Radiation source individual identification method and device based on convolutional neural network, and computer storage medium

Abstract

The embodiment of the invention discloses a radiation source individual identification method and a device based on a convolutional neural network, and a computer storage medium. The method can comprise the following steps: acquiring emission signals of a plurality of radiation sources which have the same model and are in the same working mode to obtain acquired emission signals; establishing a data set for training a convolutional neural network according to the acquired emission signals; constructing a convolutional neural network model; training the convolutional neural network model by using the established data set to obtain a trained convolutional neural network model; acquiring a target emission signal of any target radiation source in the plurality of radiation sources, and inputting the target emission signal to the trained convolutional neural network model by using a forward propagation algorithm, obtaining the output of the trained convolutional neural network model, and identifying a target radiation source corresponding to the target emission signal based on the output.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of wireless communication, and in particular, to a convolutional neural network-based individual radiation source identification method, device, and computer storage medium. Background technique [0002] In the field of modern informationized electronic countermeasures, electronic reconnaissance has become one of the important technical means to obtain enemy intelligence. With the rapid development of technical means such as signal analysis and information analysis, and with the efficient transmission of information by the Internet and mass media, It makes a lot of information that could not be used in the past can be used. For example, through our radio reconnaissance equipment, we can effectively intercept the enemy's radiation source signals, and use technical means such as parameter estimation and signal sorting to realize the classification and identification of signals, and at the...

AI Technical Summary

Problems solved by technology

The current conventional classification and identification methods are not ideal for individual identification of radiation sources, and the identification accuracy and practicability cannot achieve satisfactory results.

With the rapid development of electronic information technology and the increasing complexity of the electromagnetic environment, conventional technical solutions have been difficult to meet the needs of the modern information battlefield. Therefore, under the condition of limited signal samples, how to find a more universal and It is an important issue in the field of modern information electronic reconnaissance to use a practical method to fully mine the subtle characteristics of the signal reflected in the sample, so as to use the correlation between the signal and the individual radiation source to realize the effective identification of the individual radiation source.

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