Underwater target classification method

Abstract

The invention provides an underwater target classification method. The underwater target classification method comprises the following steps: converting a signal received by a sonar array into a digital signal; preprocessing the digital signal, calculating a cross correlation coefficient between each sonar and other sonars, summing the cross correlation coefficients, and taking the sonar signal with the maximum cross correlation coefficient sum as a reference signal; calculating the time delay of each sonar relative to the reference signal; and self-adapting the weight of each channel by usingthe cross correlation coefficient of the channels and the correlation between the front frame and the rear frame, and finally obtaining an enhanced signal; filtering the signal after framing, summingthe signal energy in each filter, and taking the logarithm as the characteristic of the frame signal; and taking the features as the input of a time delay neural network, outputting the features as the probability of each target type corresponding to the frame of signal, and training a multi-target classifier based on the rule. According to the method, the powerful nonlinear representation capability of the deep neural network is utilized, and the characteristics of the target are effectively utilized to distinguish the target.

Description

technical field [0001] The invention relates to an underwater target classification method, which tests and classifies unknown signals based on a trained multi-target classifier. Background technique [0002] The underwater target recognition technology is based on the radiation noise signal of the ship received by the sonar array to distinguish the type of the target. [0003] Due to the complexity and instability of the underwater acoustic signal, it is difficult to describe the prior mathematical knowledge of the underwater acoustic channel. Traditional classification methods such as support vector machines and decision trees cannot characterize the signal and channel well. Effectively distinguish underwater targets. Contents of the invention [0004] Aiming at the inability to effectively distinguish underwater targets in the prior art, the present invention proposes a classification method for underwater targets, which utilizes the powerful nonlinear representation c...

AI Technical Summary

Problems solved by technology

[0003] Due to the complexity and instability of the underwater acoustic signal, it is difficult to describe the prior mathematical knowledge of the underwater acoustic channel. Traditional classification methods such as support vector machines and decision trees cannot characterize the signal and channel well. Effectively distinguish underwater targets

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