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

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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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 artificial neural network is proposed. This method uses the improved HHT method to extract the features of small targets, and then uses neural network to identify these features. This method improves the accuracy of small underwater targets. Recognition rate, able to deal with the threats and attacks of these small targets on the near shore to the property of near shore underwater facilities

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