Ship radiation signal recognition method based on multi-kernel learning and discriminant analysis

A technology of radiation signal and discriminant analysis, applied in the field of ship radiation signal recognition, can solve the problems of inaccurate selection, cost, and inability of large labor.

Active Publication Date: 2014-11-19
SOUTHEAST UNIV
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Problems solved by technology

[0005] Technical problem to be solved: Aiming at the deficiencies in the prior art, the present invention proposes a ship radiation signal recognition method based on Multiple Kernel Learning (Fisher) Discriminant Analysis (MKL-FDA for short here). auditory model features, using MKL-FDA for dimensionality reduction training, to solve the existing tech

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  • Ship radiation signal recognition method based on multi-kernel learning and discriminant analysis
  • Ship radiation signal recognition method based on multi-kernel learning and discriminant analysis
  • Ship radiation signal recognition method based on multi-kernel learning and discriminant analysis

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[0098] The present invention will be further described below in conjunction with the accompanying drawings.

[0099] Such as figure 1 Shown is the flowchart of the present invention.

[0100] A ship radiation signal identification method based on multi-core learning discriminant analysis, which randomly divides several ship radiation signal samples in the ship radiation signal database into a training sample set and a test sample set in proportion, in which each ship radiation signal sample Each has a ship class label characterizing its origin, consisting of the following steps performed in sequence:

[0101] Step 1, ship radiation signal sample preprocessing: pre-emphasize the ship radiation signal sample, then frame the time-domain signal of the pre-emphasized ship radiation signal sample, and perform energy normalization on each frame signal ;

[0102]Step 2, ship radiation signal feature extraction: for each frame of the ship radiation signal sample processed in step 1,...

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Abstract

The invention discloses a ship radiation signal recognition method based on multi-kernel learning and discriminant analysis. According to the method, pretreatment, auditory sense model feature extraction, dimensionality reduction and classifier classification and judgment are sequentially conducted on a ship radiation signal sample, wherein in the stage of dimensionality reduction, a method based on multi-kernel learning and discriminant analysis is adopted, alternate optimization is utilized, and optimization operation is conducted on kernel mapping coefficients and linear multi-kernel combination coefficients respectively under the goal of kernel discriminant analysis optimization represented in a graph embedding mode. Compared with the prior art, on the aspect of ship radiation signal recognition, the recognition performance of a system can be improved effectively.

Description

technical field [0001] The invention belongs to the field of ship radiation signal recognition, in particular to a ship radiation signal recognition method based on multi-core learning discriminant analysis. Background technique [0002] The analysis of ship radiation signal is a necessary step for underwater ship target recognition through underwater acoustic signals. The ship’s radiation noise received by sonar can judge the type of ship target or even a series of targets at a relatively long distance. Specific ship parameters. Ship radiation signals come from various factors such as machinery, propellers, water flow, etc. Therefore, the analysis of ship radiation signals is a complicated task for both manual and machine. As a key step in the analysis and identification of ship radiation signals, the reduction of the characteristic dimension of ship radiation signals is of great significance for extracting features that are beneficial to identify different ships. At pres...

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Application Information

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IPC IPC(8): G06F19/00
Inventor 郑文明徐新洲赵力罗昕炜黄程韦余华吴尘查诚
Owner SOUTHEAST UNIV
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