A method for detecting the number of sources of acoustic vector circular array based on eigenvalue multi-threshold correction

Abstract

The invention belongs to the acoustic vector sensor array signal processing field, and more specifically relates to an acoustic vector circular array source number detection method based on characteristic value multiple threshold correction which is applied to underwater target remote passive detection. The method comprises establishing an acoustic vector circular array signal receiving model, obtaining acoustic vector circular array receiving acoustic pressure data, radial vibration velocity data and tangential vibration velocity, constructing a covariance matrix of acoustic vector circular array acoustic pressure and vibration velocity combined treatment, and decomposing characteristic values; and performing multiple threshold division treatment on a characteristic value set obtained by decomposing the covariance matrix to obtain a signal and noise corresponding characteristic value set. The method dynamically integrates an information theory detection method based on characteristic value multiple thresholds and the sound anti-noise performance of an acoustic vector circular array, obviously reduces the signal to noise ratio threshold of a detection algorithm, and overcomes the disadvantages that traditional detection methods such as MDL, diagonal loading MDL, and GDE are more sensitive to noise characteristic value change.

Description

technical field [0001] The invention belongs to the field of acoustic vector sensor array signal processing, and in particular relates to an acoustic vector circular array signal source number detection method based on eigenvalue multi-threshold correction, which is applied to remote passive detection of underwater targets. Background technique [0002] Estimation of the number of sources is an important issue in array signal processing. High-resolution spatial spectrum estimation technology generally needs to estimate the number of sources accurately first, otherwise it will lead to a decrease in the performance of the azimuth estimation algorithm. Therefore, in the fields of radar, sonar, communication, etc. Has a wide range of applications. [0003] With the continuous development of acoustic vector sensor technology, vector hydrophones are widely used in various fields of underwater acoustic engineering. Vector hydrophone array signal processing can effectively improve ...

AI Technical Summary

Problems solved by technology

The present invention proposes an acoustic vector circular array signal source number detection method based on eigenvalue multi-threshold correction, which overcomes the traditional minimum description length criterion (MDL), diagonally loaded MDL, Geiger's circle detection criterion (GDE), etc. The detection method is sensitive to the change of the noise characteristic value, but cannot apply the joint processing method of sound vector circular array sound pressure vibration velocity

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