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Research On DOA Estimation Of Underwater Target Based On Acoustic Vector Circular Array

Posted on:2022-10-21Degree:MasterType:Thesis
Country:ChinaCandidate:H Y LiFull Text:PDF
GTID:2492306350981299Subject:Underwater Acoustics
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The acoustic vector circle array is widely used in sonar systems such as dipping sonar and buoy sonar.At present,the array model considered by most vector array signal processing methods is linear array.Compared with linear array,the signal processing technology based on vector circular array model starts late,and the research in this field has important application value.Therefore,this paper studies the underwater DOA estimation technology based on the acoustic vector circle array.By studying and analyzing the limitations of the existing high-resolution azimuth estimation algorithms based on vector circular array,combined with spatial spectrum estimation theory,compressed sensing theory and the idea of joint processing,several solutions and methods more suitable for practical engineering are proposed.Aiming at the problem that high-resolution spatial spectrum estimation algorithms have a large amount of calculation in practical engineering applications,this paper combines the idea of compressed spectrum and vector joint processing,and proposes a fast MVDR azimuth estimation method based on a centrosymmetric sound vector circular array.Simulation and lake test results verify that the algorithm proposed in this paper can obtain complete and accurate azimuth information in the half-spectrum search,and verify that the joint processing method of sound pressure and vibration velocity can reduce the matrix dimension and play the anti noise advantage of vector hydrophone.When the number of array elements is 8 and the step size is0.2 °,the operation time of this method is about half of that of the traditional method.With the increase of the number of array elements and the number of search points,the efficiency advantage of this method is more obvious.Subsequently,the idea of a fast azimuth estimation method based on the symmetry of the center of the vector circular array is extended to the MUSIC beamformer,which makes it more widely used.The two fast azimuth estimation methods based on centrosymmetric sound vector circular arrays proposed in this paper improve the computational complexity of traditional high-resolution algorithms,enrich the applicable arrays of compressed spectrum methods,and provide a new idea for other underwater circular array signal processing methods.Aiming at the limitation of the existing DOA estimation methods based on CS theory that it has high computational complexity and is difficult to apply to vector arrays,the flow pattern of vector circular array is transformed into a form similar to uniform linear array by mode space transformation,the idea of joint processing of acoustic pressure and velocity is introduced to reduce the dimension,the sparse representation and reconstruction method of underwater acoustic signal in mode domain are studied,and finally an underwater narrowband signal DOA estimation method based on sparse representation of mode space cross covariance of vector circular array is proposed.Then,combined with the idea of CSM wideband signal processing algorithm,by constructing a suitable focus matrix,this method is extended to wideband signals,and a wideband signal DOA estimation method based on the sparse representation of vector circular array cross-covariance is proposed.Theoretical analysis,simulation and lake experiment show that this method can reduce the dimension of vector signal matrix,and make full use of the relevant information of received signal.Theoretical analysis,simulation and lake experiment show that this method can reduce the dimension of vector signal matrix,and make full use of the relevant information of received signal.It can achieve high-resolution DOA estimation of underwater targets in CS framework.
Keywords/Search Tags:DOA estimation, compressed sensing, low complexity, acoustic vector circular array, spatial spectrum estimation
PDF Full Text Request
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