interact with the sea surface,seafloor and water body during the propagation,forming a complex background noise field.Which seriously limits the effective and stable propagation of acoustic signals,and brings great challenges to signal reception,detection,estimation and processing.Moreover,in the shallow ocean environment,the above effects are further intensified due to the non-uniform seawater medium and the obvious change of ocean water temperature with depth.Based on the spatial characteristics of signals,the technology of array signal processing shows advantages in underwater signal processing.In the research process of this paper,the factors such as the types,states and properties of underwater acoustic signals are fully considered.Combining optimization theory,noise suppression technology,and beamforming theory,the signal processing methods are explored to improve the reception performance of underwater signal.The main innovations of this paper are as follows:1.Propose an underwater acoustic signal denoising method based on adaptive window median filter combined with wavelet threshold optimization.Gaussian/non-Gaussian impulsive noise in underwater acoustic channel have a serious impact to the quality of underwater acoustic communication.Common denoising algorithms are based on Gaussian noise model,which are difficult to apply to the coexistence of Gaussian/non-Gaussian impulsive noise.Therefore,a novel underwater acoustic signal denoising algorithm based on adaptive window median filter combined with wavelet threshold optimization is proposed in this paper,which is recorded as AWMF+GDES algorithm.Firstly,combined symmetric?-stable(S?S)distribution model and normal distribution model,Gaussian/non-Gaussian impulsive noise in underwater acoustic channel are described.Secondly an adaptive window median filter(AWMF)is proposed to suppress non-Gaussian impulsive noise.And based on an improved artificial bee colony algorithm based on good point set and dynamic elite group guidance combined simulated annealing selection(GDES-ABC),a wavelet threshold optimization algorithm is proposed to suppress Gaussian noise.The simulation results show that the proposed GDES-ABC algorithm has faster convergence speed and higher convergence precision;and the underwater acoustic signal denoising method based on AWMF+GDES can obtain higher output signal-to-noise ratio(SNR)and noise suppression ratio(NSR).2.Propose a new beamformer for suppressing of multiple unsteady sub-Gaussian interferers.Traditional beamforming(BF)methods can be used to suppress the Gaussian interferers in underwater acoustic communication systems.However,multiple unsteady sub-Gaussian interferers may exist that degrade the performance of BF.In order to solve this problem,based on considering the number,state and nature of interferers,a new beamformer named SMUSGI is established by minimizing the l_p norm of the received data and setting the maximum output power of interferers.Then based on the optimization theory,the optimal weight vector of this beamformer is obtained.Compared with the previous beamformer,the method proposed in this paper effectively suppresses multiple unsteady sub-Gaussian interferers in underwater acoustic communication,and can obtain higher output signal-to-interference-noise ratio(SINR),faster convergence speed,stronger universality and robustness,and is more suitable for underwater acoustic communication.The research results of this paper lay a solid theoretical foundation for solving the performance degradation of underwater acoustic communication system in complex ocean environment,and promote the development and application of high-speed and reliable underwater wireless transmission system.They have both theoretical value and practical application value.