Acoustic array near-field source ESPRIT and MUSIC parameter estimation method

Abstract

An acoustic array near-field source ESPRIT and MUSIC parameter estimation method is provided. An array receives K uncorrelated narrowband random steady near-field sound source signals with different frequencies. Two groups of received signals ahead and after a delay tap and received by the array form full array received signals. A signal data autocorrelation matrix is subjected to characteristic decomposition to obtain the estimated values of an array steering vector matrix and the frequency. A rotation-invariant relation between four sub array steering vectors is obtained from the estimated value of the array steering vector. The rough estimated values of a signal azimuth angle, a pitch angle, and a distance are obtained according to a rotation-invariant relation matrix. A MUSIC spectrum peak search method is used to obtain the accurate estimated values of the azimuth angle, the pitch angle and the distance in a small area near the rough estimated values. The method breaks through the limitation of a conventional linear array parameter estimation method and the super large calculated amount of the full-domain 3D search of a single MUSIC method, combines the advantages of the ESPRIT method and the MUSIC method, requires no parameter matching operation, greatly reduces the calculated amount and improves parameter estimation accuracy.

Description

technical field [0001] The invention belongs to the technical field of array signal processing, and in particular relates to a method for estimating near-field source parameters of an L-shaped acoustic vector sensor array. Background technique [0002] Determining the arrival direction and distance of acoustic signals is an important application field of acoustic signal processing. Traditional acoustic signal direction finding uses an array of sound pressure sensors that can only measure sound pressure intensity. Different from traditional sound pressure sensors, the sound vector sensor of the present invention is composed of three mutually perpendicular sound velocity sensors and a sound pressure sensor at the same point in space. The vector sensor can measure both sound pressure intensity information and The vibration velocity information of the acoustic signal is therefore increasingly widely used in sound source localization. The traditional far-field acoustic wave sign...

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Problems solved by technology

[0003] The subspace method with high-resolution performance has been applied to the localization of near-field sources. In the paper "Multi-parameter Estimation of Near-field Sources Based on Acoustic Vector Sensors" published by Liu Nannan (Jilin University, 2014 master's degree thesis), the method based on uniform acoustic vector The near-field source parameter estimation method of the sensor line array, the near-field source parameter estimation method based on the double quaternion MUSIC is proposed for the Gaussian white noise condition, the existing methods are all based on the linear array parameter estimation method, and the linear array requires the signal to be The incident from the yoz plane can only estimate the one-dimensional arrival angle and distance, and cannot give the two-dimensional arrival angle, that is, the algorithm fails when the signal is not incident from the yoz plane

For the two-dimensional parameter estimation multi-signal classification method (MUSIC), the accuracy of parameter estimation is limited by the search step size. To improve the accuracy, the search step size must be reduced, and the amount of calculation will be greatly increased.

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