Research On Signal Denoising And Direction-finding Technology Of MEMS Vector Hydrophone

Hydroacoustic engineering has a wide range of applications in underwater submarine monitoring,marine resource exploration,etc.The development of its technology has important strategic significance for the safety of my country's sea areas and the development of marine resources.Hydrophone is the key equipment to obtain underwater acoustic signals.In the traditional underwater acoustic engineering application,the array composed of sound pressure hydrophone is usually used to collect the sound signal,and the sound field information is single.The emergence of MEMS vector hydrophone enables researchers to obtain more abundant sound field information,and because it has the characteristics of light weight,high performance and easy to produce,it has greater application potential in underwater acoustic engineering.So the signal processing technology based on MEMS vector hydrophone has important research value.The ocean is a complex environmental system.The strong interference of ocean noise makes it extremely difficult to collect a large amount of high-quality underwater acoustic data in a short time,which also poses a huge challenge to the real-time processing of underwater acoustic signals.Based on this background,this article relies on the bionic ciliated MEMS vector hydrophone developed by North University of China,combined with its engineering application,aiming at signal denoising and baseline drift removal in strong interference environment,signal orientation in low SNR and small snapshot condition,real-time signal processing in complex environment,and stability of signal denoising and orientation algorithm in engineering application,the following work is carried out:(1)Aiming at the problem of signal denoising and baseline drift removal in a strong interference environment,a MEMS vector hydrophone signal denoising and baseline drift removal algorithm based on whale-optimized variational modal decomposition and correlation coefficients is proposed.First,select the power spectrum entropy as the fitness function of the whale optimization algorithm to find the decomposition level and penalty factor parameters of the variational modal decomposition algorithm;Then,using the VMD algorithm after obtaining the parameters,the original signal is decomposed to obtain the intrinsic mode functions(IMFs),and calculating the correlation coefficients(CC)between the IMFs and the original signal.Finally,the CC threshold is used to remove the noise IMFs,and the rest of the useful IMFs are reconstructed to complete the denoising and baseline drift removal process of the original signals.Simulation experiments and MEMS vector hydrophone signal denoising experiments have verified the excellent performance of the algorithm.This work has a significant effect in removing noise from signal baseline drift,it retains more effective information in the original signal while removing signal noise.(2)Aiming at the signal orientation problem under the condition of low SNR and small snapshot,a direction of arrival(DOA)estimation algorithm based on the principle of compressed sensing and density spatial clustering is proposed.First,the algorithm selects the DOA estimation strategy of basis pursuit de-noising.In response to the challenge of the selection of regularization parameters in this strategy,the power spectrum entropy is proposed to characterize the noise intensity of the signal,so as to provide reasonable suggestions for the selection of regularization parameters;Then,this paper finds out that the DOA estimation based on the principle of CS will get a denser estimation near the real angle under the condition of small snapshots through analysis,so it is proposed to use a DBSCAN method to process the above data to obtain the final DOA estimate;Finally,calculate the cluster center value of each cluster,the number of clusters is the number of signal sources,and the cluster center value is the final DOA estimate.The algorithm does not need to know the number of signal sources in advance,and it can obtain a good DOA estimation effect under the condition of-10 d B signalto-noise ratio and 10 snapshot data.The effective estimation of blast wave signal can also be obtained in the engineering application of MEMS vector hydrophone.(3)Aiming at the problem of real-time signal processing under complex conditions,an improved maximum likelihood DOA estimation algorithm is proposed.By improving the nonlinear harmonic index of the invasive weed optimization algorithm,the performance of the algorithm is greatly improved.The improved algorithm is used to search the optimal solution of the DOA direction likelihood function,so as to achieve fast and accurate DOA estimation.The simulation experiment verified the excellent performance of the algorithm in terms of convergence and calculation accuracy.It was applied to the real-time course tracking experiment of the speedboat by the MEMS vector hydrophone,and good results were achieved.(4)Aiming at the stability of the signal denoising and orientation algorithm in engineering applications,this part of the work is based on the analysis of the signal characteristics in actual engineering applications,and proposes a joint application idea of signal denoising and orientation algorithms.The signal denoising and directional algorithm are jointly applied to the actual engineering application experiment of MEMS vector hydrophone,which proves that the performance of the joint application algorithm in engineering application is better and more stable.Based on MEMS vector hydrophone,the research on signal denoising and directional technology of MEMS vector hydrophone under complex environmental conditions is carried out in this work.The purpose is to achieve better underwater acoustic engineering application.It is expected to lay a foundation for the theoretical development of underwater acoustic signal processing and provide technical support for the engineering application of MEMS vector hydrophone.