High-resolution Localization And Identification Method Of Underwater Noise

Radiation noise is an important index arm for measuring the fighting capacity and viability of submarine,and it directly affects the submarine acoustic stealth performance.For pertinently carrying out radiation noise measurement and analysis,as well as reducing submarine underwater noise and improving the acoustic stealth performance is very crucial to develop its combat mission.Therefore,enhancing the level of underwater noise measurement of large structures,determining the spatial distribution of the noise sources and estimating the strength of the various noise sources is very significant to improve the comprehensive performance of acoustic stealth.In order to realize the high-resolution localization and identification of the underwater noise sources,this paper research some methods from the spatial spectrum estimation,array preprocesses and post-processing respectively to solve the limitations and many defects of the existing high-resolution algorithm which is applied in the underwater acoustic system.Traditional high-resolution algorithms typically have the following drawbacks:(i)they cannot identify the noise source absolute strength;(ii)their radiation patterns are not well defined;(iii)the coherency of sources is usually unknown,or noise source may not be compact.To resolve these problems,By the Lp norm eigenvalue decomposition approach a high-resolution method of complex sound sources localization and identification is studied.According to signal subspace method principle,the signal reconstruction model in each feature subspace is established via pre-defining sound source types for the reference solutions,then utilizes the sparse constraint condition of Lp norm to calculate the optimal solution and obtain the high-resolution localization and identification effects of complex sound sources.The theory and simulation analysis show that comparing with several existing beamforming algorithms,the proposed method not only can obtain the localization results,but also can reflect the absolute contribution of each coherent source.The method is capable of locating and identifying multi-complex sources with high-precision,high-resolution and reasonable computational cost.The parameters affecting the performance of sources identification are reasonably chosen by numerical simulations.In addition,the correctness and superiority of the algorithm is verified through experiments.For solving the P-EVD algorithm during the localization and identification of multiple noise sources is limited by number of array elements,the beamforming regularization matrix for array extrapolation is established according to the principle of sound field reconstruction,on the basis of the standard Tikhonov regularization algorithm,a data-dependent discrete smoothing norm for the regularization of the inverse problem is defined by a priori beamforming measurement.By this priori information,this method achieve the largest extrapolation region around the measuring area and breaks through the array elements limitation of P-EVD algorithm,while expanding the frequency range of conventional algorithm and improving the spatial resolution without adding extra sensors or changing the layout of sensor array.The typical numerical example and experiment validate the correctness of theoretical analysis,and the influence of related parameters to reconstruction precision is investigated.A method for noise sources localization by spherical array beamforming in confined spaces is studied.A high-resolution spherical array beamforming based on virtual sources(VSSFB)is given on the principle of conventional spherical array beamfomring algorithm.Subsequent,the performance of VSSFB shows that this method can realize high-precision,high-resolution and ideal three-dimensional noise sources localization in the full band.On this basis,an iterative weighted VSSFB algorithm is studied by means of the relationship of the virtual sound sources strength which is inversely proportional to the distance between measuring array to the respective interfaces to weaken the "false sources" interference caused by reflection.The scope and precision of the method is analyzed through several examples to provide a reference for the next practical engineering applications.