High Resolution DOA Estimation Based On Vector Hydrophone Array

The vector hydrophone can pick up the sound pressure and vibration velocity information in the sound field.Compared with the traditional sound pressure array,the vector array has the advantages of strong anti-interference and side-to-side resolution,and has better applicability in harsh environments.Based on the summary of spatial spectrum estimation and the research status of vector hydrophones,this paper mainly studies the conventional beamforming improvement algorithm and high-resolution DOA estimation algorithm based on vector array.The narrowband and wideband signal models are discussed.Then the array signal models of sound pressure array and vector array are discussed respectively.Based on this,two classical DOA estimation algorithms are discussed.The conventional beamforming based on vector array and its improved algorithm are studied.The narrow-band beamforming algorithm based on joint processing of sound pressure and velocity is studied.This method reduces the amount of calculation and the beam output side lobes,and improves the side-to-side suppression gain.The vector array wideband beamforming algorithm based on all-phase preprocessing is studied,which effectively reduces the side lobes of the beam output,improves the output signal-to-noise ratio of the array,and reduces the computational complexity.The research proposes a vector matrix-based covariance matrix reset.The wideband beamforming algorithm further reduces the side lobes of the beam output.Simulation experiments verify the effectiveness of the three algorithms.High-resolution DOA estimation based on vector matrix is studied.Aiming at the problem of low performance of vector array high-resolution DOA estimation under low SNR and small sample conditions,a vector array wideband adaptive beamforming method based on dominant mode rejection is studied.This algorithm avoids the data covariance matrix singularity under small sample conditions.The irreversible problem improves the azimuth estimation performance of weak targets in the case of strong interference background and small samples.The research proposes a minimum variance undistorted adaptive beamforming method based on signal self-nulling,The algorithm reduces the main lobe width of the spatial spectrum and improves the azimuth estimation performance at low SNR and small sample conditions.Simulation experiments verify the effectiveness of the two algorithms.