Underwater maneuvering small target recognition method based on HHT and artificial neural network

An artificial neural network and recognition method technology, which is applied in the field of underwater mobile small target recognition, can solve the problem of low recognition rate of small underwater targets, and achieve the effect of strong self-learning ability and high recognition rate.

Inactive Publication Date: 2017-11-21
INST OF ACOUSTICS CHINESE ACAD OF SCI
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AI Technical Summary

Problems solved by technology

[0039] The purpose of the present invention is to solve the problem that the recognition rate of underwater small targets is not high due to the coexistence of frogmen, underwater robots, water surface speedboats, vocal mammals and other underwater mobile small targets in the current complex underwater environment. A method for underwater maneuvering small target recognition based on HHT and

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  • Underwater maneuvering small target recognition method based on HHT and artificial neural network
  • Underwater maneuvering small target recognition method based on HHT and artificial neural network
  • Underwater maneuvering small target recognition method based on HHT and artificial neural network

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[0096] Extract the radiated noise data of underwater maneuvering small targets from multiple sea tests and lake tests. First, use the data of underwater frogmen, vocal mammals, underwater robots, and surface speedboats to train the recognition system, and then use this system to identify underwater maneuvers. small goals.

[0097] like image 3 As shown, the recognition method of the present invention accurately recognizes the category to which the target belongs. The classification results show that the recognition rate of the underwater mobile small target recognition method based on HHT and artificial neural network proposed by the present invention can reach more than 90%. It has good classification results and adaptability to underwater maneuvering small targets, and can be used for the classification of underwater maneuvering small targets.

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Abstract

The invention provides an underwater maneuvering small target recognition method based on the HHT and an artificial neural network. The method includes the steps of extracting a HHT feature of a signal x(t) to be recognized: a Hilbert marginal spectrum, and extracting a HHT feature quantity from the Hilbert marginal spectrum; subjecting the signal x(t) to be recognized to Fourier transform, and extracting a peak frequency and 3dB bandwidth thereof; mixing the HHT feature quantity, the peak frequency and the 3dB bandwidth to construct a HHT mixed feature vector; and finally, inputting the HHT mixed feature vector into a trained artificial neural network classifier for recognition, and outputting the recognized type. The method of the invention makes full use of the adaptability of the HHT to signals, the advantages of processing non-stationary signals and the characteristics of the time-frequency domain of underwater small target radiated noise signals, and the extracted high-dimensional feature quantity can fully describe the features of an underwater target; and the recognition rate of the underwater maneuvering small target is improved.

Description

technical field [0001] The invention relates to the field of underwater maneuvering small target recognition, in particular to an underwater maneuvering small target recognition method based on HHT and artificial neural network. Background technique [0002] During the Cold War, countries were on war alert, and the objects of maritime detection and defense were mainly large targets such as ships and submarines of hostile countries. With the end of the Cold War, especially after the disintegration of the former Soviet Union, the miniaturization of underwater weapons and equipment has developed rapidly, and the technical equipment such as frogmen, underwater vehicles, and underwater robots has become increasingly mature. This type has good concealment and destructive power. The attack methods with obvious "asymmetrical" advantages such as strong are favored by terrorists and have become an important method for terrorists to carry out terrorist activities. [0003] In recent y...

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Application Information

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IPC IPC(8): G06K9/62G06N3/08
CPCG06N3/08G06F18/2111
Inventor 许枫宋宏健闫路
Owner INST OF ACOUSTICS CHINESE ACAD OF SCI
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