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Wavelet line spectrum feature extraction method and system for underwater target recognition

A feature extraction and underwater target technology, applied in character and pattern recognition, instruments, biological neural network models, etc., can solve problems such as poor classification results and inability to better express data feature extraction, and achieve accurate classification results

Pending Publication Date: 2021-07-09
INST OF ACOUSTICS CHINESE ACAD OF SCI +1
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AI Technical Summary

Problems solved by technology

[0004] In the underwater target recognition task, the feature extraction method and the classifier are adapted to each other. After using the deep neural network as the classifier of the underwater target recognition system, the traditional feature extraction method has poor classification results when the signal-to-noise ratio is low. , cannot better express the feature extraction of the data

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  • Wavelet line spectrum feature extraction method and system for underwater target recognition
  • Wavelet line spectrum feature extraction method and system for underwater target recognition
  • Wavelet line spectrum feature extraction method and system for underwater target recognition

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Embodiment Construction

[0058] The present invention will be further described now in conjunction with accompanying drawing.

[0059] The invention provides a wavelet line spectrum feature extraction method for underwater target recognition. The method uses wavelet transform on the basis of array beamforming signals to perform time-frequency decomposition on target signals under multi-resolution angles, and then uses The wavelet coefficient of the target frequency band reconstructs the signal and performs line spectrum analysis, which can effectively avoid noise interference, make the line spectrum characteristics of the target be better expressed, and propose a corresponding optimization algorithm.

[0060] Such as figure 1 As shown, the method includes:

[0061] Spectrum analysis is performed on the signal received by the sonar array to obtain spectrum information in each frequency band;

[0062] Specifically, beamforming is performed on the signal received by the sonar array to obtain the target...

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Abstract

The invention belongs to the technical field of underwater target recognition and signal processing, and particularly relates to an underwater target recognition method based on wavelet line spectrum feature extraction, and the method comprises the steps of carrying out the spectrum analysis of a signal received by a sonar array, and obtaining the spectrum information in each frequency band; based on the obtained frequency spectrum information in each frequency band, extracting a maximum value of a line spectrum feature in a single frequency band as a feature vector of the current frequency band, and obtaining a feature vector of each frequency band; splicing or averaging the feature vectors of all the frequency bands to obtain optimized feature vectors; and taking the feature vector of the current frequency band and the optimized feature vector as a new feature vector, inputting the new feature vector into a pre-trained time delay neural network, and outputting target category information corresponding to the current frequency band as a classification result.

Description

technical field [0001] The invention belongs to the technical field of underwater target recognition and signal processing, and in particular relates to a wavelet line spectrum feature extraction method and system for underwater target recognition. Background technique [0002] The extraction of characteristic parameters of underwater target signals is a research topic that has attracted much attention, and it has very important theoretical significance and engineering application value in both military and civilian fields. For a long period of time in the past, people have been using traditional signal processing theory as the basis for feature extraction of underwater acoustic signals, that is, to describe underwater acoustic signals with stationarity and randomness, and to use time domain and frequency domain parameters as characteristic parameters. [0003] The most critical technology in object recognition is feature extraction. Whether the feature parameters are effec...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N3/04
CPCG06N3/049G06F2218/12G06F2218/08
Inventor 徐及任佳威颜永红
Owner INST OF ACOUSTICS CHINESE ACAD OF SCI
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