Blind source separation method for multiple submarine feature signals in marine environment

A characteristic signal and blind source separation technology, applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems of complex signal separation process and low operation efficiency, and achieve the effect of improving operation efficiency and simplifying complexity

Active Publication Date: 2018-07-20
XIAMEN UNIV
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Problems solved by technology

In addition, the above algorithm needs to estimate any mixed signal matrix or source position in the mask estimation, which makes the signal separation process relatively complicated and the operation efficiency is not high

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  • Blind source separation method for multiple submarine feature signals in marine environment
  • Blind source separation method for multiple submarine feature signals in marine environment
  • Blind source separation method for multiple submarine feature signals in marine environment

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Embodiment 1

[0026] see figure 1 , the invention discloses a method for blind source separation of characteristic signals of multiple submarines in a marine environment, comprising the following steps:

[0027] S1. Collect mixed signal samples.

[0028] S2. In the time-frequency domain, based on the sample vector and reference vector of the Hermitian (Hermitian matrix) angle, the clustering algorithm is used to cluster the mixed signal samples to obtain multiple clusters, and the membership function in the clustering algorithm is used as mask. The clustering algorithm adopts K-means clustering or fuzzy C-means clustering algorithm.

[0029] S3. Perform cluster verification based on the estimated number of clusters.

[0030] S4. Based on the K-means clustering algorithm, the masks are clustered into Q mask clusters, denoted as c q ,q=1,...Q, and satisfy D q , q=1,..., the sum of Q is the smallest, D q is the total distance between the mask and the centroid of the cluster in the qth cl...

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Abstract

The invention discloses a blind source separation method for multiple submarine feature signals in a marine environment, which comprises the steps of collecting signal samples; performing clustering on mixed signal samples by adopting a clustering algorithm to obtain multiple clustering clusters based on a sample vector and a reference vector of a Hermitian angle in the time and frequency domain,and taking membership functions in the clustering algorithm to serve as masks; performing clustering verification based on the estimated cluster number; clustering the masks into Q mask clustering clusters based on a K-mean clustering algorithm; and performing signal separation through code estimation. The blind source separation method can solve a problem of blind source separation in an underdetermined condition, and the position of any mixed signal matrix or source is not required to be estimated in mask estimation, so that the complexity of signal separation is simplified, and the operation efficiency is improved.

Description

technical field [0001] The invention relates to the field of underwater acoustic signal processing, in particular to a method and system for blind source separation of characteristic signals of multiple submarines in a marine environment. Background technique [0002] There are many factors in the current blind separation algorithm. First, the blind separation algorithm is mainly used in the transient mixed form of the signal. There are relatively few blind separation algorithms in the signal convolution mixed form, which can be roughly divided into the following categories: 1) Based on the elimination of signal A signal separation network for cross-correlation between components that exploits feedback circuits to solve the problem. This algorithm has great defects in practical applications. When the scales of the signals differ greatly or the mixing matrix is ​​ill-conditioned, the separation effect is relatively poor, and even the signals cannot be separated. 2) Transform...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/00
CPCG06F2218/08G06F18/23213
Inventor 孙海信王连生成垦沈艺珊蔚然王远旭陈海兰孙伟涛苗永春
Owner XIAMEN UNIV
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